Ceramics 3D Printing by Selective Inhibition Sintering

Selective Inhibition Sintering (SIS) has been proven effective in producing polymeric and metallic parts. Due to the low cost and high quality of SIS printing, the impact of SIS printing in the 3D printing industry could be disruptive. The potential of SIS is further extended to ceramics, an important but hard to print material, by the same mechanism of creating an easy-to-break sacrificial mold. Due to the high sintering temperature of ceramics, fluid based inhibitors delivered by inkjet printing tend to not be effective in SIS for ceramics. Accordingly, the new concept of inhibition by dry powder delivery is implemented. Preliminary experiments have shown the feasibility and ease of printing of simple ceramic parts. Additional experiments are underway to increase the possible part complexity and accuracy, and to optimize the sintering process.Mechanical Engineerin

Adversarial Demonstration Attacks on Large Language Models

With the emergence of more powerful large language models (LLMs), such as ChatGPT and GPT-4, in-context learning (ICL) has gained significant prominence in leveraging these models for specific tasks by utilizing data-label pairs as precondition prompts. While incorporating demonstrations can greatly enhance the performance of LLMs across various tasks, it may introduce a new security concern: attackers can manipulate only the demonstrations without changing the input to perform an attack. In this paper, we investigate the security concern of ICL from an adversarial perspective, focusing on the impact of demonstrations. We propose an ICL attack based on TextAttack, which aims to only manipulate the demonstration without changing the input to mislead the models. Our results demonstrate that as the number of demonstrations increases, the robustness of in-context learning would decreases. Furthermore, we also observe that adversarially attacked demonstrations exhibit transferability to diverse input examples. These findings emphasize the critical security risks associated with ICL and underscore the necessity for extensive research on the robustness of ICL, particularly given its increasing significance in the advancement of LLMs.Comment: Work in Progres

Streaming Traffic Flow Prediction Based on Continuous Reinforcement Learning

Traffic flow prediction is an important part of smart transportation. The goal is to predict future traffic conditions based on historical data recorded by sensors and the traffic network. As the city continues to build, parts of the transportation network will be added or modified. How to accurately predict expanding and evolving long-term streaming networks is of great significance. To this end, we propose a new simulation-based criterion that considers teaching autonomous agents to mimic sensor patterns, planning their next visit based on the sensor's profile (e.g., traffic, speed, occupancy). The data recorded by the sensor is most accurate when the agent can perfectly simulate the sensor's activity pattern. We propose to formulate the problem as a continuous reinforcement learning task, where the agent is the next flow value predictor, the action is the next time-series flow value in the sensor, and the environment state is a dynamically fused representation of the sensor and transportation network. Actions taken by the agent change the environment, which in turn forces the agent's mode to update, while the agent further explores changes in the dynamic traffic network, which helps the agent predict its next visit more accurately. Therefore, we develop a strategy in which sensors and traffic networks update each other and incorporate temporal context to quantify state representations evolving over time

A new mono-functionalized organoimido hexa­molybdate derivative: bis­(tetra-n-butyl­ammonium) (5-chloro-2-methyl­phenyl­imido)-μ6-oxido-dodeca-μ2-oxido-penta­oxidohexa­molybdate(VI)

The title complex, [(C4H9)4N]2[Mo6(C7H6ClN)O18], was prepared by the reaction of (Bu4N)4[α-Mo8O26] and 2-methyl-5-chloro­aniline hydro­chloride with N,N′-dicyclo­hexyl­carbodiimide as dehydrating agent in dry acetonitrile solution. The aryl­imido ligand is linked to an Mo atom of the Lindqvist-type hexamolybdate anion by an Mo N triple bond, with a bond length of 1.732 (4) Å and an Mo N—C bond angle of 169.1 (4)°, typical for monodentate imido groups in such hybrid complexes. Due to the inter­action between one H atom in the aryl group and an O atom of a symmetry-related hexa­molybdate cluster, the anions form centrosymmetric dimers in the crystal structure. Weak C—H⋯O contacts are observed between the cations and anions. Unresolved disorder in some of the butyl chains of the ammonium cation is noted

Two-stage robust planning method for distribution network energy storage based on load forecasting

A two-stage robust planning method for energy storage in distribution networks based on load prediction is proposed to address the uncertainty of active load in energy storage planning. First, considering the uncertainty of active load, a short-term load forecasting model combining the mutual information method and BiLSTM is established based on k-means++ clustering. Second, based on the results of load forecasting, a comprehensive norm-constrained uncertainty set is constructed, and a two-stage robust model for distribution network energy storage planning is established. The first stage aims to minimize the annual investment cost of the energy storage system, while the second stage aims to minimize the daily operating cost of the distribution network. At the same time, a second-order cone relaxation transformation model with non-convex constraints is introduced to ultimately achieve the optimal economy of the distribution network in energy storage planning. Finally, the effectiveness of the proposed method and model is validated on the IEEE 33-node distribution network model using the MATLAB platform

Leonurine promotes the maturation of healthy donors and multiple myeloma patients derived-dendritic cells via the regulation on arachidonic acid metabolism

Objective: Leonurine is a bioactive alkaloid compound extracted from Leonurus japonicus Houtt, which potentially has immunomodulatory effects. The immunomodulatory effect and mechanism of leonurine on monocyte derived dendritic cells (moDCs) from healthy donors (HDs) and multiple myeloma (MM) patients were investigated for the first time.Methods: Peripheral blood from HDs and MM patients was isolated for peripheral blood mononuclear cells (PBMCs). The generation of moDCs was conducted by the incubation of monocytes from PBMCs in the medium consisting of RPMI 1640 medium, 2 mmol/L L-glutamine, 5% human serum, 800 U/mL GM-CSF, 500 U/mL IL-4, 100 U/mL penicillin and 0.1 mg/mL streptomycin. During the incubation of 7 days, the cells were administrated with 1 μM leonurine or 1 × PBS as the control group. On the 8th day, cells were harvested. The expression of maturation associated surface markers CD40, CD83, and HLA-DR on moDCs was analyzed by flow cytometry. Moreover, moDCs with or without 1 μM leonurine administration were evaluated by LC-MS/MS for metabolomics which was further analyzed for the potential mechanism of leonurine on moDCs.Results: The proportion of moDCs in the harvested cells was significantly higher in the HD group (n = 14) than in the MM patient group (n = 11) (p = 0.000). Leonurine significantly enhanced the median fluorescence intensity of CD83, HLA-DR and CD40 expression on HD-moDCs (n = 14; p = 0.042, p = 0.013, p = 0.084) as well as MM paitent-moDCs (n = 11; p = 0.020, p = 0.006, p = 0.025). The metabolomics data showed that in moDCs (HD, n = 15), 18 metabolites in the pathway of arachidonic acid metabolism showed significant differences between the leonurine group and the control group (VIP all >1 and P all <0.05). To be specific, 6-Keto-PGE1, 8,9-DHET, 11 (R)-HETE, 12-Keto-LTB4, 12-OxoETE, 15 (S)-HETE, 15-Deoxy-Delta12,14-PGJ2, 15-Keto-PGF2a, 20-COOH-LTB4, Lecithin, PGA2, PGB2, PGE2, PGF2a, PGG2, Prostacyclin were significantly upregulated in the leonurine group than in the control group, while Arachidonic Acid and TXB2 were significantly downregulated in the leonurine group than in the control group.Conclusion: Leonurine significantly promotes the maturation of moDCs derived from HDs and MM patients, the mechanism of which is related to arachidonic acid metabolism

Exploring the Potential of Integrated Optical Sensing and Communication (IOSAC) Systems with Si Waveguides for Future Networks

Advanced silicon photonic technologies enable integrated optical sensing and communication (IOSAC) in real time for the emerging application requirements of simultaneous sensing and communication for next-generation networks. Here, we propose and demonstrate the IOSAC system on the silicon nitride (SiN) photonics platform. The IOSAC devices based on microring resonators are capable of monitoring the variation of analytes, transmitting the information to the terminal along with the modulated optical signal in real-time, and replacing bulk optics in high-precision and high-speed applications. By directly integrating SiN ring resonators with optical communication networks, simultaneous sensing and optical communication are demonstrated by an optical signal transmission experimental system using especially filtering amplified spontaneous emission spectra. The refractive index (RI) sensing ring with a sensitivity of 172 nm/RIU, a figure of merit (FOM) of 1220, and a detection limit (DL) of 8.2*10-6 RIU is demonstrated. Simultaneously, the 1.25 Gbps optical on-off-keying (OOK) signal is transmitted at the concentration of different NaCl solutions, which indicates the bit-error-ratio (BER) decreases with the increase in concentration. The novel IOSAC technology shows the potential to realize high-performance simultaneous biosensing and communication in real time and further accelerate the development of IoT and 6G networks.Comment: 11pages, 5 figutre

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Degradation of printing and dyeing wastewater by modified biochar catalyzed persulfate

The biochar (BC) obtained from banana peel was used to catalyze persulfate (PS) to degrade the Direct Blue 86 (DB86) simulating and dyeing wastewater, which can obtain a much better degradation efficiency (71.1% within 1440 min) compared with BC (insignificant) or PS (26.7%) alone. Then BC was modified, and the influence of modified method, PS concentration, biochar content and temperature on DB86 degradation was also investigated. Results showed that the acid modified method of BC had advantage for the DB86 degradation, and 99% decolorization efficiency can reach within 240 min. The degradation of DB86 increased with PS concentration increasing, and then decreased slowly. Increasing the acid modified BC dosage and temperature can improve effectively the DB86 degradation. When the experimental conditions are PS 5×10-3 M, acid modified BC 5.0 g/L, and 25°C, the degradation of DB86 can reach 99% within 60 min