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The main purpose of this work is to explore the erosion wear characteristics of additively manufactured aluminium alloy. Additive manufacturing (AM), also known as three-dimensional (3D) manufacturing, is the process of manufacturing a part designed in a computer environment using different types of materials such as plastic, ceramic, metal or composite. Similar to other materials, aluminum alloys are also exposed to various wear types during operation. Production efficiency needs to be aware of its reactions to wearing mechanisms.

In this study, quartz sands (SiO₂) assisted with oxide ceramics were used in the slurry erosion test setup and its abrasiveness on the AlSi10Mg aluminum alloy material produced by the 3D printer as selective laser melting (SLM) technology was investigated. Quartz was sieved with an average particle size of 302.5 µm, and a slurry environment containing 5, 10 and 15% quartz by weight was prepared. The experiments were carried out at the velocity of 1.88 (250 rpm), 3.76 (500 rpm) and 5.64 m/s (750 rpm) and the impact angles 15, 45 and 75°.

With these experimental studies, it has been determined that the abrasiveness of quartz sand prepared in certain particle sizes is directly related to the particle concentration and particle speed, and that the wear increases with the increase of the concentration and rotational speed. Also, the variation of weight loss and surface roughness of the alloy was investigated after different wear conditions. Surface roughness values at 750 rpm speed, 10% concentration and 75° impingement angle are 0.32 and 0.38 µm for 0 and 90° samples, respectively, with a difference of approximately 18%. Moreover, concerning a sample produced at 0°, the weight loss at 250 rpm at 10% concentration and 45° particle impact angle is 32.8 mg, while the weight loss at 500 rpm 44.4 mg, and weight loss at 750 rpm is 104 mg. Besides, the morphological structures of eroded surfaces were examined using the scanning electron microscope to understand the wear mechanisms.

The researchers verified that this specific coating condition increases the slurry wear resistance of the mentioned steel. There are many studies about slurry wear tests; however, there is no study in the literature about the quartz sand (SiO₂) assisted slurry-erosive wear of AlSi10Mg alloy produced with AM by using SLM technology. This study is needed to fill this gap in the literature and to examine the erosive wear capability of this current material in different environments. The novelty of the study is the use of SiO₂ quartz sands assisted by oxide ceramics in different concentrations for the slurry erosion test setup and the investigations on erosive wear resistance of AlSi10Mg alloy manufactured by AM.

Following the recommendation of the food and agriculture organization of the United Nations in agricultural innovation, for taking advantage of emerging technologies, in benefit of small-farmers, the present study explores one of the most ancient crops in the world that privileging the application of tacit knowledge, to become a succulent plant called agave, into the so-called drink of the gods, the mezcal. For this, the purpose of this study is to discover innovation opportunities and reconfiguring knowledge interaction dynamics of the agricultural artisan production of agave-mezcal from Oaxaca, Mexico, using emerging technologies

Following a qualitative-quantitative approach, the study was carried out with 44 mezcal producers from Oaxaca, Mexico, through face-to-face session, questionaries’ application and field visits, based on the model of socialization, externalization, combination and internalization (SECI) through Likert-scale questions, combining the non-parametric statistical analysis and digital compass, for the detection of technological opportunities

Basing on artisanal process, context-knowledge place, technological resources and SECIs model results, the opportunities must go in the route of labour in the logic of digital performance. In this sense, becomes relevant to develop an easy-use mobile application for improving the interaction of mezcaleros with external agents and another’s producers., A second proposal is the creation of mezcal-tech-hub, thinking as collaborative space, for promoting the interaction producer-to-producer and producer-to-external agent.

The value of the present study is the empirical description of knowledge dynamics interaction contained in the agricultural artisan production of agave-mezcal through SECI model; the identification of problems, failure or barriers contained in the knowledge interaction dynamics of the agricultural artisan production agave-mezcal; the proposal of innovation opportunities for reconfiguring the knowledge interaction dynamics of the agricultural artisan production agave-mezcal from a developing economy, using emerging technologies.

Hate speech is an expression of intense hatred. Twitter has become a popular analytical tool for the prediction and monitoring of abusive behaviors. Hate speech detection with social media data has witnessed special research attention in recent studies, hence, the need to design a generic metadata architecture and efficient feature extraction technique to enhance hate speech detection.

This study proposes a hybrid embeddings enhanced with a topic inference method and an improved cuckoo search neural network for hate speech detection in Twitter data. The proposed method uses a hybrid embeddings technique that includes Term Frequency-Inverse Document Frequency (TF-IDF) for word-level feature extraction and Long Short Term Memory (LSTM) which is a variant of recurrent neural networks architecture for sentence-level feature extraction. The extracted features from the hybrid embeddings then serve as input into the improved cuckoo search neural network for the prediction of a tweet as hate speech, offensive language or neither.

The proposed method showed better results when tested on the collected Twitter datasets compared to other related methods. In order to validate the performances of the proposed method, t-test and post hoc multiple comparisons were used to compare the significance and means of the proposed method with other related methods for hate speech detection. Furthermore, Paired Sample t-Test was also conducted to validate the performances of the proposed method with other related methods.

Finally, the evaluation results showed that the proposed method outperforms other related methods with mean F1-score of 91.3.

The main novelty of this study is the use of an automatic topic spotting measure based on naïve Bayes model to improve features representation.

This study aims to formulate multiple nutritionally improved snacks intended for school-aged children according to international nutritional goals: Vanilla cookies (VC), Bay biscuits (BB), Cheese crackers (CC) and Tomato muffins (TM).

The reformulation targets implied incorporating alternative flours and milk powder and reducing the sugar and sodium contents, with respect to the usually consumed control products. These products were subjected to proximate composition, colour and sensory profile analyses. Their overall acceptability was assessed by school-aged children whose nutritional status was also evaluated.

Significant increments in relevant nutrients were observed in the composition of snacks: fibre (p = 0.01 for VC, p < 0.01 for BB and CC), proteins (p < 0.01 for all snacks) and calcium (p < 0.01 for all snacks). Average sodium reductions of 1.5% and 3.7% were achieved for CC and TM. During formulation, added sugar was reduced by 15.5% and 23.5% for VC and BB. All snacks were found to be acceptable in terms of appearance, texture, flavour and overall acceptability by the participants, and VC, BB and CC were ready for their effective implementation as part of school meals.

Comprehensive policies have become necessary to combat malnutrition, mainly overweight and obesity. The incorporation of nutritionally improved snacks in school environments is one of several strategies for promoting healthier lifestyles among children, including educational programs, workshops and food assistance.

Additively manufactured objects have layered structures, which means post processing is often required to achieve a desired surface finish. Furthermore, the additive nature of the process makes it less accurate than subtractive processes. Hence, additive manufacturing techniques could tremendously benefit from finishing processes to improve their geometric tolerance and surface finish.

Rotary ultrasonic machining (RUM) was chosen as a finishing operation for drilling additively manufactured carbon fiber reinforced polymer (CFRP) composites. Two distinct additive manufacturing methods of fused deposition modeling (FDM) and laser-assisted laminated object manufacturing (LA-LOM) were used to fabricate CFRP plates with continuous carbon fiber reinforcement. The influence of the feedrate, tool rotation speed and ultrasonic power of the RUM process parameters on the aforementioned quality characteristics revealed the feasibility of RUM process as a finishing operation for additive manufactured CFRP.

The quality of drilled holes in the CFRP plates fabricated via LA-LOM was supremely superior to the FDM counterparts with less pullout delamination, smoother surface and less burr formation. The strong interfacial bonding in LA-LOM proven to be superior to FDM was able to endure higher cutting force of the RUM process. The cutting force and cutting temperature overwhelmed the FDM parts and induced higher surface damage.

Overall, the present study demonstrates the feasibility of a hybrid additive and subtractive manufacturing method that could potentially reduce cost and waste of the CFRP production for industrial applications.

This paper aims to focus on an experimental study of surface roughness, dimensional accuracy and time of fabrication of parts produced by fused deposition modelling (FDM) technique of additive manufacturing. The fabricated parts of acrylonitrile butadiene styrene (ABS) material have pyramidal and conical features. Influence of five process parameters of FDM, namely, layer thickness, wall print speed, build orientation, wall thickness and extrusion temperature is studied on response characteristics. Furthermore, regression models for responses are developed and significant process parameters are optimized.

Comprehensive experimental study is performed using response surface methodology. Analysis of variance is used to investigate the influence of process parameters on surface roughness, dimensional accuracy and time of fabrication in both outer pyramidal and inner conical regions of part. Furthermore, a multi-response optimization using desirability function is performed to minimize surface roughness, improve dimensional accuracy and minimize time of fabrication of parts.

It is found that layer thickness and build orientation are significant process parameters for surface roughness of parts. Surface roughness increases with increase in layer thickness, while it decreases initially and then increases with increase in build orientation. Layer thickness, wall print speed and build orientation are significant process parameters for dimensional accuracy of FDM parts. For the time of fabrication, layer thickness and build orientation are found as significant process parameters. Based on the analysis, statistical non-linear quadratic models are developed to predict surface roughness, dimensional accuracy and time of fabrication. Optimization of process parameters is also performed using desirability function.

The present study is restricted to the parts of ABS material with pyramidal and conical features only fabricated on FDM machine with delta configuration.

From the critical review of literature it is found that some researchers have made to study the influence of few process parameters on surface roughness, dimensional accuracy and time of fabrication of simple geometrical parts. Also, regression models and optimization of process parameters has been performed for simple parts. The present work is focussed on studying all these aspects in complicated geometrical parts with pyramidal and conical features.