Automated Warehouse Systems: A Guideline for Future Research

This study aims to provide a comprehensive tool for the selection, design, and operation of automated warehouse systems considering multiple automated storage and retrieval system (AS/RS) options as well as different constraints and requirements from various business scenarios. We first model the retrieval task scheduling problem in crane-based 3D AS/RS with shuttle-based depth movement mechanisms. We prove the problem is NP-hard and find an optimality condition to facilitate the development of an efficient heuristic. The heuristic demonstrates an advantage in terms of solving time and solution quality over the genetic algorithms and the other two algorithms taken from literature. Numerical experiments illustrate that when a company tends to have multiple short planning horizons with small task batches (i.e., aims to increase the responsiveness level), adding more shuttles is helpful. However, if a company has a long planning horizon with a large task batch size, having faster cranes is more efficient to reduce the makespan. We then focus on the impacts of the number of shuttles, operational mode, storage policies, and shuttle dispatching rules on the expected cycle time of a tier-to-tier shuttle-based storage and retrieval system. The system is modeled as a discrete-time Markov Chain to derive the shuttle distribution under each scenario create the expected travel time models. Numerical experiments indicate that class-based storage is always better than the random storage policy. The best shuttle dispatching rule under each combination of the number of shuttles, operational mode, and storage policy can be quickly identified through the expected cycle time models which are simple and computation friendly. At last, we study the warehouse design problem considering the choice, design, and operation of 2D AS/RS and 3D AS/RS in a systematic way. The warehouse design problem under consideration aims to reduce the investment while satisfying different business needs measured by the desired throughput capacity. We propose a branch-and-bound algorithm to conquer the computational challenges. With the developed algorithm, an optimal warehouse design can be obtained under different application environments, characterized by the desired throughput capacity, inventory level, and demand rate of each SKU

Steganography for Neural Radiance Fields by Backdooring

The utilization of implicit representation for visual data (such as images, videos, and 3D models) has recently gained significant attention in computer vision research. In this letter, we propose a novel model steganography scheme with implicit neural representation. The message sender leverages Neural Radiance Fields (NeRF) and its viewpoint synthesis capabilities by introducing a viewpoint as a key. The NeRF model generates a secret viewpoint image, which serves as a backdoor. Subsequently, we train a message extractor using overfitting to establish a one-to-one mapping between the secret message and the secret viewpoint image. The sender delivers the trained NeRF model and the message extractor to the receiver over the open channel, and the receiver utilizes the key shared by both parties to obtain the rendered image in the secret view from the NeRF model, and then obtains the secret message through the message extractor. The inherent complexity of the viewpoint information prevents attackers from stealing the secret message accurately. Experimental results demonstrate that the message extractor trained in this letter achieves high-capacity steganography with fast performance, achieving a 100\% accuracy in message extraction. Furthermore, the extensive viewpoint key space of NeRF ensures the security of the steganography scheme.Comment: 6 pages, 7 figure

Strong Association Between Two Polymorphisms on 15q25.1 and Lung Cancer Risk: A Meta-Analysis

Background: The association between polymorphisms on 15q25.1 and lung cancer has been widely evaluated; however, the studies have yielded contradictory results. We sought to investigate this inconsistency by performing a comprehensive meta-analysis on two polymorphisms (CHRNA3 gene: rs1051730 and AGPHD1 gene: rs8034191) on 15q25.1. Methods: Data were extracted from 15 and 14 studies on polymorphisms rs1051730 and rs8034191 involving 12301/14000 and 14075/12873 lung cancer cases/controls, respectively. The random-effects model was applied, addressing heterogeneity and publication bias. Results: The two polymorphisms followed Hardy-Weinberg equilibrium for all studies (P\u3e0.05). For rs1051730-G/A, carriers of A allele had a 36% increased risk for lung cancer (95% confidence interval [CI]: 1.27–1.46; P\u3c0.0005), without heterogeneity (P = 0.258) or publication bias (PEgger = 0.462). For rs8034191-T/C, the allelic contrast indicated that C allele conferred a 23% increased risk for lung cancer (95% CI: 1.08–1.4; P = 0.002), with significant heterogeneity (P\u3c0.0005), without publication bias (PEgger = 0.682). Subgroup analyses suggested that the between-study heterogeneity was derived from ethnicity, study design, matched information, and lung cancer subtypes. For example, the association of polymorphisms rs1051730 and rs8034191 with lung cancer was heterogeneous between Caucasians (OR = 1.32 and 1.22; 95% CI: 1.25–1.44 and 1.05–1.42; PP = 0.237 and 0.934, respectively) under the allelic model, and this association was relatively strengthened under the dominant model. There was no observable publication bias for both polymorphisms. Conclusions: Our findings demonstrated that CHRNA3 gene rs1051730-A allele and AGPHD1 gene rs8034191-T allele might be risk-conferring factors for the development of lung cancer in Caucasians, but not in East-Asians

MILP-aided Cube-attack-like Cryptanalysis on Keccak Keyed Modes

Cube-attack-like cryptanalysis was proposed by Dinur et al. at EUROCRYPT 2015, which recovers the key of Keccak keyed modes in a divide-and-conquer manner. In their attack, one selects cube variables manually, which leads to more key bits involved in the key-recovery attack, so the complexity is too high unnecessarily. In this paper, we introduce a new MILP model and make the cube attacks better on the Keccak keyed modes. Using this new MILP tool, we find the optimal cube variables for Keccak-MAC, Keyak and Ketje, which makes that a minimum number of key bits are involved in the key-recovery attack. For example, when the capacity is 256, we find a new 32-dimension cube for Keccak-MAC that involves only 18 key bits instead of Dinur et al.\u27s 64 bits and the complexity of the 6-round attack is reduced to $2^{42}$ from $2^{66}$. More impressively, using this new tool, we give the very first 7-round key-recovery attack on Keccak-MAC-512. We get the 8-round key-recovery attacks on Lake Keyak in nonce-respected setting. In addition, we get the best attacks on Ketje Major/Minor. For Ketje Major, when the length of nonce is 9 lanes, we could improve the best previous 6-round attack to 7-round. Our attacks do not threaten the full-round (12) Keyak/Ketje or the full-round (24) Keccak-MAC. When comparing with Huang et al.\u27s conditional cube attack, the MILP-aided cube-attack-like cryptanalysis has larger effective range and gets the best results on the Keccak keyed variants with relatively smaller number of degrees of freedom

Conditional Cube Attack on Round-Reduced River Keyak

This paper evaluates the security level of the River Keyak against the cube-like attack. River Keyak is the only lightweight scheme of the Keccak-permutation-based Authenticated Encryption Cipher Keyak, which is one of the 16 survivors of the 3rd round CAESAR competition. Dinur et al. gave the seven-round cube-like attack on Lake Keyak (1600-bit) using the divide-and-conquer method at EUROCRYPT 2015, then Huang et al. improved the result to 8-round using a new conditional cube attack at EUROCRYPT 2017. While for River Keyak, the 800-bit state is so small that the equivalent key (256-bit capacity) occupy double lanes, the attacks can not be applied to the River Keyak trivially. In this paper, we comprehensively explore the conditional cube attack on the small state (800-bit) River Keyak. Firstly, we find a new conditional cube variable which has a much weaker diffusion than Huang et al.\u27s, this makes the conditional cube attack possible for small state (800-bit) River Keyak. Then we find enough cube variables for 6/7-round River Keyak and successfully launch the key recovery attacks on 6/7-round River Keyak with the time complexity $2^{33}$ and $2^{49}$ respectively. We also verify the 6 and 7-round attack on a laptop. Finally, by using linear structure technique with our new conditional cube variable, we greatly increase the freedom degree to find more cube variables for conditional cube attacks as it is complex for 800-bit state to find enough cube variables for 8-round attack. And then we use the new variables by this new method to launch 8-round conditional cube attack with the time complexity $2^{81}$. These are the first cryptanalysis results on round-reduced River Keyak. Our attacks do not threaten the full-round (12) River Keyak

Multimodal deep learning for mapping forest dominant height by fusing GEDI with earth observation data

The integration of multisource remote sensing data and deep learning models offers new possibilities for accurately mapping high spatial resolution forest height. We found that GEDI relative heights (RH) metrics exhibited strong correlation with the mean of the top 10 highest trees (dominant height) measured in situ at the corresponding footprint locations. Consequently, we proposed a novel deep learning framework termed the multi-modal attention remote sensing network (MARSNet) to estimate forest dominant height by extrapolating dominant height derived from GEDI, using Setinel-1 data, ALOS-2 PALSAR-2 data, Sentinel-2 optical data and ancillary data. MARSNet comprises separate encoders for each remote sensing data modality to extract multi-scale features, and a shared decoder to fuse the features and estimate height. Using individual encoders for each remote sensing imagery avoids interference across modalities and extracts distinct representations. To focus on the efficacious information from each dataset, we reduced the prevalent spatial and band redundancies in each remote sensing data by incorporating the extended spatial and band reconstruction convolution modules in the encoders. MARSNet achieved commendable performance in estimating dominant height, with an R2 of 0.62 and RMSE of 2.82 m, outperforming the widely used random forest approach which attained an R2 of 0.55 and RMSE of 3.05 m. Finally, we applied the trained MARSNet model to generate wall-to-wall maps at 10 m resolution for Jilin, China. Through independent validation using field measurements, MARSNet demonstrated an R2 of 0.58 and RMSE of 3.76 m, compared to 0.41 and 4.37 m for the random forest baseline. Our research demonstrates the effectiveness of a multimodal deep learning approach fusing GEDI with SAR and passive optical imagery for enhancing the accuracy of high resolution dominant height estimation

A novel non-invasive brain stimulation technique: “Temporally interfering electrical stimulation”

For decades, neuromodulation technology has demonstrated tremendous potential in the treatment of neuropsychiatric disorders. However, challenges such as being less intrusive, more concentrated, using less energy, and better public acceptance, must be considered. Several novel and optimized methods are thus urgently desiderated to overcome these barriers. In specific, temporally interfering (TI) electrical stimulation was pioneered in 2017, which used a low-frequency envelope waveform, generated by the superposition of two high-frequency sinusoidal currents of slightly different frequency, to stimulate specific targets inside the brain. TI electrical stimulation holds the advantages of both spatial targeting and non-invasive character. The ability to activate deep pathogenic targets without surgery is intriguing, and it is expected to be employed to treat some neurological or psychiatric disorders. Recently, efforts have been undertaken to investigate the stimulation qualities and translation application of TI electrical stimulation via computational modeling and animal experiments. This review detailed the most recent scientific developments in the field of TI electrical stimulation, with the goal of serving as a reference for future research

Selection for High Oridonin Yield in the Chinese Medicinal Plant Isodon (Lamiaceae) Using a Combined Phylogenetics and Population Genetics Approach

Oridonin is a diterpenoid with anti-cancer activity that occurs in the Chinese medicinal plant Isodon rubescens and some related species. While the bioactivity of oridonin has been well studied, the extent of natural variation in the production of this compound is poorly known. This study characterizes natural variation in oridonin production in order to guide selection of populations of Isodon with highest oridonin yield. Different populations of I. rubescens and related species were collected in China, and their offspring were grown in a greenhouse. Samples were examined for oridonin content, genotyped using 11 microsatellites, and representatives were sequenced for three phylogenetic markers (ITS, rps16, trnL-trnF). Oridonin production was mapped on a molecular phylogeny of the genus Isodon using samples from each population as well as previously published Genbank sequences. Oridonin has been reported in 12 out of 74 species of Isodon examined for diterpenoids, and the phylogeny indicates that oridonin production has arisen at least three times in the genus. Oridonin production was surprisingly consistent between wild-collected parents and greenhouse-grown offspring, despite evidence of gene flow between oridonin-producing and non-producing populations of Isodon. Additionally, microsatellite genetic distance between individuals was significantly correlated with chemical distance in both parents and offspring. Neither heritability nor correlation with genetic distance were significant when the comparison was restricted to only populations of I. rubescens, but this result should be corroborated using additional samples. Based on these results, future screening of Isodon populations for oridonin yield should initially prioritize a broad survey of all species known to produce oridonin, rather than focusing on multiple populations of one species, such as I. rubescens. Of the samples examined here, I. rubescens or I. japonicus from Henan province would provide the best source of oridonin

Efficacy of radiation plus transarterial chemoembolization and lenvatinib in hepatocellular carcinoma with portal vein tumor thrombus

BackgroundWe aimed to investigate the efficacy of a novel regimen, external beam radiation (RT) combined with trans arterial chemoembolization (TACE) and lenvatinib (LEN), in the treatment of hepatocellular carcinoma (HCC) with portal vein tumor thrombus.MethodsWe prospectively observed 102 participants from three tertiary medical centers in China between October 2018 and October 2020, who chose either RT plus TACE and LEN (RT-TACE-LEN) or TACE and LEN (TACE-LEN). LEN (12 mg or 8 mg daily) was administrated orally and continued until progression or intolerable side effects were noted. TACE was given one day after administration of LEN, and RT began within 4 weeks after the first TACE. The median dose/fraction of RT was 50 Gy/25 fractions (range: 45-60 Gy/25 fractions). Overall survival and progression free survival were compared between two groups, and complications were assessed.ResultsBoth 51 patients received RT-TACE-LEN and TACE-LEN, respectively. Most patients had tumor size> 5 cm (73.8%) and tumor number≥ 2 (69.9%). The overall incidence of toxicities was significantly higher in RT-TACE-LEN group than TACE-LEN group (100% vs. 64.7%, p< 0.001), but incidences of grade 3-4 toxicities were comparable (54.9% vs. 49.0%, p= 0.552). Both median overall survival (22.8 vs. 17.1 months, p= 0.031) and median progression-free survival (12.8 vs. 10.5 months, p= 0.035) were significantly longer after RT-TACE-LEN treatment than TACE-LEN.ConclusionsThe addition of RT to TACE and LEN was safe, and might improve clinical outcomes of patients with advanced HCC, which needs conformation from further studies