Experimental Investigation of Vertical Density Profile of Medium Density Fiberboard in Hot Press

This research investigates the performance of medium density fiberboard (MDF) with respect to hot press parameters. The performance of the board, type of glue, and production efficiency determine the optimum temperature and pressure for hot pressing. The actual temperature of the hot press inside the MDF board determines the properties of the final product. Hence, the optimal hot press parameters for the desired product are experimentally obtained. Moreover, MDF is experimentally investigated in terms of its vertical density profile, bending, and internal bonding under the various input parameters of temperature, pressure, cycle time, and moisture content during the manufacturing process. The experimental study is carried out by varying the temperature, pressure, cycle time, and moisture content in the ranges of 200–220 °C, 145–155 bar, 260–275 s, and 8–10%, respectively. Consequently, the optimum input parameters of a hot-pressing temperature of 220 °C, pressure of 155 bar, cycle time of 256 s, and moisture content of 8% are identified for the required internal bonding (0.64 N/mm2), bending (32 N/mm2), and increase in both the core and peak density of the vertical density profile as per the ASTM standard

Performance evaluation of phosphonium based deep eutectic solvents coated cerium oxide nanoparticles for CO2 capture

The critical challenge being faced by our current modern society on a global scale is to reduce the surging effects of climate change and global warming, being caused by anthropogenic emissions of CO2 in the environment. Present study reports the surface driven adsorption potential of deep eutectic solvents (DESs) surface functionalized cerium oxide nanoparticles (CeNPs) for low pressure CO2 separation. The phosphonium based DESs were prepared using tetra butyl phosphoniumbromide as hydrogen bond acceptor (HBA) and 6 acids as hydrogen bond donors (HBDs). The as-developed DESs were characterized and employed for the surface functionalization of CeNPs with their subsequent utilization in adsorption-based CO2 adsorption. The synthesis of as-prepared DESs was confirmed through FTIR measurements and absence of precipitates, revealed through visual observations. It was found that DES6 surface functionalized CeNPs demonstrated 27% higher adsorption performance for CO2 capturing. On the contrary, DES3 coated CeNPs exhibited the least adsorption progress for CO2 separation. The higher adsorption performance associated with DES6 coated CeNPs was due to enhanced surface affinity with CO2 molecules that must have facilitated the mass transport characteristics and resulted an enhancement in CO2 adsorption performance. Carboxylic groups could have generated an electric field inside the pores to attract more polarizable adsorbates including CO2, are responsible for the relatively high values of CO2 adsorption. The quadruple movement of the CO2 molecules with the electron-deficient and pluralizable nature led to the enhancement of the interactive forces between the CO2 molecules and the CeNPs decorated with the carboxylic group hydrogen bond donor rich DES. The current findings may disclose the new research horizons and theoretical guidance for reduction in the environmental effects associated with uncontrolled CO2 emission via employing DES surface coated potential CeNPs

Development and Comparative Analysis of Electrochemically Etched Tungsten Tips for Quartz Tuning Fork Sensor

Quartz Tuning Fork (QTF) based sensors are used for Scanning Probe Microscopes (SPM), in particular for near-field scanning optical microscopy. Highly sharp Tungsten (W) tips with larger cone angles and less tip diameter are critical for SPM instead of platinum and iridium (Pt/Ir) tips due to their high-quality factor, conductivity, mechanical stability, durability and production at low cost. Tungsten is chosen for its ease of electrochemical etching, yielding high-aspect ratio, sharp tips with tens of nanometer end diameters, while using simple etching circuits and basic electrolyte chemistry. Moreover, the resolution of the SPM images is observed to be associated with the cone angle of the SPM tip, therefore Atomic-Resolution Imaging is obtained with greater cone angles. Here, the goal is to chemically etch W to the smallest possible tip apex diameters. Tips with greater cone angles are produced by the custom etching procedures, which have proved superior in producing high quality tips. Though various methods are developed for the electrochemical etching of W wire, with a range of applications from scanning tunneling microscopy (SPM) to electron sources of scanning electron microscopes, but the basic chemical etching methods need to be optimized for reproducibility, controlling cone angle and tip sharpness that causes problems for the end users. In this research work, comprehensive experiments are carried out for the production of tips from 0.4 mm tungsten wire by three different electrochemical etching techniques, that is, Alternating Current (AC) etching, Meniscus etching and Direct Current (DC) etching. Consequently, sharp and high cone angle tips are obtained with required properties where the results of the W etching are analyzed, with optical microscope, and then with field emission scanning electron microscopy (FE-SEM). Similarly, effects of varying applied voltages and concentration of NaOH solution with comparison among the produced tips are investigated by measuring their cone angle and tip diameter. Moreover, oxidation and impurities, that is, removal of contamination and etching parameters are also studied in this research work. A method has been tested to minimize the oxidation on the surface and the tips were characterized with scanning electron microscope (SEM)

The International Natural Product Sciences Taskforce (INPST) and the power of Twitter networking exemplified through #INPST hashtag analysis

Background: The development of digital technologies and the evolution of open innovation approaches have enabled the creation of diverse virtual organizations and enterprises coordinating their activities primarily online. The open innovation platform titled "International Natural Product Sciences Taskforce" (INPST) was established in 2018, to bring together in collaborative environment individuals and organizations interested in natural product scientific research, and to empower their interactions by using digital communication tools. Methods: In this work, we present a general overview of INPST activities and showcase the specific use of Twitter as a powerful networking tool that was used to host a one-week "2021 INPST Twitter Networking Event" (spanning from 31st May 2021 to 6th June 2021) based on the application of the Twitter hashtag #INPST. Results and Conclusion: The use of this hashtag during the networking event period was analyzed with Symplur Signals (https://www.symplur.com/), revealing a total of 6,036 tweets, shared by 686 users, which generated a total of 65,004,773 impressions (views of the respective tweets). This networking event's achieved high visibility and participation rate showcases a convincing example of how this social media platform can be used as a highly effective tool to host virtual Twitter-based international biomedical research events

Predicting Friendship Levels in Online Social Networks

Abstract Context: Online social networks such as Facebook, Twitter, and MySpace have become the preferred interaction, entertainment and socializing facility on the Internet. However, these social network services also bring privacy issues in more limelight than ever. Several privacy leakage problems are highlighted in the literature with a variety of suggested countermeasures. Most of these measures further add complexity and management overhead for the user. One ignored aspect with the architecture of online social networks is that they do not offer any mechanism to calculate the strength of relationship between individuals. This information is quite useful to identify possible privacy threats. Objectives: In this study, we identify users’ privacy concerns and their satisfaction regarding privacy control measures provided by online social networks. Furthermore, this study explores data mining techniques to predict the levels/intensity of friendship in online social networks. This study also proposes a technique to utilize predicted friendship levels for privacy preservation in a semi-automatic privacy framework. Methods: An online survey is conducted to analyze Facebook users’ concerns as well as their interaction behavior with their good friends. On the basis of survey results, an experiment is performed to justify practical demonstration of data mining phases. Results: We found that users are concerned to save their private data. As a precautionary measure, they restrain to show their private information on Facebook due to privacy leakage fears. Additionally, individuals also perform some actions which they also feel as privacy vulnerability. This study further identifies that the importance of interaction type varies while communication. This research also discovered, “mutual friends” and “profile visits”, the two non-interaction based estimation metrics. Finally, this study also found an excellent performance of J48 and Naïve Bayes algorithms to classify friendship levels. Conclusions: The users are not satisfied with the privacy measures provided by the online social networks. We establish that the online social networks should offer a privacy mechanism which does not require a lot of privacy control effort from the users. This study also concludes that factors such as current status, interaction type need to be considered with the interaction count method in order to improve its performance. Furthermore, data mining classification algorithms are tailor-made for the prediction of friendship levels

Predicting Friendship Levels in Online Social Networks

Abstract Context: Online social networks such as Facebook, Twitter, and MySpace have become the preferred interaction, entertainment and socializing facility on the Internet. However, these social network services also bring privacy issues in more limelight than ever. Several privacy leakage problems are highlighted in the literature with a variety of suggested countermeasures. Most of these measures further add complexity and management overhead for the user. One ignored aspect with the architecture of online social networks is that they do not offer any mechanism to calculate the strength of relationship between individuals. This information is quite useful to identify possible privacy threats. Objectives: In this study, we identify users’ privacy concerns and their satisfaction regarding privacy control measures provided by online social networks. Furthermore, this study explores data mining techniques to predict the levels/intensity of friendship in online social networks. This study also proposes a technique to utilize predicted friendship levels for privacy preservation in a semi-automatic privacy framework. Methods: An online survey is conducted to analyze Facebook users’ concerns as well as their interaction behavior with their good friends. On the basis of survey results, an experiment is performed to justify practical demonstration of data mining phases. Results: We found that users are concerned to save their private data. As a precautionary measure, they restrain to show their private information on Facebook due to privacy leakage fears. Additionally, individuals also perform some actions which they also feel as privacy vulnerability. This study further identifies that the importance of interaction type varies while communication. This research also discovered, “mutual friends” and “profile visits”, the two non-interaction based estimation metrics. Finally, this study also found an excellent performance of J48 and Naïve Bayes algorithms to classify friendship levels. Conclusions: The users are not satisfied with the privacy measures provided by the online social networks. We establish that the online social networks should offer a privacy mechanism which does not require a lot of privacy control effort from the users. This study also concludes that factors such as current status, interaction type need to be considered with the interaction count method in order to improve its performance. Furthermore, data mining classification algorithms are tailor-made for the prediction of friendship levels

Fuzzy Logic-Based Prediction of Drilling-Induced Temperatures at Varying Cutting Conditions along with Analysis of Chips Morphology and Burrs Formation

Friction and plastic deformation at the tool–chips interaction during a dry drilling process results in temperature rise and promotes tool wear and surface roughness. In most of the components produced in industries, a drilling process is used to make a hole for final assembly. Therefore, knowledge of temperatures produced during drilling operation at various machining input parameters is required for the best quality product. A fuzzy logic-based algorithm is developed to predict the temperature generated in the drilling process of AISI 1018 mild steel. The algorithm used speed and feed rate of the drill bit as input parameters to the fuzzy domain. A set of rules was used in the fuzzy domain to predict maximum temperature produced in the drilling process. The developed algorithm is simulated for various input speed and feed rate parameters and was verified through the maximum temperature measured during drilling of the studied material at selected speed–feed combinations. Experiments were conducted to validate the results of developed fuzzy logic-based algorithm by using non-contact infrared pyrometer for drilling of AISI 1018 steel. A good agreement between the predicted and experimentally measured maximum temperature was observed with an error less than 6%. It is found that temperature increases with increase in cutting speed and feed rate. Size of roll back burr formation at the hole perimeter significantly increases with increase in drill speed and feed rate. Segmental continuity in spiral or helix chips morphology is more at low feed and high cutting speed. Chip radius increases with increase in feed rate and results in damaging of the machined surface and causes burr formation while the radius decreases with cutting speed along with improved hole surface finish

Effect of Polymerization of Aniline on Thermal Stability, Electrical Conductivity and Band Gap of Graphene Oxide/PolyanilineNanocomposites

Effect of the polymerization of aniline on graphene oxide (GO) surface on the thermal stability, electrical and optical properties of GO has been studied through its chemical functionalization with aniline and polyaniline. GO obtained through liquid ex-foliation of graphite flakes was further covalently coupled with aniline and PANI through imidation protocol in order to extend its piconjugation and to study its effect on opto-electronic properties. Band gap of pristine as well as chemically modified GO was calculated through UV-Vis spectroscopy. It was found that after functionalization, band gap of GO decreased from 3.82 eV to 2.87eV. Furthermore, the conductivity of GO increased from 96.04 S/cm to 139.87 S/cm after modifying with PANI. XRD, FTIR, TGA and elemental analysis data have supported the difference in the properties of modified GO with aniline and PANI. Finally, TGA analysis showed that the thermal stability of GO was enhanced up to 20% due to the addition of PANI

Bioresource Nutrient Recycling in the Rice–Wheat Cropping System: Cornerstone of Organic Agriculture

This study evaluated the impact of conventional practices (fertilizer alone) and diverse farming approaches (such as green manuring, farmyard manure application, rice-residue incorporation, residue mulching, residue removal and residue burning) on soil attributes. A total of thirty-five farm sites were selected, with five sites (replications) for each farming approach system, which were used over the past three years in the study farms. Characterization of rice residues of all cultivars, green manure crop (sesbenia: Sesbania sesban) and decomposed farmyard manure samples showed differential behaviours for macronutrients and micronutrients. Continuous application of inorganic fertilizers significantly influenced soil attributes, especially electrical conductivity, nutrient contents, bacterial and fungal population and soil enzymatic attributes. The crop residue treatments favourably influenced the soil parameters over the control. Crop residue incorporation or burning significantly increased soil available potassium, microbial biomass, enzymatic activities and organic carbon when compared with applications of chemical fertilizer alone, while total nitrogen content was increased by residue incorporation. However, green manuring and farmyard manure applications showed inferior responses compared with residue management treatment. It is therefore recommended that bioresources should be managed properly to warrant improvements in soil properties, nutrient recycling and the sustainability for crop productivity, in order to achieve sustainable development goals for climate action

Bioresource Nutrient Recycling in the Rice–Wheat Cropping System: Cornerstone of Organic Agriculture

This study evaluated the impact of conventional practices (fertilizer alone) and diverse farming approaches (such as green manuring, farmyard manure application, rice-residue incorporation, residue mulching, residue removal and residue burning) on soil attributes. A total of thirty-five farm sites were selected, with five sites (replications) for each farming approach system, which were used over the past three years in the study farms. Characterization of rice residues of all cultivars, green manure crop (sesbenia: Sesbania sesban) and decomposed farmyard manure samples showed differential behaviours for macronutrients and micronutrients. Continuous application of inorganic fertilizers significantly influenced soil attributes, especially electrical conductivity, nutrient contents, bacterial and fungal population and soil enzymatic attributes. The crop residue treatments favourably influenced the soil parameters over the control. Crop residue incorporation or burning significantly increased soil available potassium, microbial biomass, enzymatic activities and organic carbon when compared with applications of chemical fertilizer alone, while total nitrogen content was increased by residue incorporation. However, green manuring and farmyard manure applications showed inferior responses compared with residue management treatment. It is therefore recommended that bioresources should be managed properly to warrant improvements in soil properties, nutrient recycling and the sustainability for crop productivity, in order to achieve sustainable development goals for climate action