A Novel Black Box Process Quality Optimization Approach based on Hit Rate

Hit rate is a key performance metric in predicting process product quality in integrated industrial processes. It represents the percentage of products accepted by downstream processes within a controlled range of quality. However, optimizing hit rate is a non-convex and challenging problem. To address this issue, we propose a data-driven quasi-convex approach that combines factorial hidden Markov models, multitask elastic net, and quasi-convex optimization. Our approach converts the original non-convex problem into a set of convex feasible problems, achieving an optimal hit rate. We verify the convex optimization property and quasi-convex frontier through Monte Carlo simulations and real-world experiments in steel production. Results demonstrate that our approach outperforms classical models, improving hit rates by at least 41.11% and 31.01% on two real datasets. Furthermore, the quasi-convex frontier provides a reference explanation and visualization for the deterioration of solutions obtained by conventional models

PUMA: Secure Inference of LLaMA-7B in Five Minutes

With ChatGPT as a representative, tons of companies have began to provide services based on large Transformers models. However, using such a service inevitably leak users' prompts to the model provider. Previous studies have studied secure inference for Transformer models using secure multiparty computation (MPC), where model parameters and clients' prompts are kept secret. Despite this, these frameworks are still limited in terms of model performance, efficiency, and deployment. To address these limitations, we propose framework PUMA to enable fast and secure Transformer model inference. Our framework designs high quality approximations for expensive functions, such as GeLU and Softmax, which significantly reduce the cost of secure inference while preserving the model performance. Additionally, we design secure Embedding and LayerNorm procedures that faithfully implement the desired functionality without undermining the Transformer architecture. PUMA is about 2x faster than the state-of-the-art MPC framework MPCFORMER(ICLR 2023) and has similar accuracy as plaintext models without fine-tuning (which the previous works failed to achieve). One more thing, PUMA can evaluate LLaMA-7B in around 5 minutes to generate 1 token. To our best knowledge, this is the first time that a model with such a parameter size is able to be evaluated under MPC. PUMA has been open-sourced in the Github repository of SecretFlow-SPU

Co-Pyrolysis Behaviors of the Cotton Straw/PP Mixtures and Catalysis Hydrodeoxygenation of Co-Pyrolysis Products over Ni-Mo/Al2O3 Catalyst

The doping of PP (polypropylene) with cotton straw improved the bio-oil yield, which showed there was a synergy in the co-pyrolysis of the cotton straw and PP at the range of 380–480 °C. In a fixed-bed reactor, model compounds and co-pyrolysis products were used for reactants of hydrodeoxygenation (HDO) over Ni-Mo/Al2O3. The deoxygenation rate of model compounds decreased over Ni-Mo/Al2O3 in the following order: alcohol > aldehyde > acetic acid > ethyl acetate. The upgraded oil mainly consisted of C11 alkane

Catalysis for CO₂ Hydrogenation—What We Have Learned/Should Learn from the Hydrogenation of Syngas to Methanol

This short review provides an in-depth analysis of the achievements and further developments of the catalytic hydrogenation of carbon dioxide (CO2) to methanol from those that are worth learning about based on the transformation of syngas into methanol. We begin by exploring the environmental and energy-related implications of utilizing CO2 as a feedstock for methanol production by emphasizing its potential to mitigate greenhouse gas emissions and facilitate renewable energy integration. Then, different catalytic formulations focusing on precious metals, copper-based catalysts, and metal oxides are summarized, and insights into their advantages and limitations in the aspects of catalytic activity, selectivity, and stability are discussed. Precious metal catalysts, such as platinum and iridium, exhibit high activity but are cost-prohibitive, while copper-based catalysts present a promising and cost-effective alternative. Metal oxides are considered for their unique properties in CO2 activation. Mechanistic insights into reaction pathways are explored, with a particular emphasis on copper-based catalysts. Moreover, the complex steps involved in CO2 hydrogenation to methanol are discussed to shed light on the key intermediates and active sites responsible for catalysis, which is crucial for catalyst design and optimization. Finally, we stress the importance of ongoing research and development efforts to enhance catalyst efficiency, mechanistic comprehension, and process optimization. This review serves as a valuable resource for researchers, engineers, and policymakers working toward a more sustainable and carbon-neutral energy future. By harnessing CO2 as a carbon feedstock for methanol synthesis, we have the potential to address environmental concerns and advance the utilization of renewable energy sources, further contributing to the transition to a cleaner and more sustainable energy landscape

High power RF test of an 805 MHz RF cavity for a muon cooling channel

We present recent high power RF test results on an 805 MHz cavity for a muon cooling experiment at Lab G in Fermilab. In order to achieve high accelerating gradient for large transverse emittance muon beams, the cavity design has adopted a pillbox like shape with 16 cm diameter beam iris covered by thin Be windows, which are demountable to allow for RF tests of different windows. The cavity body is made from copper with stiff stainless steel rings brazed to the cavity body for window attachments. View ports and RF probes are available for visual inspections of the surface of windows and cavity and measurement of the field gradient. Maximum of three thermo-couples can be attached to the windows for monitoring the temperature gradient on the windows caused by RF heating. The cavity was measured to have Q{sub 0} of about 15,000 with copper windows and coupling constant of 1.3 before final assembling. A 12 MW peak power klystron is available at Lab G in Fermilab for the high power test. The cavity and coupler designs were performed using the MAFIA code in the frequency and the time domain. Numerical simulation results and cold test measurements on the cavity and coupler will be presented for comparisons

RF tests of an 805 MHz pillbox cavity at Lab G of Fermilab

We report recent high power RF tests on an 805 MHz RF pillbox cavity with demountable windows for beam apertures at Lab G of Fermilab, a dedicated facility for testing of MUCOOL (muon cooling) components. The cavity is installed inside a superconducting solenoidal magnet. A 12 MW peak RF power klystron is used for the tests. The cavity has been processed both with and without magnetic field. Without magnetic field, a gradient of 34 MV/m was reached rather quickly with very low sparking rate. In a 2.5 T solenoidal field, a 16 MV/m gradient was achieved, and it had to take many weeks of conditioning. Strong multipacting effects associated with high radiation levels were measured during the processing with the magnetic field. More recently Be windows with TiN-coated surface have been installed and tested at conditions of with and without the external magnetic field. A conservative 16 MV/m gradient without magnetic field was reached quickly as planned. Less multipacting was observed during the conditioning, it indicated that the TiN-coated surface on the windows had indeed helped to reduce the secondary electron emissions significantly. A modest gradient of 16.5 MV/m was finally achieved with magnet on in solenoidal mode and the field up to 4 T. Preliminary inspection on Be windows surface found no damage at all, in comparison with Cu windows where substantial surface damage was found. Preliminary understanding of conditioning cavity in a strong magnetic field has been developed. More through window and cavity surface inspection is under way

Intraventricular Injection of LKB1 Inhibits the Formation of Diet-Induced Obesity in Rats by Activating the AMPK-POMC Neurons-Sympathetic Nervous System Axis

Background/Aims: Obesity is increasingly becoming a major public health problem worldwide. Peripheral LKB1 inhibits white fat generation, but the effect of central LKB1 on diet-induced obesity (DIO) is unknown. Therefore, we examined whether LKB1 over-expression in the hypothalamus can inhibit the development of obesity. Methods: Adult male Sprague-Dawley rats were anesthetized and placed in a stereotaxic apparatus. LKB1-AAV-EGFP (2.0 × 108 or 2.0 × 1010 vector genomes) or Control-AAV-EGFP (2.0 × 108 vector genomes) was injected into the third ventricle. After administration, the rats were fed a high-fat diet (HFD) for 9 weeks to induce obesity. Rats fed a chow fat diet were used as normal controls. Results: LKB1 delivery decreased body weight, energy intake, fat mass, and serum lipid levels. LKB1 also improved HFD-induced hepatic fatty degeneration. Interestingly, LKB1 over-expression in the hypothalamus activated the AMPK-POMC neurons-sympathetic nervous system (SNS) axis, which can release epinephrine to promote white fat browning. Conversely, the elevated expression of MC3R/MC4R inhibited food intake. These two factors worked together to inhibit the development of obesity. Conclusions: LKB1 in the hypothalamus may have therapeutic potential for DIO through the activation of the AMPK-POMC neurons-SNS axis

Combined intervention of swimming plus metformin ameliorates the insulin resistance and impaired lipid metabolism in murine gestational diabetes mellitus

<div><p>Gestational diabetes mellitus (GDM) has short- and long- term influence on pregnant women and fetus. Swimming, as an aerobic exercise, can effectively improve the blood glucose level in GDM, but the effect of mild swimming alone was not very substantial. Metformin, as an oral antidiabetic drug, has obvious hypoglycemic effect, and is economic also, but the long-term effect on pregnant women and fetus has not been completely clear. We hypothesize that combined intervention of mild swimming and low dose of metformin, may effectively reduce blood glucose, improve the pregnancy outcomes in GDM dams, but simultaneously avoiding the adverse effects caused by overdose of drug and impotence of mild swimming. The streptozotocin was used to stimulate C57BL/6J mice to develop GDM, by which serum glucose, TC, TG, LDL-C were increased significantly, meanwhile HDL-C was decreased significantly in the GDM control (DC) group compared with the normal control group. Swimming or metformin intervention slightly or moderately improves hyperglycemia, insulin sensitivity and lipid metabolism both in liver and skeletal muscle from GDM mice, while combined therapy of swimming plus metformin markedly ameliorated hyperglycemia (FPG, decreased by 22.2–59.5% from G10 to G18 versus DC group), insulin sensitivity (2.1 and 2.8 fold increase, respectively, in AKT activity versus DC group) and <i>de novo</i> lipogenesis (3.2 and 7.0 fold decrease, respectively, in ACC activity, and 1.94 and 5.1 fold decrease, respectively, in SREBP2 level, versus DC group) both in liver and skeletal muscle from GDM mice. We conclude that the combined intervention by metformin plus swimming may be more effective than single action to ameliorate glucose and lipid metabolism <i>via</i> improving insulin sensitivity in GDM mice.</p></div