Online 3D Bin Packing with Constrained Deep Reinforcement Learning

We solve a challenging yet practically useful variant of 3D Bin Packing Problem (3D-BPP). In our problem, the agent has limited information about the items to be packed into the bin, and an item must be packed immediately after its arrival without buffering or readjusting. The item's placement also subjects to the constraints of collision avoidance and physical stability. We formulate this online 3D-BPP as a constrained Markov decision process. To solve the problem, we propose an effective and easy-to-implement constrained deep reinforcement learning (DRL) method under the actor-critic framework. In particular, we introduce a feasibility predictor to predict the feasibility mask for the placement actions and use it to modulate the action probabilities output by the actor during training. Such supervisions and transformations to DRL facilitate the agent to learn feasible policies efficiently. Our method can also be generalized e.g., with the ability to handle lookahead or items with different orientations. We have conducted extensive evaluation showing that the learned policy significantly outperforms the state-of-the-art methods. A user study suggests that our method attains a human-level performance

Near-infrared quantum cutting in Tm3+/Yb3+-doped phosphate glasses

Abstract A series of phosphate glasses with compositions of 30SrO-60P2O5-10Na2O-0.5Tm2O3-xYb2O3(x = 0, 1, 5, 9, 11 in mol%) were manufactured by melt-casting method, the quantum cutting between the Tm3+ and Yb3+ in the phosphate glasses is investigated, the energy transfer from Tm3+:1G4 to Yb3+:2F5/2 is proved. According to calculate, the highest quantum efficiency is up to 159.9%, the emission wavelength is at 1020 nm, matching the energy band gap of a silicon solar cell well, therefor, these phosphate glasses could potentially be used in silicon solar cells

Realization of Zero-Refractive-Index Lens with Ultralow Spherical Aberration

Optical complex materials offer unprecedented opportunity to engineer fundamental band dispersion which enables novel optoelectronic functionality and devices. Exploration of photonic Dirac cone at the center of momentum space has inspired an exceptional characteristic of zero-index, which is similar to zero effective mass in fermionic Dirac systems. Such all-dielectric zero-index photonic crystals provide an in-plane mechanism such that the energy of the propagating waves can be well confined along the chip direction. A straightforward example is to achieve the anomalous focusing effect without longitudinal spherical aberration, when the size of zero-index lens is large enough. Here, we designed and fabricated a prototype of zero-refractive-index lens by comprising large-area silicon nanopillar array with plane-concave profile. Near-zero refractive index was quantitatively measured near 1.55 um through anomalous focusing effect, predictable by effective medium theory. The zero-index lens was also demonstrated to perform ultralow longitudinal spherical aberration. Such IC compatible device provides a new route to integrate all-silicon zero-index materials into optical communication, sensing, and modulation, and to study fundamental physics on the emergent fields of topological photonics and valley photonics.Comment: 14 pages, 4 figure

Cross-subject EEG-based emotion recognition through dynamic optimization of random forest with sparrow search algorithm

The objective of EEG-based emotion recognition is to classify emotions by decoding signals, with potential applications in the fields of artificial intelligence and bioinformatics. Cross-subject emotion recognition is more difficult than intra-subject emotion recognition. The poor adaptability of classification model parameters is a significant factor of low accuracy in cross-subject emotion recognition. We propose a model of a dynamically optimized Random Forest based on the Sparrow Search Algorithm (SSA-RF). The decision trees number (DTN) and the leave minimum number (LMN) of the RF are dynamically optimized by the SSA. 12 features are used to construct feature combinations for selecting the optimal feature combination. DEAP and SEED datasets are employed for testing the performance of SSA-RF. The experimental results show that the accuracy of binary classification is 76.81% on DEAP, and the accuracy of triple classification is 75.96% on SEED based on SSA-RF, which are both higher than that of traditional RF. This study provides new insights for the development of cross-subject emotion recognition, and has significant theoretical value

An integral elasto-plastic constitutive theory

This paper proposes an integral elasto-plastic constitutive equation, in which it is considered that stress is a functional of plastic strain in a plastic strain space. It is indicated that, to completely describe a strain path, the arc-length and curvature of the trajectory, the turning angles at the corner points and other characteristic points on the path must be considered. In general, the plastic strain space is a non-Euclidean geometric, space hence its measure tensor is a function of not only properties of the material but also the plastic strain history. This recommended integral elasto-plastic constitutive equation is the generalization of Ilyushin, Pipkin, Rivlin and Valanis theories and is suited to research the responses of material under the complex loading path. The predictions of the proposed theory have a good agreement with the experimental results. (C) 2002 Elsevier Science Ltd. All rights reserved

Continuous Modeling for transient and steady cyclic hardening /softening behavior of metallic materials under amplitude change loading

This paper is concerned with the performance of the plastic strain amplitude measure, originally motivated and then abandoned by Haupt et al. [1]. Reasons for success and failure in modeling for the amplitude dependence are discussed. It is shown that if the memory parameter in the variable to indicate the center of the plastic strain region is determined suitably, the measure gives satisfactory performance in reflecting the amplitude behavior. By incorporating a hardening function dependent on the measure into the intrinsic time scale used in Valanis' endochronic plasticity, various transient and steady cyclic phenomena of hardening materials can be reproduced

Production of a Monoclonal Antibody for the Detection of Forchlorfenuron: Application in an Indirect Enzyme-Linked Immunosorbent Assay and Immunochromatographic Strip

In this study, a monoclonal antibody (mAb) specific to forchlorfenuron (CPPU) with high sensitivity and specificity was produced and designated (9G9). To detect CPPU in cucumber samples, an indirect enzyme-linked immunosorbent assay (ic-ELISA) and a colloidal gold nanobead immunochromatographic test strip (CGN-ICTS) were established using 9G9. The half-maximal inhibitory concentration (IC50) and the LOD for the developed ic-ELISA were determined to be 0.19 ng/mL and 0.04 ng/mL in the sample dilution buffer, respectively. The results indicate that the sensitivity of the antibodies prepared in this study (9G9 mAb) was higher than those reported in the previous literature. On the other hand, in order to achieve rapid and accurate detection of CPPU, CGN-ICTS is indispensable. The IC50 and the LOD for the CGN-ICTS were determined to be 27 ng/mL and 6.1 ng/mL. The average recoveries of the CGN-ICTS ranged from 68 to 82%. The CGN-ICTS and ic-ELISA quantitative results were all confirmed by liquid chromatography—tandem mass spectrometry (LC-MS/MS) with 84–92% recoveries, which indicated the methods developed herein are appropriate for detecting CPPU in cucumber. The CGN-ICTS method is capable of both qualitative and semiquantitative analysis of CPPU, which makes it a suitable alternative complex instrument method for on-site detection of CPPU in cucumber samples since it does not require specialized equipment

Comparison of perioperative outcomes among non-small cell lung cancer patients with neoadjuvant immune checkpoint inhibitor plus chemotherapy, EGFR-TKI, and chemotherapy alone: A real-world evidence study

Background: The utilization of neoadjuvant immune checkpoint inhibitor (ICI) plus chemotherapy has increased significantly for resectable non-small cell lung cancer (NSCLC). It is still unclear whether such a treatment paradigm affects perioperative outcomes compared with other neoadjuvant treatment. We aimed to evaluate the perioperative outcomes of pulmonary resection after neoadjuvant ICI plus chemotherapy and to compare them with neoadjuvant epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKI) and neoadjuvant chemotherapy alone for resectable NSCLC. Methods: A retrospective cohort including 194 stage IB-IIIB NSCLC underwent surgical resection after neoadjuvant treatment between 2018 and 2020 were reviewed. Perioperative complications were evaluated using the Common Terminology Criteria for Adverse Events, and were compared using one-way analysis of variance for continuous variables and Pearson chi-square test. Results: There were 42, 54, and 98 patients in the neoadjuvant ICI plus chemotherapy, EGFR-TKI, and chemotherapy alone groups, respectively. The tumor size before neoadjuvant treatment was well balanced among the three groups (P=0.122). A shorter median surgical time was observed in the EGFR-TKI group than ICI plus chemotherapy group and chemotherapy group alone (120 Conclusions: Surgical resection for NSCLC following neoadjuvant ICI plus chemotherapy was safe and feasible, the perioperative outcomes were similar with neoadjuvant EGFR-TKI and chemotherapy alone without unexpected perioperative complications. Additional prospective studies are necessary to validate our findings

Recent Advances in Rapid Detection Techniques for Pesticide Residue: A Review

As an important chemical pollutant affecting the safety of agricultural products, the on-site and efficient detection of pesticide residues has become a global trend and hotspot in research. These methodologies were developed for simplicity, high sensitivity, and multiresidue detection. This review introduces the currently available technologies based on electrochemistry, optical analysis, biotechnology, and some innovative and novel technologies for the rapid detection of pesticide residues, focusing on the characteristics, research status, and application of the most innovative and novel technologies in the past 10 years, and analyzes challenges and future development prospects. The current review could be a good reference for researchers to choose the appropriate research direction in pesticide residue detection