Within-process and seasonal changes during industrial production of high-density fibreboard. Part 2: PLS modelling of chemical alterations, refining conditions and panel thickness swell

Holzforschung ◽  
2012 ◽  
Vol 66 (5) ◽  
pp. 673-678 ◽  
Author(s):  
Martin Weigl ◽  
Gerald Maschl ◽  
Rupert Wimmer ◽  
Roland Mitter
Keyword(s):  
Partial Least Squares Regression ◽  
Raw Materials ◽  
Thickness Swell ◽  
High Density ◽  
Raw Material ◽  
Processing Conditions ◽  
Least Squares Regression ◽  
Hemicellulose Degradation ◽  
Potential Impact ◽  
Panel Thickness

Abstract Wood species, carbohydrate composition and the content of extractives were determined from extracted wood chips and refiner fibres over 1 year of sampling at an industrial high-density fibreboard (HDF) plant. Correlations were found among processing variables (discharge screw flow, digester and refiner pressure, and refiner power consumption) and the analysed composition of raw materials and semi-finished product based on partial least squares regression (PLSR) analysis. Moreover, correlations between the degree of hemicellulose degradation and process variables were found. Panel thickness swell (PTS) was found to be affected by several raw and fibre material characteristics (based on PLSR), in which PTS was lower in the case of good fibre quality. These results demonstrate the potential impact of variable raw material properties on product properties and processing conditions in an industrial environment.

Experimental Study of Effecting Factors for Plant Straw Densification

2012 ◽  
Vol 512-515 ◽  
pp. 405-408 ◽  
Author(s):  
Xin Qi Yu ◽  
Xin Lei Wan ◽  
Qing Gang Liu
Keyword(s):  
Experimental Study ◽  
Moisture Content ◽  
Smooth Surface ◽  
Raw Materials ◽  
High Density ◽  
Raw Material ◽  
Corn Straw

In this paper, plant straw densification technology has been studied. The corn straw was taken as raw material in the experiment. The influences of raw material moisture content, densification pressure and raw material size to the compact process have been studied. The results show that the 13%~18% moisture content of the corn straw is the best scope in compact process. When the raw materials are densified at a pressure of 60MPa, the products have smooth surface, high density. While the pressure continuously increases, the increase of density is not obvious. The raw material size 10~20mm are suitable for densification.

scholarly journals Fabrication and Characterization of Hydrogels Based on Gelatinised Collagen with Potential Application in Tissue Engineering

Polymers ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1146 ◽  
Author(s):  
Victor Perez-Puyana ◽  
Mercedes Jiménez-Rosado ◽  
Alberto Romero ◽  
Antonio Guerrero
Keyword(s):  
Tissue Engineering ◽  
Type I Collagen ◽  
Raw Materials ◽  
Gelation Time ◽  
Raw Material ◽  
Type I ◽  
Processing Conditions ◽  
Natural Polymers ◽  
Optimal Processing ◽  
Physical And Chemical

Regenerative medicine is increasingly focused on the development of biomaterials that facilitate cell adhesion and proliferation through the use of natural polymers, which have better biocompatibility and biodegradability. In this way, the use of hydrogels has been considered as a potential option for tissue engineering due to their physical and chemical characteristics. However, few studies associate the raw materials properties and processing conditions with the final characteristics of hydrogels, which could condition their use as scaffolds for tissue engineering. In this context, the main objective of this work was the evaluation of type I collagen as raw material for the elaboration of hydrogels. In addition, gelation time, pH and temperature were evaluated as the most influential variables in the hydrogel processing method by rheological (time, strain and frequency sweep tests) and microstructural (Cryo-SEM) measurements. The results indicate that it is possible to obtain collagen hydrogels with adequate rheological and microstructural characteristics by selecting optimal processing conditions. However, further studies are necessary to assess their suitability for cell accommodation and growth.

Analysis of Color of the Ceramic Coatings Submitted to Different Processing Conditions

2014 ◽  
Vol 798-799 ◽  
pp. 306-311
Author(s):  
Alan de Oliveira Feitosa ◽  
José Elson Soares Filho ◽  
Leonardo Leandro dos Santos ◽  
Romualdo Rodrigues Menezes ◽  
Ricardo Peixoto Suassuna Dutra
Keyword(s):  
Raw Materials ◽  
Ceramic Coatings ◽  
Color Variation ◽  
Raw Material ◽  
Processing Conditions ◽  
Standard Formulation ◽  
Relevant Factor

Color is a very important characteristic in ceramic products. In ceramic coatings, the basis of ceramic is normally classified as red or white basis. Another relevant factor for color variation is the processing to which the material is submitted. In this sense, this work aims to analyze and quantify the color of ceramic pieces used as coatings, which were developed from a formulation of masses, using raw materials such as clay, feldspar, kaolin and quartz. Each raw material was analyzed separately and then a standard formulation was made, involving all of them, and these ones were submitted to different processing temperatures. All the samples were quantified regarding the color, by using the tridimensional colorimetric space by CIELAB method. Results point out that each raw material has an own value regarding color and the temperature has contributed directly to the color variation of the ceramic pieces.

scholarly journals Characterization of Key Aroma Compounds and Construction of Flavor Base Module of Chinese Sweet Oranges

Molecules ◽  
2019 ◽  
Vol 24 (13) ◽  
pp. 2384 ◽  
Author(s):  
Mengzhu Shui ◽  
Tao Feng ◽  
Yanzun Tong ◽  
Haining Zhuang ◽  
Chihkang Lo ◽  
...  
Keyword(s):  
Least Squares ◽  
Partial Least Squares Regression ◽  
Sweet Orange ◽  
Aroma Compounds ◽  
Raw Material ◽  
Least Squares Regression ◽  
Flavor Evaluation ◽  
The World ◽  
Base Module

Sweet orange flavor, with its refreshing, joyful and attractive aroma, is favored by the majority of consumers all over the world. However, the industry terminology between flavorists for flavor evaluation is a bit vague and not intuitive for customers. Therefore, the study focused on analysis of sweet orange aroma and establishment of base module of orange flavor. The approach to the research involves screening key aroma compounds, identifying the attributes aroma and building base module of sweet orange. The notes of sweet orange flavor were determined by GC-O olfaction and sensory evaluation. 25 key aroma compounds with OAV ≥ 1 were screened and divided into eight notes: citrus, fruity, fresh, green, peely, woody, fatty, floral. Partial least squares regression (PLSR) was used to further verify the corresponding relationship between the volatile substances and notes. Terpenes, esters, aldehydes and alcohols compounds can provide these notes. Based on the notes, 8 base modules of sweet orange were built by selecting and matching aroma ingredients. Through this study, beginners could be trained according to the 8 notes of base modules and flavorists can engage in dialogue with different raw material sourcing teams or providers.

scholarly journals Production of Wood Pellets from Poplar Trees Managed as Coppices with Different Harvesting Cycles

Energies ◽  
2019 ◽  
Vol 12 (15) ◽  
pp. 2973 ◽  
Author(s):  
Vincenzo Civitarese ◽  
Andrea Acampora ◽  
Giulio Sperandio ◽  
Alberto Assirelli ◽  
Rodolfo Picchio
Keyword(s):  
Raw Materials ◽  
High Density ◽  
Raw Material ◽  
Wood Pellets ◽  
Heating Value ◽  
Poplar Trees ◽  
Forestry Sector ◽  
Mechanical Durability ◽  
Ash Melting ◽  
Materials Used

High-density biomass plantations have played a key role in the national energy landscape in Italy since the 1990s but, to date, an inversion of tendency and a significant reduction of cultivated areas has been noted. Despite this, the existing plantations have seen their coppicing rotation become significantly lengthened, resulting in large quantities of biomass per hectare. This study aimed to identify the best raw material suitable for pellet production using whole trees or stems without branches from poplar plantations at the end of the third, sixth and ninth year of age. All types of pellets made reach the requirements of class A1 for diameter, length, moisture content, ash melting point, lower heating value, as well as nitrogen (N), sulfur (S), and heavy metals. None of the theses satisfied the bulk density parameters while for ashes and mechanical durability, a great variability was observed according to the different raw materials used. An improvement in terms of heating value was observed by transforming the poplar wood chips refined into pellets. The pelletizing process using high density poplar plantation as a raw material highlights the possibility of obtaining a product that meets many of the quality standards required on the market. These aspects are closely related to the innovation carried out in the agro-forestry sector for effective energetic sustainability.

scholarly journals In-Depth Understanding of Granule Compression Behavior under Variable Raw Material and Processing Conditions

Pharmaceutics ◽  
2022 ◽  
Vol 14 (1) ◽  
pp. 177
Author(s):  
Tibor Casian ◽  
Sonia Iurian ◽  
Alexandru Gâvan ◽  
Alina Porfire ◽  
Anca Lucia Pop ◽  
...  
Keyword(s):  
Microcrystalline Cellulose ◽  
Raw Materials ◽  
Binding Capacity ◽  
Raw Material ◽  
Sensitivity Index ◽  
Processing Conditions ◽  
Water Binding ◽  
Pharmaceutical Ingredients ◽  
Compression Properties ◽  
Addition Rate

Tablet manufacturing involves the processing of raw materials through several unit operations. Thus, the mitigation of input-induced variability should also consider the downstream processability of intermediary products. The objective of the present work was to study the effect of variable raw materials and processing conditions on the compression properties of granules containing two active pharmaceutical ingredients (APIs) and microcrystalline cellulose. Differences in compressibility and tabletability of granules were highlighted in function of the initial particle size of the first API, granule polydispersity and fragmentation. Moreover, interactions were underlined with the atomizing pressure. Changing the supplier of the second API was efficiently controlled by adapting the binder addition rate and atomizing pressure during granulation, considering the starting crystal size. By fitting mathematical models on the available compression data, the influence of diluent source on granule compactibility and tabletability was identified. These differences resumed to the ease of compaction, tableting capacity and pressure sensitivity index due to variable water binding capacity of microcrystalline cellulose. Building the design space enabled the identification of suitable API types and the appropriate processing conditions (spray rate, atomizing pressure, compression force) required to ensure the desired tableting performance.

scholarly journals The Impact of Textile Waste on the Features of High-Density Polyethylene (HDPE) Composites

Urban Science ◽  
2021 ◽  
Vol 5 (3) ◽  
pp. 59
Author(s):  
Ville Lahtela ◽  
Anil Kumar ◽  
Timo Kärki
Keyword(s):  
High Density Polyethylene ◽  
Near Infrared ◽  
Raw Materials ◽  
High Density ◽  
Urban Life ◽  
Raw Material ◽  
Textile Waste ◽  
Future Challenges ◽  
Quality Of Urban Life ◽  
The Impact

An increased amount of textile waste will be available in the future, and its utilization requires attention from various perspectives. The re-utilization of textile waste in a second material cycle is an option for dealing with a global problem that puts stress on the urban environment. In this study, almost 30 kg of clothing were recycled as a raw material in the structure of a composite, whose structural properties were analyzed. The studied materials were made from high-density polyethylene (HDPE), anhydride modified polyethylene, lubricant, and either polyethylene terephthalate (PET) or rayon fibers from recycled clothes. The recycled clothes were identified by a near-infrared (NIR) analyzer, followed by treatment of size reduction and materials compounding by agglomeration and compression molding technologies. The material properties were characterized by thickness swelling, water absorption, impact, and tensile testing. The recycled clothes fibers, acting as a filler component in the structure of the composite, could maintain the properties of the material at the same level as the reference material. PET fibers being used as a component resulted in a significant improvement in impact strength. The study showed that recycled clothes can be re-utilized as a substitute for raw materials, and can be part of a solution for future challenges involving textile waste, following the principles of the circular economy. Textile recycling create opportunities to improve the quality of urban life.

Use of reflectance spectroscopy to estimate the organic carbon and CaCO3 contents of soils

2012 ◽  
Vol 61 (2) ◽  
pp. 277-290 ◽  
Author(s):  
Ádám Csorba ◽  
Vince Láng ◽  
László Fenyvesi ◽  
Erika Michéli
Keyword(s):  
Organic Carbon ◽  
Least Squares ◽  
Partial Least Squares ◽  
Partial Least Squares Regression ◽  
Mean Squared Error ◽  
Reflectance Spectroscopy ◽  
Least Squares Regression ◽  
Root Mean Squared Error ◽  
Squared Error

Napjainkban egyre nagyobb igény mutatkozik olyan technológiák és módszerek kidolgozására és alkalmazására, melyek lehetővé teszik a gyors, költséghatékony és környezetbarát talajadat-felvételezést és kiértékelést. Ezeknek az igényeknek felel meg a reflektancia spektroszkópia, mely az elektromágneses spektrum látható (VIS) és közeli infravörös (NIR) tartományában (350–2500 nm) végzett reflektancia-mérésekre épül. Figyelembe véve, hogy a talajokról felvett reflektancia spektrum információban nagyon gazdag, és a vizsgált tartományban számos talajalkotó rendelkezik karakterisztikus spektrális „ujjlenyomattal”, egyetlen görbéből lehetővé válik nagyszámú, kulcsfontosságú talajparaméter egyidejű meghatározása. Dolgozatunkban, a reflektancia spektroszkópia alapjaira helyezett, a talajok ösz-szetételének meghatározását célzó módszertani fejlesztés első lépéseit mutatjuk be. Munkánk során talajok szervesszén- és CaCO3-tartalmának megbecslését lehetővé tévő többváltozós matematikai-statisztikai módszerekre (részleges legkisebb négyzetek módszere, partial least squares regression – PLSR) épülő prediktív modellek létrehozását és tesztelését végeztük el. A létrehozott modellek tesztelése során megállapítottuk, hogy az eljárás mindkét talajparaméter esetében magas R2értéket [R2(szerves szén) = 0,815; R2(CaCO3) = 0,907] adott. A becslés pontosságát jelző közepes négyzetes eltérés (root mean squared error – RMSE) érték mindkét paraméter esetében közepesnek mondható [RMSE (szerves szén) = 0,467; RMSE (CaCO3) = 3,508], mely a reflektancia mérési előírások standardizálásával jelentősen javítható. Vizsgálataink alapján arra a következtetésre jutottunk, hogy a reflektancia spektroszkópia és a többváltozós kemometriai eljárások együttes alkalmazásával, gyors és költséghatékony adatfelvételezési és -értékelési módszerhez juthatunk.

Speech Emotion Recognition Based on Sparse Representation

2013 ◽  
Vol 38 (4) ◽  
pp. 465-470 ◽  
Author(s):  
Jingjie Yan ◽  
Xiaolan Wang ◽  
Weiyi Gu ◽  
LiLi Ma
Keyword(s):  
Dimensionality Reduction ◽  
Emotion Recognition ◽  
Least Squares ◽  
Partial Least Squares ◽  
Partial Least Squares Regression ◽  
Speech Emotion Recognition ◽  
Least Squares Regression ◽  
Computer Science Pedagogy ◽  
Reduction Methods ◽  
Analysis Computer

Abstract Speech emotion recognition is deemed to be a meaningful and intractable issue among a number of do- mains comprising sentiment analysis, computer science, pedagogy, and so on. In this study, we investigate speech emotion recognition based on sparse partial least squares regression (SPLSR) approach in depth. We make use of the sparse partial least squares regression method to implement the feature selection and dimensionality reduction on the whole acquired speech emotion features. By the means of exploiting the SPLSR method, the component parts of those redundant and meaningless speech emotion features are lessened to zero while those serviceable and informative speech emotion features are maintained and selected to the following classification step. A number of tests on Berlin database reveal that the recogni- tion rate of the SPLSR method can reach up to 79.23% and is superior to other compared dimensionality reduction methods.

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