Performance Analysis of ZF and RZF in Low-Resolution ADC/DAC Massive MIMO Systems

Large number of antennas and higher bandwidth usage in massive multiple-input-multipleoutput(MIMO)systems create immense burden on receiver in terms of higher power consumption.The power consumption at the receiver radio frequency(RF)circuits can be significantly reduced by the application of analog-to-digital converter(ADC)of low resolution.In this paper we investigate bandwidth efficiency(BE)of massive MIMO with perfect channel state information(CSI)by applying low resolution ADCs with Rician fadings.We start our analysis by deriving the additive quantization noise model,which helps to understand the effects of ADC resolution on BE by keeping the power constraint at the receiver in radar.We also investigate deeply the effects of using higher bit rates and the number of BS antennas on bandwidth efficiency(BE)of the system.We emphasize that good bandwidth efficiency can be achieved by even using low resolution ADC by using regularized zero-forcing(RZF)combining algorithm.We also provide a generic analysis of energy efficiency(EE)with different options of bits by calculating the energy efficiencies(EE)using the achievable rates.We emphasize that satisfactory BE can be achieved by even using low-resolution ADC/DAC in massive MIMO.

Force Sensitive Resistors-Based Real-Time Posture Detection System Using Machine Learning Algorithms

To detect the improper sitting posture of a person sitting on a chair,a posture detection system using machine learning classification has been proposed in this work.The addressed problem correlates to the third Sustainable Development Goal(SDG),ensuring healthy lives and promoting well-being for all ages,as specified by the World Health Organization(WHO).An improper sitting position can be fatal if one sits for a long time in the wrong position,and it can be dangerous for ulcers and lower spine discomfort.This novel study includes a practical implementation of a cushion consisting of a grid of 3×3 force-sensitive resistors(FSR)embedded to read the pressure of the person sitting on it.Additionally,the Body Mass Index(BMI)has been included to increase the resilience of the system across individual physical variances and to identify the incorrect postures(backward,front,left,and right-leaning)based on the five machine learning algorithms:ensemble boosted trees,ensemble bagged trees,ensemble subspace K-Nearest Neighbors(KNN),ensemble subspace discriminant,and ensemble RUSBoosted trees.The proposed arrangement is novel as existing works have only provided simulations without practical implementation,whereas we have implemented the proposed design in Simulink.The results validate the proposed sensor placements,and the machine learning(ML)model reaches a maximum accuracy of 99.99%,which considerably outperforms the existing works.The proposed concept is valuable as it makes it easier for people in workplaces or even at individual household levels to work for long periods without suffering from severe harmful effects from poor posture.

Experimental and numerical analyses of magnesium alloy hot workability

Due to their hexagonal crystal structure,magnesium alloys have relatively low workability at room temperature.In this study,the hot workability behavior of cast-extruded AZ31B magnesium alloy is studied through hot compression testing,numerical modeling and microstructural analyses.Hot deformation tests are performed at temperatures of 250℃ to 400℃ under strain rates of 0.01 to 1.0 s^(−1).Transmission electron microscopy is used to reveal the presence of dynamic recrystallization(DRX),dynamic recovery(DRY),cracks and shear bands.To predict plastic instabilities during hot compression tests of AZ31B magnesium alloy,the authors use Johnson–Cook damage model in a 3D finite element simulation.The optimal hot workability of magnesium alloy is found at a temperature(T)of 400℃ and strain rate(ε)of 0.01 s^(−1).Stability is found at a lower strain rate,and instability is found at a higher strain rate.

Influence of different cultivars of Phoenix dactylifera L-date fruits on blood clotting and wound healing

Objective: To investigate different types of dates and medical properties of influencing blood clotting and wound healing in an animal model. Methods: Three different cultivars of dates(Ajwa, Khalas, and Fardh) were examined in-vivo, for blood clotting and wound healing using CD1 mice of both sexes. Study of toxicity to animals was performed accordingly prior to further investigations. The ethanolic extracts were given orally to animals as a constituent in their daily water. Blood samples were obtained from the mice inferior vena cava to carry out the prothrombin time(PT) assay using the manual method and confirmed using a semi-automated machine. The bleeding time(BT) assay was performed using the cutting technique. In the wound healing analysis, a small cut(5-10 mm) in the skin overlying the thigh was conducted in all mice under anesthesia. The diameter of the cut and healing status were measured on a daily basis throughout the time of the experiment using a roller. Results: Ajwa was able to elevate both PT and BT(P<0.05), significantly in a time-dependent manner followed by Khalas date(P<0.05). The results of PT and BT of Fardh date were found to be very close to those of the control group(P<0.05). Despite its activity as an anticoagulant, Khalas date showed a potential property to enhance wound healing in contrast to other dates and the control groups in this study. Conclusions: Omani Khalas date fruit has both antithrombotic as well as wound healing properties. The results open a new gate with these fruits for exploring the potential component(s) that may play an important role in antithrombotic as well as wound healing process.

Impact of petroleum and non-petroleum indices on financial development in Oman

This study analyzes the impact of petroleum and non-petroleum indices on the financial development of the Sultanate of Oman from 1978 to 2017.To this end,it uses the petroleum proxy of oil rents(%of gross domestic product,GDP)and the non-petroleum proxy of industry(including construction)value added(%of GDP);agriculture,forestry,and fishing value added(%of GDP);and services value added(%of GDP)to determine the effect on financial development,measured by the amount of domestic credit extended to the private sector by banks(%of GDP).It applies an autoregressive distributed lag(ARDL)model.The long-term equation illustrates that the agriculture and industry GDPs have a negative and significant relationship with domestic credit in Oman.However,the oil and service sector GDPs promote financial development.The short-term equation illustrates that the oil,agricultural,and service sectors have positive and significant effects on domestic credit.The conclusion is that the economy of Oman is still in the first phase of economic diversification.Accordingly,the government should use oil revenues to develop various non-oil industrial sectors.This would enhance the country’s competitiveness in the global economy and positively contribute to improving the liquidity of the banking sector for stimulating credit at the macroeconomic level.

Remote Health Monitoring Using IoT-Based Smart Wireless Body Area Network

A wireless body area network(WBAN)consists of tiny healthmonitoring sensors implanted in or placed on the human body.These sensors are used to collect and communicate human medical and physiological data and represent a subset of the Internet of Things(IoT)systems.WBANs are connected to medical servers that monitor patients’health.This type of network can protect critical patients’lives due to the ability to monitor patients’health continuously and remotely.The inter-WBAN communication provides a dynamic environment for patients allowing them to move freely.However,during patient movement,the WBAN patient nodes may become out of range of a remote base station.Hence,to handle this problem,an efficient method for inter-WBAN communication is needed.In this study,a method using a cluster-based routing technique is proposed.In the proposed method,a cluster head(CH)acts as a gateway between the cluster members and the external network,which helps to reduce the network’s overhead.In clustering,the cluster’s lifetime is a vital parameter for network efficiency.Thus,to optimize the CH’s selection process,three evolutionary algorithms are employed,namely,the ant colony optimization(ACO),multi-objective particle swarm optimization(MOPSO),and the comprehensive learning particle swarm optimization(CLPSO).The performance of the proposed method is verified by extensive experiments by varying values of different parameters,including the transmission range,node number,node mobility,and grid size.A comprehensive comparative analysis of the three algorithms is conducted by extensive experiments.The results show that,compared with the other methods,the proposed ACO-based method can form clusters more efficiently and increase network lifetime,thus achieving remarkable network and energy efficiency.The proposed ACO-based technique can also be used in other types of ad-hoc networks as well.

Dietary crocin reverses melanoma metastasis

Crocus sativus and its bioactive constituent crocin are well known for anti-tumor potential in different models.However, the efficacy of crocin on in-vivo melanoma metastasis is not yet reported. In this study, melanoma metastatic model was developed by tail vein injection of B16 F-10 cells in to C57 BL/6 mice. Metastatic mice treated with two different doses of crocin（250 and 500 μg/kg of bodyweight） for 10 days and parameters such as lung metastasis inhibition, mean survival time, lung hydroxyproline, uronic acid and hexosamine levels were analyzed after 21 days of treatment. Then blood was collected and serum gamma glutamyl transpeptidase（γ-GGT）, sialic acid,tumor necrosis factor alpha（TNF-a）, interleukin 10（IL-10）, IL-6, IL-2, and TIMP-1 levels were measured. Further, a lung histological examination was done in crocin treated metastatic mice. Subsequently hallmark metastatic parameters such as matrix metalloproteinases（MMPs）, extracellular regulated kinase 2（ERK2）, vascular endothelial growth factor（VEGF）, and K-ras gene expression were investigated in the lungs of crocin treated metastatic mice.Further, in-vitro adhesion, invasion and migration of B16 F-10 cells were examined after 24 hours of crocin（5 and 10μg/mL） treatment. Administration of crocin to tumor bearing C57 BL/6 mice reduced the lung metastasis by 85%.Elevated levels of hydroxyproline, uronic acid, hexosamine, serum sialic acid and y-GGT in metastatic control were found to be significantly reduced in crocin treated mice. Crocin also inhibited expression of MMP-2, MMP-9, ERK-2,K-ras, and VEGF. Crocin reduced the ability of B16 F-10 cells invasion（P〈0.05）, migration（P〈0.05） and adhesion by upregulating E-cadherin expression. In conclusion, crocin elicited marked anti-metastatic potential by regulating the metastasis induced biomarkers.

A Novel Framework for Multi-Classification of Guava Disease

Guava is one of the most important fruits in Pakistan,and is gradually boosting the economy of Pakistan.Guava production can be interrupted due to different diseases,such as anthracnose,algal spot,fruit fly,styler end rot and canker.These diseases are usually detected and identified by visual observation,thus automatic detection is required to assist formers.In this research,a new technique was created to detect guava plant diseases using image processing techniques and computer vision.An automated system is developed to support farmers to identify major diseases in guava.We collected healthy and unhealthy images of different guava diseases from the field.Then image labeling was done with the help of an expert to differentiate between healthy and unhealthy fruit.The local binary pattern(LBP)was used for the extraction of features,and principal component analysis(PCA)was used for dimensionality reduction.Disease classification was carried out using multiple classifiers,including cubic support vector machine,Fine K-nearest neighbor(F-KNN),Bagged Tree and RUSBoosted Tree algorithms and achieved 100%accuracy for the diagnosis of fruit flies disease using Bagged Tree.However,the findings indicated that cubic support vector machines(C-SVM)was the best classifier for all guava disease mentioned in the dataset.

Sizing of STATCOM to Enhance Voltage Stability of Power Systems for Normal and Contingency Cases

The electric power infrastructure that has served huge loads for so long is rapidly running up against many limitations. Out of many challenges it is to operate the power system in secure manner so that the operation constraints are fulfilled under both normal and contingent conditions. Smart grid technology offers valuable techniques that can be deployed within the very near future or which are already deployed nowadays. Flexible AC Transmission Systems (FACTS) devices have been introduced to solve various power system problems. In literature, most of the methods proposed for sizing the FACTS devices only consider the normal operating conditions of power systems. Consequently, some transmission lines are heavily loaded in contingency case and the system voltage stability becomes a power transfer-limiting factor. This paper presents a technique for determining the proper rating/size of FACTS devices, namely the Static Synchronous Compensator (STATCOM), while considering contingency cases. The paper also verifies that the weakest bus determined by eigenvalue and eigenvectors method is the best location for STATCOM. The rating of STATCOM is specified according to the required reactive power needed to improve voltage stability under normal and contingency cases. Two case system studies are investigated: a simple 5-bus system and the IEEE 14-bus system. The obtained results verify that the rating of STATCOM can be determined according to the worst contingency case, and through proper control it can still be effective for normal and other contingency cases.

Numerical Analysis of the Behavior of A New Aeronautical Alloy (Ti555-03) Under the Effect of A High-Speed Water Jet

In this paper, we present a numerical simulation of a water jet impacting a new aeronautical material Ti555-03 plate.The Computational Fluid Dynamics(CFD) behavior of the jet is investigated using a FV(Finite Volume) method.The Fluid–Structure Interaction(FSI) is studied using a coupled SPH(Smoothed Particle Hydrodynamics)-FE(Finite Element) method. The jets hit the metal sheet with an initial velocity 500 m/s. Two configurations which differ from each other by the position(angle of inclination) of the plate relatively to the axis of revolution of the jet inlet are investigated in this study. The objective of this study is to predict the impact of the fluid produced at high pressure and high speed especially at the first moment of impact. Numerical simulations are carried out under ABAQUS. We have shown in this study that the inclination of the titanium alloy plate by 45° stimulates the phenomenon of recirculation of water. This affects the velocity profile, turbulence and boundary layers in the impact zone. The stagnation zone and the phenomenon of water recirculation are strongly influenced by the slope of the plate which gives a pressure gradient and displacement very important between the two configurations. Fluctuations of physical variables(displacement and pressure) prove the need for a noise and vibratory study. These predictions will subsequently be used for the modeling of the problem of an orthogonal cut in a high-speed machining process assisted by high-pressure water jet.

Construction and Optimization of TRNG Based Substitution Boxes for Block Encryption Algorithms

Internet of Things is an ecosystem of interconnected devices that are accessible through the internet.The recent research focuses on adding more smartness and intelligence to these edge devices.This makes them susceptible to various kinds of security threats.These edge devices rely on cryptographic techniques to encrypt the pre-processed data collected from the sensors deployed in the field.In this regard,block cipher has been one of the most reliable options through which data security is accomplished.The strength of block encryption algorithms against different attacks is dependent on its nonlinear primitive which is called Substitution Boxes.For the design of S-boxes mainly algebraic and chaos-based techniques are used but researchers also found various weaknesses in these techniques.On the other side,literature endorse the true random numbers for information security due to the reason that,true random numbers are purely non-deterministic.In this paper firstly a natural dynamical phenomenon is utilized for the generation of true random numbers based S-boxes.Secondly,a systematic literature review was conducted to know which metaheuristic optimization technique is highly adopted in the current decade for the optimization of S-boxes.Based on the outcome of Systematic Literature Review(SLR),genetic algorithm is chosen for the optimization of s-boxes.The results of our method validate that the proposed dynamic S-boxes are effective for the block ciphers.Moreover,our results showed that the proposed substitution boxes achieve better cryptographic strength as compared with state-of-the-art techniques.

Acquisition of pronunciation of consonant clusters by Arabic speakers of English as a second language

The study is based on an observation of the pronunciation of a group of undergraduate students of English as a Second Language （ESL） whose mother tongue is Arabic and who have no formal training in the spoken variety of English other than that received in the classroom. The study of acquisition of pronunciation of consonant clusters at morphological, particularly at the morphophonological levels indicates that the learners are sensitive to the syllabic structure viz., cccv type and cccvcc type, at the word-initial, medial and final positions. Samples of words with different consonant clusters were tested with a homogeneous group of students. Words of identical morphological categories were used as the data to test the students＇ level of perception. These were analyzed using Speech Analyzer Version 2.5. The data includes consonant clusters like plosive-fricative, plosive-plosive, fricative-fricative and plosive-fricative-trill/liquid combinations. The results varied according to the perceptual and articulatory abilities of the learners. It was observed that the plosive perception and acquisition of three-consonant clusters of plosive-plosive word initially, plosive-plosive combinations word finally and plosive-fricative type, posed more difficulty for the learners. The tendency to drop one of the consonants of the cluster was more pronounced with syllables ending in plural morphemes and those ending in -mp, -pt, -kt, -nt, -bt, etc. Difficulty was also noticed with the initial plosive＋/r/, plosive＋/1/combinations, especially in word initial positions. Across the syllable boundaries, these clusters are almost inaudible with some speakers. The difficulty in the articulation of these consonant clusters can be accounted for the mother tongue influence, as in the case of many other features. The results of the analysis have a pedagogical implication in the use of such words with consonant clusters, to teach reading skills to the students of undergraduate level in the present setting and promote self-learning through the use of speech tools.

Shakespeare＇s Language Strategies in Hamlet

This study investigates the language strategies used by Shakespeare in The Tragedy of Hamlet, Prince of Denmark （1603）. Emphasis is given to the type of language or register Shakespeare provides his characters with in order to give them genuine or assumed identities. The linguistic register of the three major characters of Claudius, the Ghost, and Hamlet is explored in light of the Elizabethan cultural context. This concern with these three characters stems from the basic assumption of the paper that the play is a struggle between Claudius and the Ghost over Hamlet. Claudius speaks the language of a monarch which is informed by the code of society; the Ghost, who used to speak such language of sovereignty while alive, speaks a language of the dead informed by a newly acquired experience not familiar to human beings. On the other hand, Hamlet＇s use of language is the most peculiar in the play. His register keeps changing according to his tragic growth and his readiness for action. The study indicates that the language functions Shakespeare utilizes in Hamlet are numerous. Language is used creatively for a variety of purposes in addition to communication. The playwright employs language as a shield for self-defense, a tool for defining and hiding identity and misleading and manipulating others, a means of search for reality, and a tool for punishment, among other functions. The study findings invite further research into Shakespeare＇s use of language in his plays. No detailed in-depth studies of Shakespearean language and its implications exist.

Lightweight Key Management Scheme Using Fuzzy Extractor for Wireless Mobile Sensor Network

The mature design of wireless mobile sensor network makes it to be used in vast verities of applications including from home used to the security surveillance.All such types of applications based on wireless mobile sensor network are generally using real time data,most of them are interested in real time communication directly from cluster head of cluster instead of a base station in cluster network.This would be possible if an external user allows to directly access real time data from the cluster head in cluster wireless mobile sensor network instead of accessing data from base station.But this leads to a serious security breach and degrades the performance of any security protocol available in this domain.Most existing schemes for authentication and cluster key management for external users,exchange a number of messages between cluster head and base station to allow external to access real time data from the base station instead of cluster head.This increase communication cost and delay in such real time access information.To handle this critical issue in cluster wireless mobile sensor network,we propose a lightweight authentication and key management scheme using a fuzzy extractor.In this scheme,any external user can access data directly from the cluster head of any cluster without the involvement of the base station.The proposed scheme only uses the one-way hash functions and bitwise XOR operations,apart from the fuzzy extractor method for the user biometric verification at the login phase.The presented scheme supports scalability for an increasing number of nodes using polynomials.The proposed scheme increases the life-time of the network by decreasing the key pool size.

Handling Class Imbalance in Online Transaction Fraud Detection

With the rise of internet facilities,a greater number of people have started doing online transactions at an exponential rate in recent years as the online transaction system has eliminated the need of going to the bank physically for every transaction.However,the fraud cases have also increased causing the loss of money to the consumers.Hence,an effective fraud detection system is the need of the hour which can detect fraudulent transactions automatically in real-time.Generally,the genuine transactions are large in number than the fraudulent transactions which leads to the class imbalance problem.In this research work,an online transaction fraud detection system using deep learning has been proposed which can handle class imbalance problem by applying algorithm-level methods which modify the learning of the model to focus more on the minority class i.e.,fraud transactions.A novel loss function named Weighted Hard-Reduced Focal Loss(WH-RFL)has been proposed which has achieved maximum fraud detection rate i.e.,True PositiveRate(TPR)at the cost of misclassification of few genuine transactions as high TPR is preferred over a high True Negative Rate(TNR)in fraud detection system and same has been demonstrated using three publicly available imbalanced transactional datasets.Also,Thresholding has been applied to optimize the decision threshold using cross-validation to detect maximum number of frauds and it has been demonstrated by the experimental results that the selection of the right thresholding method with deep learning yields better results.

Power Domain Multiplexing Waveform for 5G Wireless Networks

Power domain non-orthogonal multiple access combined with a universal filtered multi-carrier(NOMA-UFMC)has the potential to cope with fifth generation(5G)unprecedented challenges.NOMA employs powerdomainmultiplexing to support several users,whereasUFMC is robust to timing and frequency misalignments.Unfortunately,NOMA-UFMC waveform has a high peak-to-average power(PAPR)issue that creates a negative affect due to multicarrier modulations,rendering it is inefficient for the impending 5G mobile and wireless networks.Therefore,this article seeks to presents a discrete Hartley transform(DHT)pre-coding-based NOMA enabled universal filter multicarrier(UFMC)(DHT-NOMA-UFMC)waveform design for lowering the high PAPR.Additionally,DHT precoding also takes frequency advantage variations in the multipath wireless channel to get significant bit error rate(BER)gain.In the recommended arrangement,the throughput of the systemis improved by multiplexing the users in the power domain and permitting the users with good and bad channel conditions to concurrently access the apportioned resources.The simulation outcomes divulge that the projected algorithm accomplished a gain of 5.8 dB as related to the conventional framework.Hence,it is established that the proposed DHT-NOMA-UFMC outperforms the existing NOMA-UFMC waveform.The key benefit of the proposed method over the other waveforms proposed for 5G is content gain due to the power domain multiplexing at the transmitting side.Thus,a huge count of mobile devices could be supported under specific restrictions.DHTNOMA-UFMC can be regarded as the most effective applications for 5G Mobile andWireless Networks.However,the main drawback of the proposed method is that the Fourier peak and phase signal is not easily estimated.

Effect of erosion on corrosion of API X120 steel in relation to erodent particle size

The nature of the solid erodent particles present in corrosive petroleum fluid can cause transporting pipeline to experience severe erosion and corrosion damages. The effect of erosion on corrosion behavior of API X120 steel was investigated using aluminum oxide and silicon carbide particles with different sizes as erodent and 3.5wt.% NaCl aqueous solution saturated with carbon dioxide as a corrosive medium. The effect of the erodent particle size on the corrosion behavior of the steel material at different particle speeds and impact angles was investigated using weight loss, potentiodynamic polarization and surface analysis techniques. The erosion results confirmed that the material damage increased with increasing particle speed. It was observed that in carbon dioxide-saturated saline solution, deposition of protective iron carbonate film occurred on the steel surface. It was found that the corrosion film can provide better protection at lower particle speed than at higher speed. The ratio of total erosion-corrosion (S)/effect of erosion on corrosion (T) analysis confirmed that at higher S/T ratio, the particle speed and material removal rate are low and vice versa at lower S/T ratio. Lower S/T values for the combined erosion and corrosion tests performed with erodent silicon carbide particle compared to erodent aluminum oxide particle showed that erosion enhancement of corrosion is more evident in the test performed using aluminum oxide particle than using silicon carbide particle. The result also suggests that when subjected to larger size erodent particle, the damage to pipeline due to effect of erosion on corrosion process can be more significant compared to smaller size erodent particle.

Plant extract-loaded bacterial cellulose composite membrane for potential biomedical applications

Bacterial cellulose(BC)has been extensively explored as biomaterial for various biomedical applications owing to its non-toxic nature and unique structural morphology and impressive physicochemical and mechanical properties.However,its high production cost and lack of antimicrobial activity have restricted its large-scale production and therapeutic applications.Therefore,the current study is aimed to devise a strategy for low-cost BC production and develop its composite with bioactive materials to bless it with antimicrobial activity.Herein,5 mm thick reticulated fibrous and highly porous BC was produced by utilizing the wasted rotten tomatoes as the production medium.The produced bacterial cellulose waste(BCW)(i.e.,produced from wastes)was ex-situ modified with bioactive plant extract(PE)obtained from Euclea schimperi,and the bactericidal activity of the developed BCW/PE was evaluated against Gram-positive Staphylococcus aureus and Gram-negative Escherichia coli through disc diffusion and colony forming unit(CFU)count methods.The BCW/PE composite showed high bactericidal activities against S.aureus and produced clear inhibition zone whereas negligible activity was observed against E.coli,indicating its bactericidal activity mainly against the Gram-positive bacterium.Overall,this study illustrates that there is a huge potential for developing valuable biomaterials from food wastes and utilizing their liquid holding capabilities for value-added applications in medical and pharmaceutical fields.

Synthesis and applications of fungal mycelium-based advanced functional materials

Over the last couple of decades,the introduction of living systems to material science for the synthesis of functional materials from biological resources is receiving immense consideration.This is also in accordance with the need for green and sustainable development of new materi-als.For example,the growing concerns of the degradation of synthetic plastics are shifting the direction of materials-related research to the use of polymeric materials acquired from renewable resources.For example,the fungal mycelium-based materials are produced by growing the vegetative part of mushroom-forming fungi on different organic substrates.Such fungi are known for their ability to degrade agricultural wastes such as straws and sawdust.The mycelium-based composites having tailored structural,physical,chemical,mechanical,and biological properties are relying on the strain,feeding substrate,and the manufacturing process.The mycelium cell wall mainly contains the chitin,glucans,proteins,and lipids,whose concentrations depend upon the feeding substrate that ultimately defines the final properties of the synthesized materials.The mycelium-based functional materials with tunable properties are synthesized by selecting the desired components and the synthesis method.The pure and composites of stiff,elastic,porous,less dense,fast-growing,and low-cost mycelium-derived materials with efficient antimicrobial,antioxidant,and skin whitening properties pave their way in various applications such as construction,packaging,medicine,and cosmetics.This review describes the synthesis and structural organization of mycelium-based materials.It further discusses the effect of different factors on the material properties.Finally,it summarizes different applications of mycelium-based materials in medicine,cosmetics,packaging,and construction fields.

Higher-Level Hardware Synthesis of the KASUMI Algorithm

Programmable Logic Devices （PLDs） continue to grow in size and currently contain several millions of gates. At the same time, research effort is going into higher-level hardware synthesis methodologies for reconfigurable computing that can exploit PLD technology. In this paper, we explore the effectiveness and extend one such formal methodology in the design of massively parallel algorithms. We take a step-wise refinement approach to the development of correct reconfigurable hardware circuits from formal specifications. A functional programming notation is used for specifying algorithms and for reasoning about them. The specifications are realised through the use of a combination of function decomposition strategies, data refinement techniques, and off-the-shelf refinements based upon higher-order functions. The off-the-shelf refinements are inspired by the operators of Communicating Sequential Processes （CSP） and map easily to programs in Handel-C （a hardware description language）. The Handel-C descriptions are directly compiled into reconfigurable hardware. The practical realisation of this methodology is evidenced by a case studying the third generation mobile communication security algorithms. The investigated algorithm is the KASUMI block cipher. In this paper, we obtain several hardware implementations with different performance characteristics by applying different refinements to the algorithm. The developed designs are compiled and tested under Celoxica＇s RC-1000 reconfigurable computer with its 2 million gates Virtex-E FPGA. Performance analysis and evaluation of these implementations are included.