Structure of miniature components from steel produced by forming in semi-solid state

To obtain new unconventional structures with specific mechanical and physical properties is possible not only by the development of new types of materials but also by treatment of conventional materials using unconventional innovative technological procedures.One of these technologies is the forming in semi-solid state involving rapid solidification of miniature components from steels.Production of such components is complicated by a number of technical problems.To explain phenomena of the process and structure development,the production of miniature components from the tool steel X210Cr12 difficult to form was experimentally tested.The structure of this originally ledeburite steel consisted of 95 % of metastable austenite after the treatment.Metastable austenite was located particularly in globular and polygonal grains while the remaining interspaces were filled by lamellar network.The detected high stability of extremely high fraction of metastable austenite was tested under different conditions of thermal exposition and mechanical loading.

The Effect of Inorganic Nanoadditives on the Thermal, Mechanical and UV Radiation Barrier Properties of Polypropylene Fibres

The objective of this study of modified polypropylene (PP) fibres using nanoadditives (nano-CaCO3 and Cloisite 30B) was to determine the influence of these additives on thermal and mechanical properties, but especially on the barrier properties of the nanocomposite fibres against UV radiation. The DSC data obtained from measurements of PP/CaCO3 or PP/C30B nanocomposite fibres were used for determination of the constants n and K of the Avrami equation and in the estimation of other thermal properties of the fibres, such as their crystallization half-time t1/2, rate of crystallization t1/2, the necessary time for maximum crystallization tmax and free energy per unit area of surface in the lamella perpen-dicular to the axis of a high-molecular chain se. The nano-CaCO3 or Closite 30B fillers (pre-treated separately in three different solvents: glycerine, acetone and water) did not influence the melting temperatures but caused an increase in PP crystallization temperatures in comparison with the pure PP fibres. The pre-treatments of nanoadditives resulted in increase of n, K, t1/2 values and decrease of t1/2, tmax as well as the values of free surface energies per unit area of the modified PP fibres. There was also observed a decrease in the mechanical properties, however, there was an increase of barrier properties against UV radiation of nanocomposite PP fibres in comparison with neat PP fibres, which was one of the main objectives of the study.

Synthesis,Characterizations and in Vitro Assessment of the Cytotoxicity and Genotoxicity of Novel Silicon Nitride-Based Porous Ceramics

Porous Si3N4-SiO2-based ceramics with different porosity were prepared via free sintering of Si3N4 on air with an addition of semolina (5, 10 and 20 wt%) as a pore-forming agent. The semolina content in the starting powder controlled the volume fraction of pores in the sintered body. Small pores (5 μm) formed a continuous network in the whole volume of the ceramic material, while the large pores (~100 μm), formed from the added semolina were mostly isolated in the ceramic matrix. Mercury porosimetry and strength measurements have shown that specific surface area, volume density and compressive strength decreased with the amount of semolina in the samples. Mechanical properties similar to bone were obtained for the sample with 20 wt% semolina pore forming agent (compressive strength 350 MPa, density 2.17 g.cm-3). The prepared Si3N4-SiO2-based ceramics were evaluated for cytotoxic and genotoxic potential on human fibroblast VH10 and B-HNF-1 cells. Biological tests have shown that both these human fibroblast cell lines were sensitive to the samples with lower porosity and cell growth inhibition was observed in the range 14.9% - 21.3%. The cytotoxicity of the sample with the highest porosity (~40%) was not significant (10%). The microscopic observations have shown that VH10 and B-HNF-1 cells growing around the silicon nitride ceramic discs were homogeneously distributed on the cultivation surface. No significant morphologic changes were found in treated cells, their morphology was very similar to that of the control cells. None of the tested Si3N4-based ceramic samples induced necrotic/apoptotic death of human fibroblasts. Sample S-20 had similar properties to bones and was characterized by very good biocompatibility, slight cytotoxicity and none genotoxicity. Therefore, Si3N4-SiO2-based ceramics prepared by free sintering on air are potential biomaterials for medical applications.

Perceived Injustices in Forest Policy Interventions are Causes of Forest Resources Degradation and Loss in Ghana: A Review

Forests provide diverse co-benefits, including livelihoods enhancement, poverty alleviation, and biodiversity conservation and ecosystem services such as climate mitigation. Consequently, Ghana has embraced several global, regional, national, and local forest policy interventions to safeguard its forest resources’ sustainable management. However, the forest policy interventions have not adequately addressed the co-benefits issues of forest resources leading to several forest illegalities that drive forest resources degradation and loss. These forest policies and interventions on the ground primarily favour carbon stocks enhancement and sequestration activities for carbon mitigation purposes compared to the benefits, access and rights that forest-dependent people and communities are supposed to derive from forest resources. These perceived injustices in the access and distribution of forest resources have culminated into all forms of forest illegalities driving Ghana’s forest resources into massive degradation and loss. Currently, Ghana is experiencing a 2% rate of annual deforestation and forest degradation, which translates into approximately 135,000 ha/year of forest cover loss due to anthropogenic causes. Our review is based on relevant and critical forest documents, and scientific peer-reviewed papers on Ghana’s forest policy interventions and dynamics recently published. The information gathered enabled us to highlight the perceived injustices in the forest policy interventions and their effects on forest resources. Unjust forest resources sharing and distribution are critical drivers of forest resources degradation and loss. We thus offer lessons for remedying the unfair distribution and injustices to promote equitable forest resources rights and benefit access to local forest-dependent people. It is expected that this review will offer and assist forest policy, intervention spatial and other planners and designers to find a possible way forward to avoid nature degradation, including biodiversity loss, to resolve perceived injustices in the forestry sector, to use adequate all ecosystem services provided by forests as well as to promote local livelihood and sustainability.

Evaluation of Uncertainties Related to the Near Field Model of Geological Repository for Spent Nuclear Fuel

In Slovakia, a direct disposal of spent nuclear fuel in a deep geological repository within the country after a certain period of interim storage is a preferred option. This paper briefly describes near field model of radionuclide migration developed in GoldSim simulation code environment and analyses the calculated results on time-dependent release rates of safety relevant radionuclides. Given the fact that GoldSimalso enables to perform probabilistic simulations using the Monte Carlo method, a probabilistic approach was chosen to assess the influence of selected near field parameter uncertainties related to radionuclide migration on the radionuclide release rates from the bentonite buffer to the surrounding host rock. Based on the results, release rates of nuclides which exceed their solubility limits are effectively lowered and many of nuclides are significantly sorbed on the buffer material. It can be seen that the variance of the total release rate in the case of solubility uncertainty is almost two orders of magnitude within a long period of time.

Prediction of External Exposure during Dismantling of Steam Generator

The decommissioning of nuclear power plants is in the Slovak Republic an actual issue. In 2015 started the second decommissioning stage of nuclear power plant V1 in Jaslovské Bohunice. This stage involves the dismantling and segmentation of activated (reactor pressure vessel, reactor internals) and contaminated parts (steam generators, pressurizer). From this reason it is necessary to investigate the radiation situation in the vicinity of the component to be cut. The presented results show that during remote dismantling the exposure is small (compared with the fragmentation tasks). Moreover, when the pre-dismantling decontamination with decontamination factor of 100 is applied, the total collective effective dose is below the yearly limit of 20 mSv for workers.

Mossbauer Spectroscopy of Fe-Ni-Nb-B Alloy in Weak Magnetic Field

Amorphous and nanocrystalline (Fe1–xNix)81Nb7B12 (x = 0, 0.25, 0.5, 0.75) alloys were measured by M?ssbauer spectrometry in the weak external magnetic field of 0.5 T. From structural analyses, ferromagnetic bcc-FeNi and fcc-FeNi and paramagnetic (Fe-Ni)23B6 phases were identified in the annealed samples. It was shown that in the external magnetic field the intensities of the 2nd and the 5th lines (A23 parameter) are the most sensitive M?ssbauer parameters. Rather small changes were observed in the values of internal magnetic field. Our results showed that the amorphous precursor is more sensitive to the influence of external magnetic field than the nanocrystalline alloy. All spectra of amorphous precursor showed the increase of A23 parameter and decrease of internal magnetic field values of about 1 T (±0.5 T) under influence of external magnetic field. In the case of nanocrystalline samples the tendency for the values of internal magnetic field is similar but the effect is not so pronounced. The measurements confirmed that even weak external magnetic field affected orientation of the net magnetic moments. Our results indicate that effect of the external magnetic field is stronger in the case of amorphous samples due to their disordered structure.

Two Layer Symmetric Cryptography Algorithm for Protecting Data from Attacks

Many organizations have insisted on protecting the cloud server from the outside,although the risks of attacking the cloud server are mostly from the inside.There are many algorithms designed to protect the cloud server from attacks that have been able to protect the cloud server attacks.Still,the attackers have designed even better mechanisms to break these security algorithms.Cloud cryptography is the best data protection algorithm that exchanges data between authentic users.In this article,one symmetric cryptography algorithm will be designed to secure cloud server data,used to send and receive cloud server data securely.A double encryption algorithm will be implemented to send data in a secure format.First,the XOR function will be applied to plain text,and then salt technique will be used.Finally,a reversing mechanism will be implemented on that data to provide more data security.To decrypt data,the cipher text will be reversed,salt will be removed,andXORwill be implemented.At the end of the paper,the proposed algorithm will be compared with other algorithms,and it will conclude how much better the existing algorithm is than other algorithms.

Preventing Cloud Network from Spamming Attacks Using Cloudflare and KNN

Cloud computing is one of the most attractive and cost-saving models,which provides online services to end-users.Cloud computing allows the user to access data directly from any node.But nowadays,cloud security is one of the biggest issues that arise.Different types of malware are wreaking havoc on the clouds.Attacks on the cloud server are happening from both internal and external sides.This paper has developed a tool to prevent the cloud server from spamming attacks.When an attacker attempts to use different spamming techniques on a cloud server,the attacker will be intercepted through two effective techniques:Cloudflare and K-nearest neighbors(KNN)classification.Cloudflare will block those IP addresses that the attacker will use and prevent spamming attacks.However,the KNN classifiers will determine which area the spammer belongs to.At the end of the article,various prevention techniques for securing cloud servers will be discussed,a comparison will be made with different papers,a conclusion will be drawn based on different results.

Aspect Level Songs Rating Based Upon Reviews in English

With the advancements in internet facilities,people are more inclined towards the use of online services.The service providers shelve their items for e-users.These users post their feedbacks,reviews,ratings,etc.after the use of the item.The enormous increase in these reviews has raised the need for an automated system to analyze these reviews to rate these items.Sentiment Analysis(SA)is a technique that performs such decision analysis.This research targets the ranking and rating through sentiment analysis of these reviews,on different aspects.As a case study,Songs are opted to design and test the decision model.Different aspects of songs namely music,lyrics,song,voice and video are picked.For the reason,reviews of 20 songs are scraped from YouTube,pre-processed and formed a dataset.Different machine learning algorithms—Naïve Bayes(NB),Gradient Boost Tree,Logistic Regression LR,K-Nearest Neighbors(KNN)and Artificial Neural Network(ANN)are applied.ANN performed the best with 74.99%accuracy.Results are validated using K-Fold.

A Fused Machine Learning Approach for Intrusion Detection System

The rapid growth in data generation and increased use of computer network devices has amplified the infrastructures of internet.The interconnectivity of networks has brought various complexities in maintaining network availability,consistency,and discretion.Machine learning based intrusion detection systems have become essential to monitor network traffic for malicious and illicit activities.An intrusion detection system controls the flow of network traffic with the help of computer systems.Various deep learning algorithms in intrusion detection systems have played a prominent role in identifying and analyzing intrusions in network traffic.For this purpose,when the network traffic encounters known or unknown intrusions in the network,a machine-learning framework is needed to identify and/or verify network intrusion.The Intrusion detection scheme empowered with a fused machine learning technique(IDS-FMLT)is proposed to detect intrusion in a heterogeneous network that consists of different source networks and to protect the network from malicious attacks.The proposed IDS-FMLT system model obtained 95.18%validation accuracy and a 4.82%miss rate in intrusion detection.

Automated File Labeling for Heterogeneous Files Organization Using Machine Learning

File labeling techniques have a long history in analyzing the anthological trends in computational linguistics.The situation becomes worse in the case of files downloaded into systems from the Internet.Currently,most users either have to change file names manually or leave a meaningless name of the files,which increases the time to search required files and results in redundancy and duplications of user files.Currently,no significant work is done on automated file labeling during the organization of heterogeneous user files.A few attempts have been made in topic modeling.However,one major drawback of current topic modeling approaches is better results.They rely on specific language types and domain similarity of the data.In this research,machine learning approaches have been employed to analyze and extract the information from heterogeneous corpus.A different file labeling technique has also been used to get the meaningful and`cohesive topic of the files.The results show that the proposed methodology can generate relevant and context-sensitive names for heterogeneous data files and provide additional insight into automated file labeling in operating systems.