21:I[432972,["/_next/static/chunks/bb923814e1f4d2e9.js","/_next/static/chunks/dd3ee9f5b7716ca6.js","/_next/static/chunks/4204a0ae82542ca8.js","/_next/static/chunks/1270dead247da766.js","/_next/static/chunks/6e1aa89a642f40be.js","/_next/static/chunks/2d7aa753e81324a8.js","/_next/static/chunks/8ffd0b71567920d8.js","/_next/static/chunks/67ea6dfd21f16c5f.js","/_next/static/chunks/24eb4379f68013fd.js","/_next/static/chunks/b8cd775ffdf935bd.js","/_next/static/chunks/983103cd9eb7b428.js","/_next/static/chunks/263f2cdcb9aa2341.js","/_next/static/chunks/294b9525248c8e5f.js"],"default"] 22:T435,A novel strategy has been proposed to produce in situ Li₂S at the interfacial layer between lithium anode and the solid electrolyte, by using an amorphous-sulfide-LiTFSI-poly(vinylidene difluoride) (PVDF) composite solid electrolyte (SLCSE). Besides retarding the decomposition of PVDF in CSE, the Li₂S-modified interfacial layer (SMIL) also improves the wettability between lithium metal and SLCSE which in turn optimizes the lithium deposition process. Our density functional theory calculation results reveal that the migration energy barrier of Li passing through SMIL is much lower than that of Li passing through LiF-modified interfacial layer (FMIL) formed from the decomposition of PVDF. The as-prepared SLCSE shows a Li ionic transference number of 0.44 and Li ion conductivity of 3.42 × 10^-4 S/cm at room temperature, and the Li||SLCSE||LiFePO₄ cell exhibits an outstanding rate performance with a capacity of 153, 144, 131, and 101 mAh/g at a current density of 0.05, 0.10, 0.25, and 0.50 mA/cm², respectively.23:T54e,Dynamic ridesharing refers to services that arrange one-time shared rides on short notice. It underpins various real-world intelligent transportation applications such as car-pooling, food delivery and last-mile logistics. A core operation in dynamic ridesharing is the "insertion operator". Given a worker and a feasible route which contains a sequence of origin-destination pairs from previous requests, the insertion operator inserts a new origin-destination pair from a newly arrived request into the current route such that certain objective is optimized. Common optimization objectives include minimizing the maximum flow time of all requests and minimizing the total travel time of the worker. Despite its frequent usage, the insertion operator has a time complexity of O(n^3), where n is the number of all requests assigned to the worker. The cubic running time of insertion fundamentally limits the efficiency of urban-scale dynamic ridesharing based applications. In this paper, we propose a novel partition framework and a dynamic programming based insertion with a time complexity of O(n^2). We further improve the time efficiency of the insertion operator to O(n) harnessing efficient index structures, such as fenwick tree. Evaluations on two real-world large-scale datasets show that our methods can accelerate insertion by 1.5 to 998.1 times.24:T58c,

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1	Engineering	3	3	94
2	Business	1	1	49
3	Natural Sciences	1	1	14
4	Applied Physics	1	1	14
5	Chemistry	1	1	14

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