Texture Structure Research Articles

Enhanced formability of Al–Mg–Si–Zn alloy sheet via dislocation structure and texture during cold rolling

The effects of cold rolling deformation on microstructure, texture, and formability of Al–Mg–Si–Zn alloy were systematically investigated using OM, SEM, TEM, XRD, and tensile tests. The results indicated that the effect of cold rolling deformation on the recrystallized microstructure and texture of the sheets mainly depended on the differences in dislocation structure and texture distribution. With the increase of cold rolling deformation, the dislocation structure gradually changed from a mixture of density dislocation walls and microbands to a lamellar bands structure, the large-angle boundary gradually increased, and the size of dislocation cells gradually decreased, which indicated a gradual increase of the stored deformation energy. In addition, the deformation texture increased gradually with the raise of cold rolling deformation. After T4P treatment, the recrystallized grain size gradually reduced with the increase of cold rolling deformation. The main recrystallization textures in the sheets with 41 % and 55 % deformation were Cube {001}<100> and CubeRD {310}<001> textures, respectively. The CubeND {001}<310> texture was predominantly present in the sheets with 69 % and 82 % deformation, meanwhile some P {011}<233> texture was also observed in the sheets with 82 % deformation. It was found that the dislocation structure and deformation texture distribution formed in the sheet with 82 % cold rolling deformation contributed to smaller recrystallized grains and weaker P texture after solution heat treatment, which enhanced the average plastic strain ratio r value and improved the formability.

Image deblurring method based on self-attention and residual wavelet transform

The restoration technology of non-uniform blurred images is a challenging open topic. Most of the existing algorithms fail to effectively fuse multi-scale feature extraction with a self-attention mechanism, and also ignore the potential contribution of image frequency domain information to image restoration. Frequency domain features play an important role in restoring high-quality images and ignoring this property often leads to over-smoothing of the restoration results. In response to these problems, an image deblurring method based on self-attention and residual wavelet transform is proposed in this paper. Based on a single U-Net network, the multi-scale feature cross-fusion strategy and self-attention mechanism are combined to make the network pay more attention to different degrees of blurred regions so that relatively robust blurred features can be extracted for image deblurring. Meanwhile, considering the important role of frequency domain features for image restoration, the wavelet transform is embedded into the depth residual network to convert spatial domain features to wavelet domain, and the sharp details such as edge contours of blurred features are restored by making full use of the texture structure information possessed by high-frequency sub-bands, which further improves the image restoration performance. Experimental results of quantitative and qualitative comparison with other state-of-the-art methods show that the image deblurring effect of the proposed network performs favorably in terms of peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) metrics. The codes and models are available at https://github.com/BingY998/MRDNet.

Novel ZrB2 and HfB2 metaldiboride coatings by LPCVD

The synthesis of metal diboride thin films has recently attracted great interest. Boron forms binary compounds with most metals. In general, these materials are high-melting, extremely hard solids with high degrees of thermal stability and chemical inertness.In this work the preparation of metal diboride coatings of ZrB2 and HfB2 by CVD is described. A low-pressure CVD (LPCVD) process using MeCl4 (Me = Zr or Hf), BCl3, H2 and Ar was applied. Diboride layers were prepared at deposition temperatures between 800 °C and 1000 °C. The coatings were characterized with respect to phase composition, crystal structure, hardness and wear behavior. The deposited diboride layers show well defined crystallites with a high hardness up to 3200 HV[0.01] for ZrB2 and 3900 HV[0.01] for HfB2. Depending on the substrate temperature and precursor ratio, layers with different textured crystalline structure were obtained at different deposition rates. Phase composition and structure of the deposited layers were examined using SEM and EDS-analysis.A TiN bonding layer prior the diboride deposition ensures a strong adhesion to the hard metal inserts. Scratch test measurements showed critical loads of about 90 N. In wear tests a high performance of the CVD diboride coatings were observed. HfB2 coated inserts exceeded the lifetime of state-of-the-art CVD-TiB2 coatings in face-milling TiAl6V4.

Agricultural waste-based microporous catalysts for oxidative desulfurization of highly sour heavy gas oil

In recent years, the use of abundant and low-cost biomaterials such as agricultural wastes in the preparation of activated carbon has been receiving a lot of attention. Besides, the conventional middle and heavy fuel cuts require a substantial and cost-effective sweetening process because sulfur in transportation fuel was found as one of the main causes of air pollution. The present work explored the preparation and characterization of microporous activated carbon (AC) catalysts prepared from olive stone by tubular furnace (Fe/AC1) and microwave (Fe/AC2) heating methods using H3PO4 (85 wt%) as chemical activating agents. The kinetics of the oxidative desulfurization process (ODS) of a highly sour diesel fuel (sulfur content = 7361 ppm) was determined. The effect of the heating method on the texture and morphological structure, surface area, and surface chemistry of the carbons produced was investigated. Fe/AC1 was prepared in a horizontal tabular furnace at 650 °C calcination temperature and 90 min residence time under a nitrogen atmosphere, while Fe/AC2 was performed in a microwave reactor with 565 W and 7 min microwave power and irradiation time respectively. The catalysts were characterized by N2- adsorption-desorption, SEM-EDX, FTIR, XRD, XRF, TGA, PSD, and elemental analysis. It was found that the use of a tubular furnace for heating the olive seeds resulted in a higher surface area and yield. Also, the characterizations of the Fe/AC1 catalyst showed that it has a large surface area of 1175 m2/g and micropore volume of 0.6954 cm3/g whereas Fe/AC2 had a surface area of 854 m2/g and micropore volume of 0.6936 cm3/g. Moreover, SEM-EDX results indicated that Fe/AC1 was dispersed uniformly better than Fe/AC2. Also, TGA/DTA results revealed better results for Fe/AC1 than Fe/AC2 making it favorable in ODS experiments. The difference in texture and chemical properties is caused by the heating methods. The desulfurization removal was investigated under different temperatures (80, 90, 100, 110 °C) and reaction time (30–90 min). The kinetics of the ODS were conducted over the efficient Fe/AC1 catalyst prepared. It was shown that the ODS reaction followed pseudo-first-order kinetics with a fairly low activation energy over the catalyst was 40.71 kJ/mol.

Reconstruction and Intelligent Evaluation of Three-Dimensional Texture of Stone Matrix Asphalt-13 Pavement for Skid Resistance

To examine the three-dimensional texture structure of SMA-13 asphalt pavement and assess its anti-skid performance, a light gradient-boosting machine evaluation model was developed using non-contact three-dimensional laser-scanning technology. The study focused on collecting three-dimensional texture data from newly laid SMA-13 asphalt pavement. Subsequently, wavelet transform was employed to reconstruct the pavement’s three-dimensional texture, and discrete Fourier transform was utilized to separate macro- and microtextures, enabling the calculation of their characteristics. The macro- and micro-characteristics of the three-dimensional texture and friction coefficient were input into the model. A comparative analysis with linear regression and a random forest model revealed superior accuracy and efficiency in the model. The training set R2 is 0.948, and the testing set R2 is 0.842, effectively enabling the evaluation of pavement anti-skid performance. An analysis of parameter importance indicated that Rku and MPD are still effective indicators for evaluating skid resistance. Furthermore, diverse texture indexes exhibited varying effects on the anti-skid performance. The established asphalt pavement anti-skid evaluation model serves as a theoretical foundation for understanding the actual influence on pavement anti-skid performance.

Permian Granitic Plutons from the Northern Margin of the North China Craton: Implications for the Tectonic Evolution of the Central Asian Orogenic Belt

As the world’s largest accretionary orogen, the Central Asian Orogenic Belt (CAOB) underwent continuous juvenile crustal growth in the Phanerozoic. The northern margin of the North China Craton (NCC) and its adjacent area form the eastern segment of the CAOB, which is a key area for learning about the geological evolution of the Paleo-Asian Ocean (PAO). In the Permian, the west of the northern margin of the NCC was a post-collision extensional environment, while the east was in a subduction stage. As a connecting area, the Permian evolution of the PAO in the middle of the northern margin of the NCC has not been systematically studied. In order to fill the gap and understand the continuous temporal and spatial evolutionary process of the PAO, this paper focuses on the Permian granitic rocks in the Chifeng area. Zircon U-Pb dating and the geochemical analysis of whole-rock major and trace elements were conducted to build a granite chronological framework, and to discuss the genesis and tectonic background of the granitic rocks, along with tectono-magmatic evolutionary history in the Chifeng area. The respective LA-ICP-MS zircon U-Pb dating results from eight samples are 269 ± 1, 268 ± 3, 260 ± 4, 260 ± 1, 260 ± 1, 255 ± 2, 254 ± 2 and 256 ± 1 Ma, respectively. These results, combined with previous data, revealed that the Permian granitic rocks had undergone three events of magmatism: (1) monzogranitic-syenitic phase (294–284 Ma; Cisuralian); (2) monzogranitic phase (269–260 Ma; Guadalupian) and (3) late monzogranitic-syenitic phase (256–254 Ma; Lopingian). From the Early Permian (294–284 Ma) to the Middle Permian (269–260 Ma), granites with fine-medium-grained locally porphyritic texture and massive structure showed a high-potassium calc-alkaline series formed in a compressional setting, indicating a continuous collision between the Xing’an-Mongolian Orogenic Belt (XMOB) and the NCC. During the Late Permian-Early Triassic (256–248 Ma), granites with massive structure and medium-grained texture in the Chifeng area were magmatism dominated by A- and I-type granites of high-potassium calc-alkaline series, combined with the coeval basic rocks, which constituted a typical “bimodal” rock assemblage. This suggests that the Chifeng area was located in an extensional setting where the subducting slab broke off during the collision between the XMOB and NCC. These granitic plutons from the Permian are believed to have been generated by the subduction-collision of the Paleo-Asian oceanic crust beneath the NCC, according to emplacement time and occurrence location. Our findings provide strong evidence for Permian continuous temporal and spatial tectonic evolution and the characterization of the eventual closure of the PAO in Chifeng area at the northern margin of the NCC.

Tribological Synergism of Anodic Aluminum Oxide Surface Containing Micro-Holes and Nanopores under Lubricated Reciprocation

Micro-drilled aluminum surfaces containing micro-holes were anodized to produce nanopores over the machined and lapped surfaces. The anodized nanopores had an approximate diameter of 30–40 nm and a depth distribution of 20–30 μm from the surface. The diameter and depth of the machined micro-holes were 125 μm and 300 μm, respectively. Anodization itself did not change the surface roughness because the nanopores were very small. Ball-on-disk reciprocating tests were performed under lubricated conditions for 2 h using a frequency of 2 Hz, a load of 2 N, and a travel distance of 5 mm. The results showed that both the micro-drilled and anodized surfaces greatly reduced the coefficient of friction compared with the lapped bare surface; however, the coefficient of friction of the hole-textured specimen was not maintained till the end. Contrary to expectations, the lubricant retention capability of the textured structure declined because of hole failure that occurred during oscillation. This gradually increased friction until the end of the reciprocating test. When the micro-drilled surface was anodized, the coefficient of friction decreased again, implying that non-anodized micro-holes alone were ineffective for reducing friction. The surface hardness of Al increased owing to anodization, and thus the micro-holes remained intact. Therefore, it is concluded in this study that a prerequisite for friction reduction in Al is to increase the hardness to minimize the failure of micro-holes, which can be achieved by anodization. The synergistic lubricant retention capability can be maintained by the presence of both nanopores and micro-holes.

Competitive multi-component bio-syngas separation for hydrogen production: breakthrough dynamics, thermal effects, and adsorbent stability analysis under practical operating conditions

The present work experimentally investigates the ability of zeolite 13X to purify H2 from a multi-component bio-syngas feed [composition (mol%): H2/CH4/CO/CO2 – 51.7/3.4/13.2/31.7] in a bench scale, glass wool insulated column simulating a near-industrial adiabatic environment. The column breakthrough dynamics and thermodynamic interactions are studied as a function of total pressure and feed flow rate. The adsorbent showed excellent separation characteristics with the highest affinity for CO2 followed by CO and CH4, and completely restricts their propagation for pure H2 production. The non-isothermal operation results in forming two distinct temperature fronts and manifests itself by broadening the mass transfer zone, decreasing loadings, and causing an early breakthrough of various adsorbates. The competitive adsorption is confirmed through the presence of roll-ups with a slowly moving CO2 concentration front displacing pre-adsorbed CH4 and CO over the duration of the experiment. Further, dynamic adsorption and desorption (sweep gas: He and CO2) experiments are respectively employed to measure competitive equilibrium loadings of heavy (CO2) and light components (CH4, CO). Additionally, the variation in breakthrough time, adsorbate propagation rate, column peak temperature, breakthrough and effective loading, and competitive selectivities are analyzed and discussed. Finally, a novel methodology to design H2 purification systems is proposed and put to practical use by developing and long duration (∼1500 cycles) testing a pilot scale (feed flow rate: 100 Nm3/h) vacuum pressure swing adsorption system. The cyclic separation unit while generating fuel-cell grade H2, displayed complete operational repeatability, with minimal deviation (<6 %) in adsorbent textural properties and crystalline structure.

Silver nanowire networks on textured silicon as low-emissivity coatings for photovoltaic/thermal applications

Photovoltaic/thermal (PV/T) conversion can convert part of photons into electricity and simultaneously harvest the remaining solar power into heat, which dramatically improves overall solar conversion efficiency and has been recognized as a promising technique for carbon neutrality. However, the textured structure on the surface of crystalline silicon photovoltaic cells greatly enhances the overall mid-infrared emissivity to 0.8 ∼ 0.9, and current research on PV/T low-emissivity coatings does not address this texture structure. Herein, solar-transparent and infrared-reflective silver nanowire networks were introduced to textured silicon surfaces to suppress mid-infrared emissivity and maintain strong solar absorption. The mid-infrared emissivity of the textured silicon is remarkably reduced from 0.97 to 0.19 after coating the silver nanowire networks, while the solar absorptivity is still maintained at a high level with a weighted solar absorptivity of 0.81. Besides, the above-band-gap photon absorptivity of the silver nanowires coating on texture silicon is 0.84 due to the plasmonic effect of the silver nanowire networks and the light trapping effect of the texture structure. The FDTD simulation confirms the spectral selectivity of silver nanowires coating on texture silicon, and the validated energy balance model captures the solar thermal potential of the silver nanowires coating on texture silicon.

Cobalt oxide/polypyrrole derived Co/NC to activate peroxymonosulfate for benzothiazole degradation: Enhanced conversion efficiency of PMS to free radicals

Loading metal on N-doped C material is an effective way of improving the activation efficiency of heterogeneous catalysts for persulfate. Many studies have explored the intrinsic relationship between material modification and enhanced activation efficiency from various aspects. In this study, a cobalt oxide/polypyrrole (Co3O4/PPy) derived Co/NC composite catalyst has been synthesized and used for the activation of PMS. The mechanism study showed that Co/NC can enhance the oxidation efficiency of the reaction system by improving the conversion efficiency of PMS to free radicals. Furthermore, the mechanism of the effect of physicochemical properties of Co/NC (electron transfer capacity, functional bonds, structural texture, etc.) on the conversion of PMS to free radical was explored by regulating the ratio of PPy and metal Co. This study can provide a new catalyst synthesis strategy for the efficient formation of free radicals in heterogeneous persulfate activated systems.

Unleashing the full potential of hyperspectral imaging: Decoupled image and frequency-domain spatial–spectral framework

Hyperspectral image classification (HSIC) is a rapidly developing field that utilizes deep learning methods. However, the reliance on convolutional neural networks (CNNs) for spectral–spatial feature extraction presents certain limitations. Specifically, the use of the fixed-position convolutional kernels in CNNs hinders their ability to capture fully the spectral information around the spatial central pixel, thereby overlooking critical differences between features. To address this issue, a decoupled image- and frequency-domain spectral–spatial framework for HSIC was developed in this study. This method incorporates image- and frequency-domain-based multiscale learnable convolutional attention to refine the differentiating features of the different feature distributions. Additionally, a novel frequency-domain information enhancement module was designed to extract the structural shape and texture details under the semantic constraints of the frequency phase, complementing the image domain to improve the extracted feature maps. Furthermore, a simple and efficient hierarchical feature representation module was introduced to extract both local and global information effectively from the fused features. The experimental results obtained using three open datasets and a practical hyperspectral image of the Gaofen-5 satellite demonstrate that the proposed method outperforms other state-of-the-art HSIC methods.

Crack detection of masonry structure based on thermal and visible image fusion and semantic segmentation

The integration of visible and thermal images has demonstrated the potential ability to enhance crack segmentation accuracy. However, due to the intricate texture of masonry structures and the challenges posed in precisely aligning these cross-modality images, it is necessary to explore pixel-level alignment and develop a comprehensive dataset to enable deep-learning based methods. Therefore, a dataset, Crack900, including five image types, is developed together with a proposed two-step registration to achieve highly accurate pixel-level alignment. In addition, both Train from Scratch and Transfer Learning (TL) strategies are applied on eleven models to investigate the impact of different fused image types. Our findings reveal that the concatenation strategy markedly improves segmentation accuracy, and the performance of TL depends on the compatibility of channel numbers and domain difference between pre-trained and target models. These findings pave the way for further development of cross-modality in masonry crack segmentation methodologies for structural health monitorin.

Exploring the promotion behavior of manganese in Fischer–Tropsch synthesis by changing the interaction patterns between manganese and iron

Mn promoter is widely investigated and employed in Fe-based catalysts. However, it remains a substantial challenge to elucidate how the Mn promoter tunes the product selectivity because the Mn promoter can change crystal structure, particle size, phase composition, etc. simultaneously. Hence, three kinds of newly designed catalysts with different interaction patterns between Mn and Fe were developed in this work to explore the promotion mechanism, including Mn-Fe spinel, core–shell Fe3O4@MnO2 and physical mixing of Fe3O4 and MnO2. Texture structure, reduction behavior and phase transformation of the catalysts were carefully investigated. The Mn content and Mn-Fe interaction pattern determine the strength of the Mn-Fe interaction, which affects the Fe species and FTS performance. Strong Mn-Fe interaction in spinel promotes the generation of ε-Fe2C, reducing C5+ selectivity while enhancing C2-C4 selectivity. C2-C4 O/P ratio of Mn-Fe spinel is dramatically elevated while simultaneously rapidly decreasing over time. Although the Mn-Fe interaction patterns are different, the medium content MnO2-coated Fe3O4 catalyst with strong interaction strength exhibits the similar Fe species and FTS performance feature as Mn-Fe spinel. The decrease in the Mn-Fe interaction strength at high MnO2 coating content contributes to the formation of χ-Fe5C2 and displays the alkaline effect of Mn promotion, i.e., a considerable drop in methane selectivity and an increase in C5+ selectivity. The effect on the FTS performance is relatively moderate for physical mixing of Fe3O4 and MnO2 due to the weak Mn-Fe interaction strength. Combining Fe species and product distribution, χ-Fe5C2 is favorable to produce long-chain hydrocarbons while ε-Fe2C is favorable to produce C2=-C4=. Most importantly, our work is expected to open up a new avenue for guiding the design of efficient catalysts.

Topological electronic structure and spin texture of quasi-one-dimensional higher-order topological insulator Bi4Br4

The notion of topological insulators (TIs), characterized by an insulating bulk and conducting topological surface states, can be extended to higher-order topological insulators (HOTIs) hosting gapless modes localized at the boundaries of two or more dimensions lower than the insulating bulk. In this work, by performing high-resolution angle-resolved photoemission spectroscopy (ARPES) measurements with submicron spatial and spin resolution, we systematically investigate the electronic structure and spin texture of quasi-one-dimensional (1D) HOTI candidate Bi4Br4. In contrast to the bulk-state-dominant spectra on the (001) surface, we observe gapped surface states on the (100) surface, whose dispersion and spin-polarization agree well with our ab-initio calculations. Moreover, we reveal in-gap states connecting the surface valence and conduction bands, which is a signature of the hinge states inside the (100) surface gap. Our findings provide compelling evidence for the HOTI phase of Bi4Br4. The identification of the higher-order topological phase promises applications based on 1D spin-momentum locked current in electronic and spintronic devices.

Image Inpainting based on Gated Convolution and spectral Normalization

Traditional image inpainting methods based on deep learning have the problem of insufficient discrimination between the missing area and the global area information in the feature extraction of image inpainting tasks because of the characteristics of the model constructed by the convolutional layer. At the same time, the traditional generative adversarial network often has problems such as training difficulties and model collapse in the training process. To solve the above problems and improve the repair effect of the model, this paper proposes a dual discriminator image inpainting model based on generative adversarial network combining gated convolution and spectral normalization. The model is mainly composed of an image inpainting module and an image recognition module. The traditional image inpainting model considers all input pixels as valid pixels when extracting the features of the image to be inpainted, which is unreasonable for the image inpainting task. In order to solve this problem, the gated convolution is designed to replace the role of traditional convolution in the image inpainting module. Gated convolutions address the irrationality of ordinary convolutions in image inpainting tasks by providing learnable dynamic feature selection mechanisms for each channel at each spatial location in all layers. At the same time, generative image inpainting models usually have problems such as training hard mode collapse during the training process. In this paper, we intend to introduce the spectral normalization mechanism in the convolutional layer design of the discriminator module. By introducing Lipschitz continuity constraints from the spectral norm of the parameter matrix of each layer of the neural network, the neural network is better insensitive to input perturbations, making the training process more stable and easier to converge. It solves the problems of mode collapse and model training difficulty in the training of image inpainting model based on generative adversarial network. Finally, qualitative and quantitative experiments show that the image inpainting model based on gated convolution and spectral normalization solves the above problems, and the inpainted image has reasonable texture structure and contextual semantic information.

Wavelet Approximation-Aware Residual Network for Single Image Deraining.

It has been made great progress on single image deraining based on deep convolutional neural networks (CNN). In most existing deep deraining methods, CNNs aim to learn a direct mapping from rainy images to clean rain-less images, and their architectures are becoming more and more complex. However, due to the limitation of mixing rain with object edges and background, it is difficult to separate rain and object/background, and the edge details of the image cannot be effectively recovered in the reconstruction process. To address this problem, we propose a novel wavelet approximation-aware residual network (WAAR), wherein rain is effectively removed from both low-frequency structures and high-frequency details at each level separately, especially in low-frequency sub-images at each level. After wavelet transform, we propose novel approximation aware (AAM) and approximation level blending (ALB) mechanisms to further aid the low-frequency networks at each level recover the structure and texture of low-frequency sub-images recursively, while the high-frequency network can effectively eliminate rain streaks through block connection and achieve different degrees of edge detail enhancement by adjusting hyperparameters. In addition, we also introduce block connection to enrich the high-frequency details in the high-frequency network, which is favorable for obtaining potential interdependencies between high- and low-frequency features. Experimental results indicate that the proposed WAAR exhibits strong performance in reconstructing clean and rain-free images, recovering real and undistorted texture structures, and enhancing image edges in comparison with the state-of-the-art approaches on synthetic and real image datasets. It shows the effectiveness of our method, especially on image edges and texture details.

Current Enhancement of Ultrathin GaAs Solar Cells with Rear Light Scattering Structures Using Block Copolymers

Ultrathin GaAs solar cells have gained attention because they are cost‐effective and exhibit high carrier‐collection efficiency and open‐circuit voltage compared with cells with thicker absorber layers. However, ultrathin GaAs solar cells have a low current density due to their thin light‐absorbing layers. To improve the photoabsorption of ultrathin GaAs solar cells, light‐trapping structures with textured front or rear surfaces are necessary, and easy methods for fabricating textured structures are required. In this study, a new method to create light‐scattering textured surfaces using block copolymers is developed. This method only requires spin coating, annealing, and wet etching, making it easily applicable to large‐area devices such as solar cells. An ultrathin GaAs solar cell is fabricated with a rear‐textured structure using block copolymers as masks for wet etching. The results demonstrate that the short‐circuit current density is enhanced by 1.39 mA cm−2, which improves the energy conversion efficiency by 0.71 percentage points compared with a reference cell without a rear‐textured structure.

SIFAT AIR LINDIAN DAN TANAH SERTA RESPON TANAMAN PADA MODIFIKASI TEKSTUR, TEHNIK PENGAIRAN DAN APLIKASI LIMBAH PERIKANAN PADA TANAH LAHAN BASAH GARAMAN DARI DESA PANTAI HARAPAN TANAH LAUT KALIMANTAN SELATAN UNTUK PRODUKSI BAWANG MERAH DAN SAWI SISTEM POT

The nature of the soil is massive and saline, not fertile for horticultural crops such as shallots and mustard greens. The soil properties of Tidal Wetland Type-A (direct), the soil sample mentioned above, is known from the analysis results to have an EC value of 153.5 ds/m (very high), Na (1 NH4Oac) 1.21 me/ 100 g soil (very high), pH (1: 5 H2O) 6.74 (neutral), C-organic (Walkley-Black) 2.08% (medium), clay soil texture (clay 76%) and massive structure, Such land is very difficult for agricultural plants such as horticulture to grow, because it is difficult for the soil to pass water and salt which poisons plants. The application of sand, irrigation methods, and organic materials can change the properties of the soil and support the growth of shallots and mustard greens.

Acidic water tempering and heat treatment, a hurdle approach to reduce wheat Salmonella load during tempering and its effects on flour quality

The cultivation and processing of wheat render it susceptible to microbial contamination from varied sources. Hence, pathogens such as Salmonella can contaminate wheat grains, which poses a food safety risk in wheat-based products. This risk is displayed by the incidence of foodborne illness outbreaks linked to Salmonella-contaminated wheat flour and flour-based products. The purpose of this study was to assess the effectiveness of combining acidic water and heat treatment in reducing the Salmonella load of hard red spring (HRS) wheat grains during tempering. Effective treatments were then evaluated for their effects on wheat flour quality. Tempering with sodium bisulfate (SBS), lactic acid (LA), and citric acid (CA) at 15% w/v alone reduced (p < 0.001) wheat Salmonella load by 3.15, 3.23, and 2.91 log CFU/g, respectively. Heat treatment (55 °C) reduced (p < 0.001) wheat Salmonellaload by 4.1 log CFU/g after 24 h of tempering. Combining both tempering and heat treatments resulted in a greater reduction in Salmonella load as non-detectable levels (<2 log CFU/g) of Salmonella in the wheat grains were obtained after 12 h of tempering with LA (15%) + heat. A similar result were achieved for both SBS (15%) + heat and CA (15%) + heat treatments after 18 h of tempering. Applying the combined treatments in HRS wheat grains resulted in comparable wheat flour baking (volume, texture, and crumb structure) and physicochemical properties (rheology and composition) relative to the control (tempering with water alone). The results from this study has the potential to be utilized for developing more effective methods for improving the food safety of wheat flour against Salmonella contamination.

ENGLISH TEACHERS' ABILITY IN WRITING JOURNAL ARTICLES IN THE INDONESIAN LANGUAGE

&lt;em&gt;This research was conducted to study the language skills of English teachers of senior high schools in Sragen Regency in composing a journal article for publication in Bahasa Indonesia. This is aimed to see the quality of Bahasa Indonesia skills of the teachers in the article even though they have an English education background and they are English teachers at present. Members of the High School English Teachers Association in the regency were involved in the research. A questionnaire consisting of 45 statements was distributed to the teachers. They were asked to give responses and then the collected responses were analysed to see their language quality related to the process of article production. Furthermore, they were also asked to write a journal article in Bahasa Indonesia, and the collected manuscripts were then analysed for their text structure and text texture. The results show that they do not have good knowledge and language skills in identifying as well as producing texts of certain types. Furthermore, they also got problems positioning what type of text to which part of a journal article. This condition indicates that the teachers still need an upgrading program for their language skills to compose a journal article, and in addition, they need others to give a hand during the process of article writing&lt;/em&gt;