Mesoscale Analysis of Hydraulics

This open access book presents a series of complicated hydraulic phenomena and related mechanism of high-speed flows in head-head dam. According to the basic hydraulic theory, detailed experiments and numerical simulations, microscopic scale analysis on cavitation bubbles, air bubbles, turbulent eddy vortices and sand grains are examined systemically. These investigations on microscopic fluid mechanics, including cavitation erosion, aeration protection, air–water flow, energy dissipation and river-bed scouring, allow a deep understanding of hydraulics in high-head dams. This book provides reference for designers and researchers in hydraulic engineering, environment engineering and fluid mechanics

Efficient Defenses Against Adversarial Attacks

Following the recent adoption of deep neural networks (DNN) accross a wide range of applications, adversarial attacks against these models have proven to be an indisputable threat. Adversarial samples are crafted with a deliberate intention of undermining a system. In the case of DNNs, the lack of better understanding of their working has prevented the development of efficient defenses. In this paper, we propose a new defense method based on practical observations which is easy to integrate into models and performs better than state-of-the-art defenses. Our proposed solution is meant to reinforce the structure of a DNN, making its prediction more stable and less likely to be fooled by adversarial samples. We conduct an extensive experimental study proving the efficiency of our method against multiple attacks, comparing it to numerous defenses, both in white-box and black-box setups. Additionally, the implementation of our method brings almost no overhead to the training procedure, while maintaining the prediction performance of the original model on clean samples.Comment: 16 page

Modification of wool fiber using steam explosion

Wool fiber was modified by steam explosion in this study. SEM results show that some scales on the fiber surface were cleaved and tiny grooves generated during the explosion. FTIR results suggest no evident changes in the chemical composition of the fiber after the explosion treatment. However, the crystallinity of the fiber decreased slightly as the steam pressure increased based on the X-ray results. In the thermal analysis, DSC results show that the temperature corresponding to vaporization of absorbed water and cleavage of disulfide bonds respectively decreased as the steam pressure increased. The reduction in thermal decomposition energy of the treated fiber indicates that steam explosion might have destroyed some crystals and crosslinks of macromolecular chains in the fiber. The treatment also led to some alterations of the fiber properties, including reduction in strength, moisture regain and solubility in caustic solution.<br /

Bleaching and dyeing of superfine wool powder/polypropylene blend film

Fibers based regenerated protein draw much attention for recycling discarded protein resources and can produce biodegradable and environmental friendly polymers. In this study, superfine wool powder is blended with polypropylene (PP) to produce wool powder/PP blend film through extrusion and hot-pressing. Hydrogen peroxide is used to bleach the black colored surface of the blend films. The effects of peroxide concentration, bleaching time and powder content on the final whiteness and mechanical properties of the blend films are investigated. The bleached films are dyed with acid red dyes and the dyed color is evaluated using a Computer Color Matching System. Color characters of dyed films, such as L*, a*, b*, ΔE*ab, C*ab and K/S values are measured and analyzed. The study not only reuses discarded wool resources into organic powder, widens the application of superfine wool powder on polymers, but also improves the dyeing properties of PP through the addition of protein content

CPET: Effective Parameter-Efficient Tuning for Compressed Large Language Models

Parameter-efficient tuning (PET) has been widely explored in recent years because it tunes much fewer parameters (PET modules) than full-parameter fine-tuning (FT) while still stimulating sufficient knowledge from large language models (LLMs) for downstream tasks. Moreover, when PET is employed to serve multiple tasks, different task-specific PET modules can be built on a frozen LLM, avoiding redundant LLM deployments. Although PET significantly reduces the cost of tuning and deploying LLMs, its inference still suffers from the computational bottleneck of LLMs. To address the above issue, we propose an effective PET framework based on compressed LLMs, named "CPET". In CPET, we evaluate the impact of mainstream LLM compression techniques on PET performance and then introduce knowledge inheritance and recovery strategies to restore the knowledge loss caused by these compression techniques. Our experimental results demonstrate that, owing to the restoring strategies of CPET, collaborating task-specific PET modules with a compressed LLM can achieve comparable performance to collaborating PET modules with the original version of the compressed LLM and outperform directly applying vanilla PET methods to the compressed LLM

Development of Weft Knitted Heating Pads on V-bed Hand Flat Knitting Machine by Using Conductive Yarns

In this investigation weft knitted heating pad was developed on V-bed hand flat knitting machine by using acrylic, polyester as a main yarns  and three different copernic, thermotech –N, thermaram  as conductive yarns with both all knit and inlaid insertion. Moreover time period for heating of yarn, recovery time of yarn for making weft knitted heating pad, structural comparison of different conductive yarn as copernic, thermaram ,thermotech –N  and main yarn as acrylic yarn, polyester yarn was studied. Through analysis conductive yarn that inlaid in the acrylic yarn showed satisfactory heating performance for different time periods and retained more heat rather than polyester yarn. Copernic conductive yarn and thermotech-N conductive yarn had high resistance when compared with thermaram conductive yarn that generated more heat. Acrylic yarn when used as main yarn having conductive thermotech-N yarn inlaid in its structure had produced better heating and retaining properties for the weft knitted heating pad

Cytokine-Induced Killer Cells As Pharmacological Tools for Cancer Immunotherapy

Cytokine-induced killer (CIK) cells are a heterogeneous population of effector CD3+CD56+ natural killer T cells, which can be easily expanded in vitro from peripheral blood mononuclear cells. CIK cells work as pharmacological tools for cancer immunotherapy as they exhibit MHC-unrestricted, safe, and effective antitumor activity. Much effort has been made to improve CIK cells cytotoxicity and treatments of CIK cells combined with other antitumor therapies are applied. This review summarizes some strategies, including the combination of CIK with additional cytokines, dendritic cells, check point inhibitors, antibodies, chemotherapeutic agents, nanomedicines, and engineering CIK cells with a chimeric antigen receptor. Furthermore, we briefly sum up the clinical trials on CIK cells and compare the effect of clinical CIK therapy with other immunotherapies. Finally, further research is needed to clarify the pharmacological mechanism of CIK and provide evidence to formulate uniform culturing criteria for CIK expansion