A novel integrated microfluidic chip for on-demand electrostatic droplet charging and sorting

On-demand droplet sorting is extensively applied for the efficient manipulation and genome-wide analysis of individual cells.However,state-of-the-art microfluidic chips for droplet sorting still suffer from low sorting speeds,sample loss,and labor-intensive preparation procedures.Here,we demonstrate the development of a novel microfluidic chip that integrates droplet generation,on-demand electrostatic droplet charging,and high-throughput sorting.The charging electrode is a copper wire buried above the nozzle of the microchannel,and the deflecting electrode is the phosphate buffered saline in the microchannel,which greatly simplifies the structure and fabrication process of the chip.Moreover,this chip is capable of high-frequency droplet generation and sorting,with a frequency of 11.757 kHz in the drop state.The chip completes the selective charging process via electrostatic induction during droplet generation.On-demand charged microdroplets can arbitrarilymove to specific exit channels in a three-dimensional(3D)-deflected electric field,which can be controlled according to user requirements,and the flux of droplet deflection is thereby significantly enhanced.Furthermore,a lossless modification strategy is presented to improve the accuracy of droplet deflection or harvest rate from 97.49% to 99.38% by monitoring the frequency of droplet generation in real time and feeding it back to the charging signal.This chip has great potential for quantitative processing and analysis of single cells for elucidating cell-to-cell variations.

Joint Optimization for on-Demand Deployment of UAVs and Spectrum Allocation in UAVs-Assisted Communication

To improve the efficiency and fairness of the spectrum allocation for ground communication assisted by unmanned aerial vehicles(UAVs),a joint optimization method for on-demand deployment and spectrum allocation of UAVs is proposed,which is modeled as a mixed-integer non-convex optimization problem(MINCOP).An algorithm to estimate the minimum number of required UAVs is firstly proposed based on the pre-estimation and simulated annealing.The MINCOP is then decomposed into three sub-problems based on the block coordinate descent method,including the spectrum allocation of UAVs,the association between UAVs and ground users,and the deployment of UAVs.Specifically,the optimal spectrum allocation is derived based on the interference mitigation and channel reuse.The association between UAVs and ground users is optimized based on local iterated optimization.A particle-based optimization algorithm is proposed to resolve the subproblem of the UAVs deployment.Simulation results show that the proposed method could effectively improve the minimum transmission rate of UAVs as well as user fairness of spectrum allocation.

A distributed on-demand bandwidth-constrained multicast routing protocol for wireless ad hoc networks

To meet the bandwidth requirement for the multicasting data flow in ad hoc networks, a distributed on- demand bandwidth-constrained multicast routing （BCMR） protocol for wireless ad hoc networks is proposed. With this protocol, the resource reservation table of each node will record the bandwidth requirements of data flows, which access itself, its neighbor nodes and hidden nodes, and every node calculates the remaining available bandwidth by deducting the bandwidth reserved in the resource reservation table from the total available bandwidth of the node. Moreover, the BCMR searches in a distributed manner for the paths with the shortest delay conditioned by the bandwidth constraint. Simulation results demonstrate the good performance of BCMR in terms of packet delivery reliability and the delay. BCMR can meet the requirements of real time communication and can be used in the multicast applications with low mobility in wireless ad hoc networks.

Comparative study of on-demand and daily use of sertraline in treatment of premature ejaculation:A randomized clinical trial

Objective:The intravaginal ejaculatory latency time(IELT)may increase less in on-demand compared to daily intake,but may fulfill a suitable treatment for specific patients.We decided to compare the efficacy and safety of on-demand and daily use of sertraline in order to find the most effective and least complicated method in treatment of premature ejaculation(PE).Methods:This study was parallel or concurrent control randomized clinical trial.Two hundred and forty patients with PE diagnosed by urologist in the two groups of 120 from July 2017 to February 2019 enrolled in the study.In the first group,it is prescribed 50 mg sertraline each 12 h daily and the second group received 50 mg 4 h before coitus for 4 and 8 weeks.The IELT before treatment and during all coitus after treatment were recorded by the patient’s wife with a stopwatch.Results:Mean IELT before,4 and 8 weeks after treatment in two groups were:On-demand group 101.62±65.44 s,208.75±128.02 s and 265.87±145.70 s;daily use group 102.50-81.22 s,276.87±181.08 s and 353.75±176.45 s,respectively.The ejaculation time increased significantly in both groups(p<0.05).However,increase in ejaculation time in daily use group was significantly higher than the on-demand group in 4 weeks(p=0.036),especially in 8 weeks(p=0.009).The percent of side effects in daily use group(26.7%)was higher than on-demand group(20%)(p<0.05).Drowsiness,diarrhea and vertigo were significantly higher in the daily use than on-demand(p<0.05).Conclusions:On-demand and daily use of sertraline are effective and usually have no serious complications,but the on-demand method is considerably more tolerable.In patients who did not tolerate to daily use of this drug,on-demand could be used as a salvage therapy.

一种安全的Ad Hoc On-demand路由协议

由于Ad Hoc网络固有的弱点,设计安全、有效的Ad Hoc路由协议是困难的。本文从新的角度设计了一个简单、安全的On-demand路由协议。在路径请求和响应阶段,源节点和目的节点的身份分别被隐藏,只有那些位于目的节点选择的最优路径上的节点可以获得完整的路由信息,从而产生有效的前向和反向路径。同时,一个公开的单向Hash函数可以利用隐藏的路由信息构建单向Hash链用于路由信息的认证,从而不需要预先的共享密钥。在一次路由计算中,只有源节点和目的节点需要进行一次非对称密码运算。

Ants-Based On-Demand Routing Algorithm for Mobile Ad Hoc Networks

An ants-based on-demand routing algorithm （AORA） specialized for mobile ad hoc networks is proposed. AORA measures the network＇s traffic information including delivery time, route energy etc. by the continuous delivery of data packets, then calculates the compositive parameter for each route which can be seen as the stigmity and uses it to choose the comparatively optimal route in real time. To adjust the weight of each traffic information, the algorithm can meet the different demand of the network＇s user. Multipath source self repair routing （MSSRR） algorithm and dynamic source routing （DSR） can be seen as the special samples of AORA. The routing overhead is not increased in this algorithm. By using simulation, it can be seen that the performance of AORA is better than that of DSR in all scenarios obviously, especially the delivery fraction is increased by more than 100 96.

Network coding-aware cache replacement policy in on-demand broadcast environments

Network coding has been proved to be an effective technique in improving the performance of data broadcast systems because clients requesting different data items can be served simultaneously in one broadcast. Previous studies showed that its efficiency is highly related to the content of clients' cache. However, existing data broadcast systems do not take network coding information into account when making cache replacement decisions. In this paper, we propose two networks coding-aware cache replacement policies called DLRU and DLRU-CP to supplement network coding assisted data broadcast in on-demand broadcast environments. In DLRU, both data access and decoding contribution are taken into account to make replacement decisions. DLRU-CP is based on DLRU but allows clients to retrieve decodable data items that have not been requested yet. The performance gain of our proposed cache replacement policies over traditional cache replacement policy is shown in the simulation results, which demonstrate conclusively that the proposed policies can effectively reduce the overall response time.

On-Demand Service in Cloud Computing

Cloud computing provides a new paradigm for hardware and software infrastructure design as well as planning and usage of information systems. It offers flexible, efficient, inexpensive, and quality services. This paper proposes an on-demand service system using the cloud computing architecture and analyzes important issues such as organization, management, and monitoring of distributed service resources; context-aware on-demand service modeling, on-demand automated service composition in large-scale networks, and service system analysis based on complex system theory. Continuous Operating Reference Station （CORS） of a geo-spatial information system is taken as an example, and its architecture is analyzed from the perspective of cloud computing. Some fundamental questions are raised about its service.

Topology Control for Ad-Hoc Networks: A Comprehensive Review for Table Driven and On-Demand Routing Protocols

Routing on ad-hoc network has become a major research issue among the networking communities due to its increasing complexity and the surge of challenging problems. One major factor contributing to this tendency is that every terminal of an ad-hoc network is also functioning as a network router. In this paper we provide a comprehensive review about the principles and mechanisms of routing protocols used in ad-hoc networks. For comparison purposes, we discuss some relevant technical issues of two well-known routing strategies, namely On-Demand (Proactive routing) and Table-Driven (Reactive routing). In particular, focus our attention on two major and well-known routing protocols: AODV (Ad-hoc On-Demand Distance Vector Protocol) and OLSR (Optimized Link State Routing Protocol). Our study has no intention to suggest any definite solution for any ad-hoc network, because it is the case depending on dictated by the nature and varying factors of networks. Instead, we demonstrate our major perception and describe general models that may assist us while modeling a given network.

Route maintenance of on-demand routing protocol in mobile ad hoc networks

In mobile ad hoc networks （MANETs）, if a mnltihop route breaks, route maintenance is typically performed to establish a new route which causes high control overhead and long packet delay. To decrease the time of recovery and the overhead of maintenance, a new route maintenance mechanism in which the maintenance is confined to the vicinity of the broken link is proposed. This mechanism patches broken route through some other nodes in which only nodes near the broken link（s） may need to be substituted and the rest of nodes can be retained on the route. The broken link can be repaired without considering its relative position in the whole path, so the abihty of dealing with hnk failure is improved obviously. Simulation results show that the proposed strategy improves network performance significantly, such as in merits of control overhead and packet delay.

On-Demand Post-Disaster Emergency Shelters

In post-disaster emergency shelter aid, various relief agencies and other actors with different backgrounds need to cooperate in a tremendously short amount of time and under very different circumstances. In this article, we describe a research project that develops and tests a new approach in which the demands for shelters in a specific situation are methodically connected with available, innovative and sustainable shelter solutions, a DSS （decision support system）. The DSS is a digital tool that translates the gathered evidence on needs, solutions and location including long-term effects of shelter provision into advice for the provision of sustainable, integral broader shelter solutions and designs. The outcome is a set of characteristics for a DSS for the provision of on-demand emergency shelters. A DSS that meets these characteristics leads to the provision of sustainable shelters that meet the needs of the users and, therefore, have higher performance in long term.

Diversified Business Model of On-Demand Cooking:An Analysis Based on the Business Model Canvas

With the acceleration of the pace of social life and the emergence of the convenience economy,the requirements for on-demand cooking services have increased due to the increasing demand for food quality and the health concerns associated with takeaway food,as well as the lack of cooking skills.This paper aims to analyze the business model of on-demand cooking service platforms in China with the theory of Business Model Canvas proposed by Alexander Osterwalder.By exploring the advantages and disadvantages of the business model of on-demand door-to-door cooking,the study seeks to provide relevant recommendations.

On-demand:新“游戏”?新“模式”?

IBM蓄意要将"On demand"发展成为未来第三代电子商务的新"模式"。尽管这一理想蓝图已经在业界引起极大反响,但更多的声音却表示怀疑:这究竟是一场新游戏,还是从根本上改变电子商务运作的新模式?

Reinforcement Learning-Based Dynamic Order Recommendation for On-Demand Food Delivery

On-demand food delivery(OFD)is gaining more and more popularity in modern society.As a kernel order assignment manner in OFD scenario,order recommendation directly influences the delivery efficiency of the platform and the delivery experience of riders.This paper addresses the dynamism of the order recommendation problem and proposes a reinforcement learning solution method.An actor-critic network based on long short term memory(LSTM)unit is designed to deal with the order-grabbing conflict between different riders.Besides,three rider sequencing rules are accordingly proposed to match different time steps of the LSTM unit with different riders.To test the performance of the proposed method,extensive experiments are conducted based on real data from Meituan delivery platform.The results demonstrate that the proposed reinforcement learning based order recommendation method can significantly increase the number of grabbed orders and reduce the number of order-grabbing conflicts,resulting in better delivery efficiency and experience for the platform and riders.

Underoil superhydrophilic flame-retardant 3D porous composite for efficient on-demand emulsion separation:Interface engineering design on sphagnum moss

Oil pollution and the energy crisis make oil-water separation an urgent for human need.The widespread use of materials with a single emulsion separation capability is limited.Multifunctional on-demand separation materials can adapt to a wide range of application scenarios,thus having a wider range of applications.The underoil superhydrophilic surface is of great significance for realizing the on-demand separation of oil/water emulsions through the removal of water in the oil and oil in the water.A 3D porous emulsion separation material based on the superhydrophilic principle of sphagnum moss was designed.The material was prepared in a simple step by taking advantage of the adhesion of polydopamine and the introduction of the as-prepared superhydrophilic BaSO4 nanoparticles to achieve superhydrophilicity with a water contact angle(WCA)of 0°and an oil contact angle(OCA)of 157.3°,resulting in excellent separation performance for both water-in-oil and oil-in-water emulsions.Underoil superhydrophilic porous composite(OSPC)can complete two kinds of emulsion separations by filtration or adsorption.It adsorbs water from water-in-oil emulsion to achieve separation,with a good adsorption capacity of 74.38 g/g and efficiency up to 99%.It can also filter oil-in-water emulsions with an efficiency of 99.92%.The separation efficiencies are all almost unchanged after ten separation cycles.Furthermore,the material has excellent flame retardancy,which reduces the possibility of secondary disasters.The three-dimensional porous sponge has excellent on-demand separation performance for multiple emulsions.It provides a new preparation strategy for underoil superhydrophilic materials and a new idea for the design direction of special wetting materials for the on-demand separation of oil/water emulsions.

A Matching Algorithm with Reinforcement Learning and Decoupling Strategy for Order Dispatching in On-Demand Food Delivery

The on-demand food delivery(OFD)service has gained rapid development in the past decades but meanwhile encounters challenges for further improving operation quality.The order dispatching problem is one of the most concerning issues for the OFD platforms,which refer to dynamically dispatching a large number of orders to riders reasonably in very limited decision time.To solve such a challenging combinatorial optimization problem,an effective matching algorithm is proposed by fusing the reinforcement learning technique and the optimization method.First,to deal with the large-scale complexity,a decoupling method is designed by reducing the matching space between new orders and riders.Second,to overcome the high dynamism and satisfy the stringent requirements on decision time,a reinforcement learning based dispatching heuristic is presented.To be specific,a sequence-to-sequence neural network is constructed based on the problem characteristic to generate an order priority sequence.Besides,a training approach is specially designed to improve learning performance.Furthermore,a greedy heuristic is employed to effectively dispatch new orders according to the order priority sequence.On real-world datasets,numerical experiments are conducted to validate the effectiveness of the proposed algorithm.Statistical results show that the proposed algorithm can effectively solve the problem by improving delivery efficiency and maintaining customer satisfaction.

Self-adaptive hydrogel for breast cancer therapy via accurate tumor elimination and on-demand adipose tissue regeneration

The irregular defects and residual tumor tissue after surgery are challenges for effective breast cancer treatment.Herein,a smart hydrogel with self-adaptable size and dual responsive cargos release was fabricated to treat breast cancer via accurate tumor elimination,on-demand adipose tissue regeneration and effective infection inhibition.The hydrogel consisted of thiol groups ended polyethylene glycol(SH-PEG-SH)and doxorubicin encapsulated mesoporous silica nanocarriers(DOX@MSNs)double crosslinked hyaluronic acid(HA)after loading of antibacterial peptides(AP)and adipose-derived stem cells(ADSCs).A pH-cleavable unsaturated amide bond was pre-introduced between MSNs and HA frame to perform the tumor-specific acidic environment dependent DOX@MSNs release,meanwhile an esterase degradable glyceryl dimethacrylate cap was grafted on MSNs,which contributed to the selective chemotherapy in tumor cells with over-expressed esterase.The bond cleavage between MSNs and HA would also cause the swelling of the hydrogel,which not only provide sufficient space for the growth of ADSCs,but allows the hydrogel to fully fill the irregular defects generated by surgery and residual tumor atrophy,resulting in the on-demand regeneration of adipose tissue.Moreover,the sustained release of AP could be simultaneously triggered along with the size change of hydrogel,which further avoided bacterial infection to promote tissue regeneration.

On-demand assembly of polymeric nanoparticles for longer-blood-circulation and disassembly in tumor for boosting sonodynamic therapy

Sonodynamic therapy (SDT) is one of the promising strategies for tumor therapy, but its application is usually hindered by fast clearance in blood-circulation, abnormal tumor microenvironment, and inefficient generation of reactive oxygen species. To solve these problems, we proposed an on-demand assembly-disassembly strategy, where the assembly is favorable for longer-blood-circulation and then the disassembly in tumor is favorable for boosting SDT. Hematoporphyrin monomethyl ether (HMME) as the model of organic sonosensitizers were conjugated with hyaluronic acid (HA). Then HA-HMME was mixed with catalase (CAT) and assembled into polymeric nanoparticles (CAT@HA-HMME NPs) with size of ~80 nm. CAT@HA-HMME NPs exhibit good biocompatibility and a longer blood half-time (t1/2 = 4.17 h) which is obviously longer than that (~0.82 h) of HMME molecules. After HA receptor-mediated endocytosis of cancer cells, CAT@HA-HMME NPs can be cleaved by endogenous hyaluronidase, resulting in the on-demand disassembly in tumor to release HA-HMME molecules and CAT. The CAT catalyzes the endogenous H_(2)O_(2) into O_(2) to relieve the hypoxic microenvironment, and the released HA-HMME exhibits a higher ROS generation ability, greatly boosting SDT for the inhibition of tumor growth. Therefore, the on-demand assembly-disassembly strategy may provide some insight in the design and development of nanoagents for tumor therapy.

On-demand data broadcast scheduling based on AHP and GRA methods in wireless broadcast/UMTS integrated systems

The increasing demand for interactive mobile multimedia service is causing the integration of 3rd generation （3G） cellular systems and wireless broadcast systems. The key challenge is to support data dissemination with low response time, request drop rate, and the unfairness of request drop. This article proposes a novel scheduling algorithm called DAG （on-demand scheduling utilizing analytic hierarchy process （AHP） and grey relational analysis （GRA））, which takes multiple factors--waiting time, number of active requests, deadline--into consideration, and models the data scheduling process as a multiple factors＇ decision-making and best option-selecting process. The proposed approach comprises two parts. The first part applies AHP to decide the relative weights of multiple decision factors according to user requests, while the second adopts GRA to rank the data item alternatives through the similarity between each option and the ideal option. Simulation results are presented to demonstrate that DAG performs well in the multiple criterions mentioned above.

Photodynamic therapy-triggered on-demand drug release from ROS-responsive core-cross-linked micelles toward synergistic anti-cancer treatment

Polymeric micelles have demonstrated wide utility for chemodrug delivery,which however,still suffer from shortcomings such as undesired drug loading,disassembly upon dilution,pre-leakage of drug cargoes during systemic circulation,and lack of cancer-selective drug release.Herein,a poly(ethylene glycol)(PEG)-polyphosphoester-based,reactive oxygen species (ROS)-responsive,core-cross-linked (CCL) micellar system was developed to encapsulate both chemodrug (doxorubicin,Dox) and photosensitizer (chlorin e6,Ce6).The hydrophobic core of the micelles was cross-linked via a thioketal (TK)-containing linker,which notably enhanced the drug loading and micelle stability.In tumor cells,far-red light irradiation of Ce6 generated ROS to cleave the TK linkers and disrupt the micelle cores.As such,micelles were destabilized and Dox release was promoted,which thereafter imparted synergistic anti-cancer effect with ROS-mediated photodynamic therapy.This study provides an effective approach to realize the precise control over drug loading,formulation stability,and cancer-selective drug release using polymeric micelles,and would render promising utilities for the programmed anti-cancer combination therapy.