An Actor-Critic-Based UAV-BSs Deployment Method for Dynamic Environments

In this paper, the real-time deployment of unmanned aerial vehicles (UAVs) as flying base stations (BSs) for optimizing the throughput of mobile users is investigated for UAV networks. This problem is formulated as a time-varying mixed-integer non-convex programming (MINP) problem, which is challenging to find an optimal solution in a short time with conventional optimization techniques. Hence, we propose an actor-critic-based (AC-based) deep reinforcement learning (DRL) method to find near-optimal UAV positions at every moment. In the proposed method, the process searching for the solution iteratively at a particular moment is modeled as a Markov decision process (MDP). To handle infinite state and action spaces and improve the robustness of the decision process, two powerful neural networks (NNs) are configured to evaluate the UAV position adjustments and make decisions, respectively. Compared with the heuristic algorithm, sequential least-squares programming and fixed UAVs methods, simulation results have shown that the proposed method outperforms these three benchmarks in terms of the throughput at every moment in UAV networks

Controlling Class Layout for Deep Ordinal Classification via Constrained Proxies Learning

For deep ordinal classification, learning a well-structured feature space specific to ordinal classification is helpful to properly capture the ordinal nature among classes. Intuitively, when Euclidean distance metric is used, an ideal ordinal layout in feature space would be that the sample clusters are arranged in class order along a straight line in space. However, enforcing samples to conform to a specific layout in the feature space is a challenging problem. To address this problem, in this paper, we propose a novel Constrained Proxies Learning (CPL) method, which can learn a proxy for each ordinal class and then adjusts the global layout of classes by constraining these proxies. Specifically, we propose two kinds of strategies: hard layout constraint and soft layout constraint. The hard layout constraint is realized by directly controlling the generation of proxies to force them to be placed in a strict linear layout or semicircular layout (i.e., two instantiations of strict ordinal layout). The soft layout constraint is realized by constraining that the proxy layout should always produce unimodal proxy-to-proxies similarity distribution for each proxy (i.e., to be a relaxed ordinal layout). Experiments show that the proposed CPL method outperforms previous deep ordinal classification methods under the same setting of feature extractor.Comment: Accepted by AAAI 202

Multi-Prompting Decoder Helps Better Language Understanding

Recent Pre-trained Language Models (PLMs) usually only provide users with the inference APIs, namely the emerging Model-as-a-Service (MaaS) setting. To adapt MaaS PLMs to downstream tasks without accessing their parameters and gradients, some existing methods focus on the output-side adaptation of PLMs, viewing the PLM as an encoder and then optimizing a task-specific decoder for decoding the output hidden states and class scores of the PLM. Despite the effectiveness of these methods, they only use a single prompt to query PLMs for decoding, leading to a heavy reliance on the quality of the adopted prompt. In this paper, we propose a simple yet effective Multi-Prompting Decoder (MPD) framework for MaaS adaptation. The core idea is to query PLMs with multiple different prompts for each sample, thereby obtaining multiple output hidden states and class scores for subsequent decoding. Such multi-prompting decoding paradigm can simultaneously mitigate reliance on the quality of a single prompt, alleviate the issue of data scarcity under the few-shot setting, and provide richer knowledge extracted from PLMs. Specifically, we propose two decoding strategies: multi-prompting decoding with optimal transport for hidden states and calibrated decoding for class scores. Extensive experiments demonstrate that our method achieves new state-of-the-art results on multiple natural language understanding datasets under the few-shot setting

Recent Advances in Organic Light-Emitting Diodes Based on Pure Organic Room Temperature Phosphorescence Materials

Pure organic room temperature phosphorescence (RTP) materials have attracted extensive attention in recent years due to their unique characteristics, such as flexible design method, low toxicity, low cost, as well as the ease of production at scale. The involvement of triplet state and direct radiative transition from the triplet state show that RTP materials have great potential as a new generation emitter in organic light-emitting diodes (OLEDs). Based on the mechanism of phosphorescence, various methods have been developed to achieve RTP emissions in the crystal state. However, the observation of RTP in the thin film state is much more difficult to achieve because of the lower degree of rigidity and suppression of the non-radiative transition. In this mini-review, molecular design strategies developed to achieve RTP emissions and their application in OLEDs are summarized and discussed. The conclusion and outlook point to great potential as well as the challenges for the continued study of pure organic RTP materials-based OLEDs

LawBench: Benchmarking Legal Knowledge of Large Language Models

Large language models (LLMs) have demonstrated strong capabilities in various aspects. However, when applying them to the highly specialized, safe-critical legal domain, it is unclear how much legal knowledge they possess and whether they can reliably perform legal-related tasks. To address this gap, we propose a comprehensive evaluation benchmark LawBench. LawBench has been meticulously crafted to have precise assessment of the LLMs' legal capabilities from three cognitive levels: (1) Legal knowledge memorization: whether LLMs can memorize needed legal concepts, articles and facts; (2) Legal knowledge understanding: whether LLMs can comprehend entities, events and relationships within legal text; (3) Legal knowledge applying: whether LLMs can properly utilize their legal knowledge and make necessary reasoning steps to solve realistic legal tasks. LawBench contains 20 diverse tasks covering 5 task types: single-label classification (SLC), multi-label classification (MLC), regression, extraction and generation. We perform extensive evaluations of 51 LLMs on LawBench, including 20 multilingual LLMs, 22 Chinese-oriented LLMs and 9 legal specific LLMs. The results show that GPT-4 remains the best-performing LLM in the legal domain, surpassing the others by a significant margin. While fine-tuning LLMs on legal specific text brings certain improvements, we are still a long way from obtaining usable and reliable LLMs in legal tasks. All data, model predictions and evaluation code are released in https://github.com/open-compass/LawBench/. We hope this benchmark provides in-depth understanding of the LLMs' domain-specified capabilities and speed up the development of LLMs in the legal domain

Phragmites australis

Aquatic plants play an essential role and are effective in mitigating lake eutrophication by forming complex plant-soil system and retaining total nitrogen (TN) and phosphorus (TP) in soils to ultimately reduce their quantities in aquatic systems. Two main vegetation types (Phragmites australis community and P. australis + Typha latifolia community) of Qin Lake wetland were sampled in this study for the analysis of TN and TP contents and reserves in the wetland soils. The results showed that (1) the consumption effect of Qin Lake wetland on soluble N was much more significant than on soluble P. (2) The efficiency of TN enrichment in wetland soil was enhanced by vegetation covering of P. australis and T. latifolia. (3) Wetland soil P was consumed by P. australis community and this pattern was relieved with the introduction of T. latifolia. (4) According to the grey relativity analysis, the most intensive interaction between plants and soil occurred in summer. In addition, the exchange of N in soil-vegetation system primarily occurred in the 0–15 cm soil layer. Our results indicated that vegetation covering was essential to the enrichment of TN and TP, referring to the biology-related fixation in the wetland soil

Extinction risk of Chinese angiosperms varies between woody and herbaceous species

Aim: Understanding how species' traits and environmental contexts relate to extinction risk is a critical priority for ecology and conservation biology. This study aims to identify and explore factors related to extinction risk between herbaceous and woody angiosperms to facilitate more effective conservation and management strategies and understand the interactions between environmental threats and species' traits. Location: China. Taxon: Angiosperms. Methods: We obtained a large dataset including five traits, six extrinsic variables, and 796,118 occurrence records for 14,888 Chinese angiosperms. We assessed the phylogenetic signal and used phylogenetic generalized least squares regressions to explore relationships between extinction risk, plant traits, and extrinsic variables in woody and herbaceous angiosperms. We also used phylogenetic path analysis to evaluate causal relationships among traits, climate variables, and extinction risk of different growth forms. Results: The phylogenetic signal of extinction risk differed among woody and herbaceous species. Angiosperm extinction risk was mainly affected by growth form, altitude, mean annual temperature, normalized difference vegetation index, and precipitation change from 1901 to 2020. Woody species' extinction risk was strongly affected by height and precipitation, whereas extinction risk for herbaceous species was mainly affected by mean annual temperature rather than plant traits. Main conclusions: Woody species were more likely to have higher extinction risks than herbaceous species under climate change and extinction threat levels varied with both plant traits and extrinsic variables. The relationships we uncovered may help identify and protect threatened plant species and the ecosystems that rely on them

Biological characterization of novel Escherichia coli O157:H7 phages and their bacteriostatic effects in milk and pork

Foodborne bacteria, particularly Escherichia coli (E. coli) O157:H7, are significant contributors to foodborne illnesses, with antibiotic overuse exacerbating the issue through the emergence of multidrug-resistant strains. This study investigated the potential of E. coli phages in food safety, examining their biological traits and bacteriostatic properties. Two phages (vB_EcoP_SD2, vB_EcoP_SD6) of E. coli O157:H7 were isolated from slaughterhouse sewage and characterized for morphology, genomic composition, phage phylogenetic tree, optimal multiplicity of infection (MOI), one-step growth curve, thermal and pH stability and antibacterial efficacy. The optimal MOIs of vB_EcoP_SD2 and vB_EcoP_SD6 was 0.1 and 0.01, and temperature range for maintaining activity was 4°C to 55°C. The host range of vB_EcoP_SD2 and vB_EcoP_SD6 was 65% (13/20) and 55% (11/20), which was partially complementary to each other (75%, 15/20). Notably, vB_EcoP_SD2 displayed a latent period of 10 min, a burst period of 80 min, and a burst volume of 80 PFU per cell, while vB_EcoP_SD6 had a burst volume of 10 PFU per cell. Comprehensive whole-genome analysis confirmed two phages has no presence of pathogenic factors or resistance genes. Genomic comparisons suggest vB_EcoP_SD2 and vB_EcoP_SD6, respectively, constituted a novel member of a new genus, Justusliebigvirus genus and Kayfunavirus genus which genome, respectively, was found to be 1,49,066 bp, 40,202 bp long with an average GC content of 37.5 and 49.8%. The phages effectively inhibited host bacteria in LB broth for at least 6 h and showed promise in inhibiting bacteria in milk and pork, which indicated that the two phages exhibited a favorable bacteriostatic effect on milk and pork within the first 6 h under the optimal MOI. In the milk bacteriostasis experiment, vB_EcoP_SD2 could reduce bacteria by 3.16 × 104 CFU/mL, and vB_EcoP_SD6 could reduce bacteria by 1.05 × 104 CFU/mL. Phage vB_EcoP_SD2 decreased bacteria by 1.14 × 104 CFU/mL, and vB_EcoP_SD6 decreased bacteria by 2.04 × 103 CFU/mL in the pork. There was no disparity in bacteriostatic effect of different MOI within the first 6 h, but bacteriostatic effect of all groups still remained different from that of the control group. This study indicates the two phages possess excellent biological characteristics, thereby providing a theoretical foundation for the subsequent development of natural fungicides

The heterogeneity of genomic alterations, metastatic patterns and immune microenvironment in metastatic ovarian cancer originating from colorectal cancer

PurposeThe ovarian metastases originating from colorectal cancer (CRCOM) develops rapidly and lethally. Previously, the genetic alterations and metastatic pathway in CRCOM were not well understood. The aim of this study is to explore the special molecular phenotype and dissemination patterns of CRCOM.MethodsThe whole-exome sequencing (WES) was performed on 65 matched tissue samples from 11 CRCOM patients, including 11 primary colorectal cancer (CRC) with 11 matched normal tissues, and 43 multi-site metastases (including 15 CRCOMs and 4 patients had bilateral ovarian metastases (OMs). Genetic landscape, neoantigens, tumor clonal origin and spread of CRCOMs were analyzed. TCGA-COAD dataset combined with our data were used for survival analysis and validation of the findings.ResultsThere was significant intertumoral heterogeneity among patients with CRCOM and intra-tumoral heterogeneity among multiorgan metastases. 19 genes were inferred as the potential driver genes of CRCOM. USP7 and RPA1 were HRD-related mutations and potential to serve as predictive biomarkers in OM. The putative neoantigen number of the primary CRC and OM varies widely among patients. The OM showed an immune desert state, extremely deficient in each subtype of immune cells. According to COSMIC signatures features, the CRCOM patients were divided into two groups, which are different in overall survival (OS) (median OS, 720 days vs 360 days, P = 0.074) and genetic alterations. Two metastatic patterns of CRCOM were summarized, which were primary CRC to OM, and metastases to metastases (including lymph node metastases (LNM) to OM, peritoneal metastases (PM) to OM, and other metastases to OM). Interestingly, the sources of bilateral OM might be different in the two patients.ConclusionThis study presents a better understanding the heterogeneity of the genetic characterizations and metastatic pattern in CRCOM. The subtypes of CRCOM with USP7 mutation, more copy number alterations, lower neoantigens, and immunoscore have a worse prognosis