42 research outputs found
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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 hexaÂmolybdate derivative: bisÂ(tetra-n-butylÂammonium) (5-chloro-2-methylÂphenylÂimido)-ÎĽ6-oxido-dodeca-ÎĽ2-oxido-pentaÂoxidohexaÂmolybdate(VI)
The title complex, [(C4H9)4N]2[Mo6(C7H6ClN)O18], was prepared by the reaction of (Bu4N)4[α-Mo8O26] and 2-methyl-5-chloroÂaniline hydroÂchloride with N,N′-dicycloÂhexylÂcarbodiimide as dehydrating agent in dry acetonitrile solution. The arylÂimido 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 interÂaction between one H atom in the aryl group and an O atom of a symmetry-related hexaÂmolybdate cluster, the anions form centrosymmetric dimers in the crystal structure. Weak C—Hâ‹ŻO 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, 2Â mmol/L L-glutamine, 5% human serum, 800Â U/mL GM-CSF, 500Â U/mL IL-4, 100Â U/mL penicillin and 0.1Â mg/mL streptomycin. During the incubation of 7Â days, the cells were administrated with 1Â ÎĽM leonurine or 1 Ă— 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 1Â ÎĽM 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