Exergy analysis of porous cotton fabric drying process during the domestic air vented dryer

This study reveals energy and exergy efficiencies of the fabric drying processes during air vented dryer. Exergy models of thedrying processes have been formed and each stage is examined in terms of exergetic parameters. Additionally, parametricstudies, including the exergy destruction rates, exergy efficiencies, and exergy loss ratios of the system and its components,have been investigated under various operating conditions. The results indicate that the exergy efficiency increases with theincrease in drying rate. Heater of dryer is the highest exergy destruction component of the whole dryer and its powersignificantly affects exergy destruction of whole drying process; while fan and motor of driving drum are lower exergydestruction component of dryer. Use of staged heating model of adjusting heater power based on drying period is found to be aneffective method to reduce the exergy destruction rate of dryer and fabric damage caused by over-drying. Specifically, exergyefficiency of dryer can be improved by increasing the heater power during the warm up and the constant rate period, or bydecreasing the drying-power during the falling rate and the blow-air period. The findings are found to be useful to systemdesign and performance optimization of domestic dryer in term of reducing irreversibility of the drying system.

Diversity Oriented Synthesis of Furan Epoxide

In this project, we are doing the Diversity Oriented Synthesis of Furan Epoxide. There are two main reactions we are trying to accomplish with the epoxide which are the Achmatowicz reaction with the furan ring, and the epoxide ring opening reaction with amine. During this summer, we are able to make the amino alcohol and the Achmatowicz product has been made from the previous semester. We were also trying to get Achmatowicz reaction happening with the amino alcohol product. However, the result doesn\u27t show the expected structure and still needs further research. Besides organic chemistry synthesis, we also tested the bioactivity of our amino alcohol product since it was similar to another bioactive structure. We did both the Brian Shrimp Lethality Assay with our amino alcohol product

Evolution-Operator-Based Single-Step Method for Image Processing

This work proposes an evolution-operator-based single-time-step method for image and signal processing. The key component of the proposed method is a local spectral evolution kernel (LSEK) that analytically integrates a class of evolution partial differential equations (PDEs). From the point of view PDEs, the LSEK provides the analytical solution in a single time step, and is of spectral accuracy, free of instability constraint. From the point of image/signal processing, the LSEK gives rise to a family of lowpass filters. These filters contain controllable time delay and amplitude scaling. The new evolution operator-based method is constructed by pointwise adaptation of anisotropy to the coefficients of the LSEK. The Perona-Malik-type of anisotropic diffusion schemes is incorporated in the LSEK for image denoising. A forward-backward diffusion process is adopted to the LSEK for image deblurring or sharpening. A coupled PDE system is modified for image edge detection. The resulting image edge is utilized for image enhancement. Extensive computer experiments are carried out to demonstrate the performance of the proposed method. The major advantages of the proposed method are its single-step solution and readiness for multidimensional data analysis

RAIN: Your Language Models Can Align Themselves without Finetuning

Large language models (LLMs) often demonstrate inconsistencies with human preferences. Previous research gathered human preference data and then aligned the pre-trained models using reinforcement learning or instruction tuning, the so-called finetuning step. In contrast, aligning frozen LLMs without any extra data is more appealing. This work explores the potential of the latter setting. We discover that by integrating self-evaluation and rewind mechanisms, unaligned LLMs can directly produce responses consistent with human preferences via self-boosting. We introduce a novel inference method, Rewindable Auto-regressive INference (RAIN), that allows pre-trained LLMs to evaluate their own generation and use the evaluation results to guide backward rewind and forward generation for AI safety. Notably, RAIN operates without the need of extra data for model alignment and abstains from any training, gradient computation, or parameter updates; during the self-evaluation phase, the model receives guidance on which human preference to align with through a fixed-template prompt, eliminating the need to modify the initial prompt. Experimental results evaluated by GPT-4 and humans demonstrate the effectiveness of RAIN: on the HH dataset, RAIN improves the harmlessness rate of LLaMA 30B over vanilla inference from 82% to 97%, while maintaining the helpfulness rate. Under the leading adversarial attack llm-attacks on Vicuna 33B, RAIN establishes a new defense baseline by reducing the attack success rate from 94% to 19%

MiRNA-let-7b smanjuje proliferacijsku aktivnost i razvoj folikularnih stanica putem ciljnog gena MAP3K1

To date, it has not yet been determined if the apoptosis of follicular granulosa cells (FGCs) is mediated by miR- let-7b via MAP3K1. In the present study, FGCs were transfected with a miR-let-7b mimic at different doses (0, 40, 60, 80, 100 and 120 μM), and were allocated into the control group (CG), and MIM-1, MIM-2, MIM-3, MIM-4 and MIM- 5, respectively. Expression levels of miR-let-7b and mitogen-activated protein kinase kinase kinase 1 (MAP3K1) mRNAs and proteins were determined using RT-PCR and Western blots. Luciferase report assay was applied to verify the targeting relationship between miR-let-7b and MAP3K1. The results revealed that the proliferation activity of FGCs in the MIM-4 group was significantly lower than that of the CG and MIM-1 groups (P<0.05). The MiR-let-7b mimic obviously reduced expression levels of miR-let-7b of the FGCs. The largest reduction was found in MIM-4. Levels of MAP3K1 mRNAs and proteins in the MIM-3 and MIM-4 groups were lower than that of the CG (P<0.05 or P<0.01). Co-transfection of let-7b mimic significantly inhibited luciferase activity (P<0.05) as compared with the CG. In conclusion, miR-let-7b may obviously depress the cell viability and accelerate apoptosis of ovine FGCs. Higher doses of miR-let-7b mimic (80 μM and 100 μM) could significantly depress expressions of miR-let-7b mRNAs, MAP3K1 mRNAs and protein in ovine FGCs. MiR-let-7b promoted FGCs apoptosis by inhibiting the MAP3K1 gene.Do danas nije definirano je li apoptoza folikularnih granuloza-stanica (FGCs) posredovana prekursorom miR-let- 7b putem gena MAP3K1. U ovom je istraživanju FGC transfeciran miR-let-7b imitatorom u različitim dozama (0, 40, 60, 80, 100 i 120 μM) i potom razvrstan u kontrolnu skupinu (CG), te u skupine označene kao MIM-1, MIM-2, MIM-3, MIM-4 i MIM-5. Razine ekspresije mRNA i proteina miR-let-7b i mitogenom-aktivirane proteinske kinase kinase kinase1 (MAP3K1) određene su uporabom RT-PCR-a i Western blot-a. Test luciferaze je primijenjen kako bi se potvrdio ciljni odnos između miR-let-7b i MAP3K1. Rezultati su pokazali da je proliferacijska aktivnost FGC-a u skupini MIM-4 bila znakovito manja nego u kontrolnoj skupini i MIM-1 skupini (P<0,05) što ide u prilog pretpostavci da miR-let-7b imitator može u FGCs smanjiti razinu ekpresije miR-let-7b. Najveće smanjenje utvrđeno je u skupini MIM-4. Razine MAP3K1 mRNAs i proteina u skupinama MIM-3 i MIM-4 bile su niže nego u kontrolnoj skupini (P<0,05; P<0,01). Transfekcija let-7b imitatorom znakovito je inhibirala aktivnost luciferaze (P<0,05) u usporedbi s kontrolnom skupinom. Zaključno, miR-let-7b može smanjiti opstojnost stanice i ubrzati apoptozu ovčjih FGC-a. Veće doze miR-let-7b mimic (80 μM i 100 μM) mogu znakovito smanjiti ekspresiju miR-let-7b mRNAs, MAP3K1 mRNAs i proteina u ovčjih FGC-a. MiR-let-7b putem inhibirajućeg gena MAP3K1 doprinosi apoptozi folikularnih granuloza-stanica (FGCs)