The effect of triangular shutter type flow deflector perforated baffle plate on the thermofluid performance of a heat exchanger

The study aimed to investigate the heat transfer (HT) properties of a tubular heat exchanger (HX) by using innovative baffle plate arrangements. The newly designed baffle plate was circular with triangular openings and adjustable triangular flow deflectors. These deflectors were strategically placed at the inlet of the HX to create a swirling flow downstream. Three baffle plates were installed along the flow direction with different length-to-diameter ratios (pitch ratios) to assess their impact on HT, pressure drop, and thermal enhancement factor. The study compared these results with a smooth channel under varying Reynolds numbers (16,500–29,500). The findings revealed that both the pitch ratio (0.6–1.2) and the inclination angle of the deflectors (30⁰–50⁰) significantly affected the HX's performance. Notably, the baffle plate with a deflector inclination angle of 30° and a pitch ratio of 1 showed a remarkable average improvement of 36.5% compared to other angles and ratios.     

Ensemble learning of diffractive optical networks

A plethora of research advances have emerged in the fields of optics and photonics that benefit from harnessing the power of machine learning.Specifically,there has been a revival of interest in optical computing hardware due to its potential advantages for machine learning tasks in terms of parallelization,power efficiency and computation speed.Diffractive deep neural networks(D²NNs)form such an optical computing framework that benefits from deep learning-based design of successive diffractive layers to all-optically process information as the input light diffracts through these passive layers.D²NNs have demonstrated success in various tasks,including object classification,the spectral encoding of information,optical pulse shaping and imaging.Here,we substantially improve the inference performance of diffractive optical networks using feature engineering and ensemble learning.After independently training 1252 D²NNs that were diversely engineered with a variety of passive input filters,we applied a pruning algorithm to select an optimized ensemble of D²NNs that collectively improved the image classification accuracy.Through this pruning,we numerically demonstrated that ensembles of N=14 and N=30 D²NNs achieve blind testing accuracies of 61.14±0.23%and 62.13±0.05%,respectively,on the classification of GFAR-10 test images,providing an inference improvennent of>16%compared to the average performance of the individual D²NNs within each ensemble.These results constitute the highest inference accuracies achieved to date by any diffractive optical neural network design on the same dataset and might provide a significant leap to extend the application space of diffractive optical image classification and machine vision systems.     

Occurrence of two genotypes of tetracycline (TC) resistance gene tet(M) in the TC-resistant bacteria in marine sediments of Japan

The tetracycline (TC) resistance gene tet(M) was monitored in bacteria isolated from Japanese coastal and off-shore marine sediments. The high rate of occurrence of TC resistant (TC(r)) bacteria (120 microg mL(-1) TC) was observed at frequency ranges between 0.0-0.08% in Tokyo Bay, 1.67-1.82% in Sagami Bay and 0.0-4.35% in the open Pacific Ocean. The tet(M) gene was PCR amplified from the TC(r) isolates, showing 127 of 209 isolates (60.8%) as positive. The rate of occurrence of tet(M) was between 32.0-96.0%, 21.1 -28.0% and 0.0-83.3% in the isolates from Tokyo Bay, Sagami Bay and the open Pacific Ocean, respectively. The tet(M) positive isolates belonged to 4 orders of bacteria. Bacillales was the most dominant order (121 strains) among tet(M) possessing bacteria, followed by Actinomycetales (three strains), Flavobacteriales (one strain) and Pseudomonadales (one strain). This indicates that tet(M) is present in various bacterial species and suggests that marine sediments are a natural reservoir of the tet(M) gene. Nucleotide sequence of the tet(M) revealed that two genotypes of tet(M) were found in the bacteria. The two genotypes were placed in genetically distant branches of the phylogenetic tree, suggesting that the two tet(M)s have different origins.     

Mass balance of total mercury and monomethylmercury in coastal embayments of a volcanic island: significance of submarine groundwater discharge

To understand the contribution of submarine groundwater discharge (SGD) to the coastal mass budgets of Hg and monomethylmercury (MMHg), preliminary mass balance estimates were made for Hwasun and Bangdu Bays on Jeju Island, known to have large SGD due to the high permeability of the volcanic rocks. The mass balance results indicate that SGD is a main source of Hg in Hwasun Bay (23 ± 14 × 10(-2) mol yr(-1), 34%) and Bangdu Bay (23 ± 20 × 10(-2) mol yr(-1), 67%), although the contribution from atmospheric deposition was considerable (25% for Hwasun and 23% for Bangdu). MMHg was also discharged primarily from submarine groundwater at Hwasun (0.30 ± 0.17 × 10(-2) mol yr(-1), 55%) and Bangdu (0.65 ± 0.49 × 10(-2) mol yr(-1), 64%), which was higher than atmospheric deposition (6% for Hwasun and 2% for Bangdu) and sediment diffusion flux (5% for Hwasun and 3% for Bangdu). The overall mass balance results suggest that, although there are large spatial variations in SGD rates throughout the region, the coastal mass budgets of Hg and MMHg need to include SGD as well as atmospheric deposition and sediment diffusion as primary sources of Hg and MMHg.     

A new document representation using term frequency and vectorized graph connectionists with application to document retrieval

This paper presents a new document representation with vectorized multiple features including term frequency and term-connection-frequency. A document is represented by undirected and directed graph, respectively. Then terms and vectorized graph connectionists are extracted from the graphs by employing several feature extraction methods. This hybrid document feature representation more accurately reflects the underlying semantics that are difficult to achieve from the currently used term histograms, and it facilitates the matching of complex graph. In application level, we develop a document retrieval system based on self-organizing map (SOM) to speed up the retrieval process. We perform extensive experimental verification, and the results suggest that the proposed method is computationally efficient and accurate for document retrieval.     

Effect of machining parameters in ultrasonic vibration cutting

The ultrasonic vibration cutting (UVC) method is an efficient cutting technique for difficult-to-machine materials. It is found that the UVC mechanism is influenced by three important parameters: tool vibration frequency, tool vibration amplitude and workpiece cutting speed that determine the cutting force. However, the relation between the cutting force and these three parameters in the UVC is not clearly established. This paper presents firstly the mechanism how these parameters effect the UVC. With theoretical studies, it is established that the tool–workpiece contact ratio (TWCR) plays a key role in the UVC process where the increase in both the tool vibration parameters and the decrease in the cutting speed reduce the TWCR, which in turn reduces both cutting force and tool wear, improves surface quality and prolongs tool life. This paper also experimentally investigates the effect of cutting parameters on cutting performances in the cutting of Inconel 718 by applying both the UVC and the conventional turning (CT) methods. It is observed that the UVC method promises better surface finish and improves tool life in hard cutting at low cutting speed as compared to the CT method. The experiments also show that the TWCR, when investigating the effect of cutting speed, has a significant effect on both the cutting force and the tool wear in the UVC method, which substantiates the theoretical findings.     

Chemical composition and inhibitory parameters of essential oil and extracts of Nandina domestica Thunb. to control food-borne pathogenic and spoilage bacteria

The aim of this study was to examine the chemical composition of the essential oil isolated from the floral parts of Nandina domestica Thunb. by hydrodistillation, and to test the efficacy of essential oil and various organic extracts against a panel of food-borne pathogenic and spoilage bacteria such as Bacillus subtilis ATCC6633, Listeria monocytogenes ATCC19166, Staphylococcus aureus KCTC1916, S. aureus ATCC6538, Pseudomonas aeruginosa KCTC2004, Salmonella typhimurium KCTC2515, Salmonella enteridis KCCM12021, Escherichia coli 0157-Human, E. coli ATCC8739, E. coli 057:H7 ATCC43888 and Enterobacter aerognes KCTC2190. The chemical composition of essential oil was analysed by GC-MS. It was determined that 79 compounds, which represented 87.06% of total oil, were present in the oil. The oil contained mainly 1-indolizino carbazole (19.65%), 2-pentanone (16.4%), mono phenol (12.1%), aziridine (9.01%), methylcarbinol (4.6%), ethanone (3.3%), furfural (2.96%), 3,5-dimethylpyrazole (1.29%) and 2(5H)-furanone (1.32%). The oil (1000 ppm/disc), and various organic extracts of hexane, chloroform, ethyl acetate and methanol (1500 ppm/disc) exhibited promising antibacterial effect as a diameter of zones of inhibition (9-18 and 7-13 mm) and MIC values (62.5 to 1000 and 250 to 2000 microg/ml), respectively against the tested bacteria. Also the oil had strong detrimental effect on the viable count of the tested bacteria. These results indicate the potential efficacy of plant-based natural products such as essential oil and organic extracts of N. domestica to control food-borne pathogenic and spoilage bacteria.     

Increasing fermentable sugar yields by high‐pressure treatment during beer mashing

High‐pressure treatment, which is an effective means of enhancing enzymatic reactions, was implemented during beer mashing to increase the production yield of fermentable sugar (FS). The malt solution was heated (62, 67, and 72°C) under pressure [0.1 (1 atm), 2, 50 and 100 MPa], and the FS was measured. The amount of FS reached an equilibrium level, which was the highest at 67°C and at 2 MPa. The pressures were 2, 50, 100, and 0.1 MPa in decreasing order of FS amount at 67°C. The temperatures were 67, 72 and 62°C in decreasing order of FS amount at 2 MPa. With a mechanistic approach, only the effect of pressure on gelatinization was analysed. The gelatinization degrees were also higher at pressures higher than 0.1 MPa. This observation highlights the positive effect (increasing the FS yield) of high‐pressure treatment on beer mashing. Copyright © 2015 The Institute of Brewing & Distilling     

民勤枸杞主要营养、功能成分、重金属及农药残留量分析

本文为了探讨民勤枸杞的营养、活性成分和安全性评价,通过使用高效液相、气相色谱法和其他测定方法分析民勤枸杞的基本营养和功能成分、氨基酸组成、重金属和农药残留量。民勤枸杞的基本营养成分（以每100 g干重计）蛋白质、粗脂肪和碳水化合物含量分别为13.71 g、3.09 g和60.80 g;功能成分多糖、类胡萝卜素、甜菜碱、抗坏血酸、总酚和总黄酮含量分别为2.11 g、569.81 mg、1.57 g、45.08 mg、81.95 mg和70.23 mg。民勤枸杞主要基本营养成分为碳水化合物和蛋白质,并含有丰富的功能性氨基酸天冬氨酸,脯氨酸和谷氨酸。民勤枸杞中色氨酸和芳香氨基酸等必须氨基酸含量丰富;天冬氨酸含量最为丰富;赖氨酸是第一限制必须氨基酸。民勤枸杞含有相对较高的脂肪、类胡萝卜素和抗坏血酸含量;其重金属和农药残留量没有超绿色食品枸杞标准限制。研究结果可为民勤枸杞质量定位提供理论依据。