Characteristics Of Different Applications Research Articles

Nanozymes in Biomedical Applications: Innovations Originated From Metal-Organic Frameworks.

Nanozymes exhibit significant potential in medical theranostics, environmental protection, energy development, and biopharmaceuticals due to their exceptional catalytic performance. Compared with natural enzymes, nanozymes have the advantages of simple preparation and purification, convenient production and low cost. Therefore, it is very important to prepare nanozymes quickly and efficiently, which not only helps to expand their application scope, but also can further exert their great potential in various fields. Metal-organic frameworks (MOF) materials serve as versatile substrates for constructing nanozymes, offering unique advantages like adjustable structure, high specific surface area, and porous channels. MOF coordination nodes constructed from metal ions or metal clusters have unique properties that can be leveraged to tailor nanozyme characteristics for different applications. This review describes and analyzes recent methods for constructing nanozymes using MOF materials, and explores their application prospects in biomedicine. By expounding the preparation techniques and biomedical applications of nanozymes, this review aims to inspire researchers to develop innovative nanozyme materials and explore new application directions.

Manufacturing Low-Fat Processed Cheese Using Chickpea Proteins as a Fat Substitute and Studying Its Physicochemical, Rheological, and Sensory Quality Characteristics

Background: Manufacturing processed cheese has many advantages compared to natural cheese because the cost of refrigeration is lower during storage and transportation, and maintaining improved quality with minimal changes in the characteristics of the cheese during storage. It is possible to produce cheese with different intensity in flavor, functionality, and characteristics for different applications. Methods: This study was carried out in the laboratories of the College of Food Sciences, department of dairy science and technology at Al-Qasim green university, where full-fat cheddar cheese was mixed with full-fat soft cheese and used in the manufacture of cooked cheese treated with positive control + C, as well as mixing full-fat cheddar cheese with low-fat soft cheese to manufacture low-fat processed cheese, the negative control treatment was treated C-. Full-fat cheddar cheese was mixed with soft, low-fat cheese, with the addition of chickpea proteins as a fat replacers, with addition rates of 1.5, 3, and 4.5%, represented by treatments T3, T2, and T1, respectively. Results: The chemical tests included estimating the percentage of moisture, protein, fat, ash, carbohydrates, and total acidity, in addition to estimating the pH, while the rheological tests included hardness, adhesion, and springiness. A sensory evaluation of processed cheese parameters was also conducted. The results showed that the replacement treatments were characterized by a lower moisture content and protein percentage than the negative control treatment and close to the positive control treatment. The percentages of carbohydrates, ash, and acidity also increased in the replacement treatments, but the percentage of fats and pH decreased.

MXene‐Based Nanomaterials for Biomedical Applications: Healthier Substitute Materials for the Future

MXene‐based nanomaterial is a revolution 2D material achieving outstanding scientific attention owing to its universal characteristics for different applications (such as electronic appliances, power production, sensors, drug transfer, and biomedical). Although, the cytotoxic consequences of MXene have a considerable circumstance. Thus, rigorous investigation of the biocompatibility of MXene is a crucial prerequisite, formerly the preface to the human biological approach. Literature reveals functional outcomes wherever MXenes are used in vitro and in vivo cancer representatives. It affects drug transfer methods, sensoring electrodes, and assisting mechanisms for photothermal treatment and hyperthermy techniques. In this review, the synthesis process (such as top‐down and bottom‐up approaches) and properties (such as mechanical, electrical, optical, oxidative/thermal stability, and magnetic) of MXene‐based nanomaterials (NMs) are discussed. In addition, the different applications (such as tissue engineering, cancer theranostic, and other biomedical [such as drug delivery biosensors and surface‐enhanced Raman spectroscopy substrates for biomedical applications], antiviral, and immunomodulatory properties against SARS‐CoV‐2) of MXene‐based NMs are discussed in detail. Finally, the conclusion, existing challenges, and future outlooks are highlighted for more scope in this field.

Teaching redundant residue number system for electronics and computer students

This paper describes a study for teaching number system in a computer arithmetic course and addresses the existing gap in the current course by focusing on the characteristics of applications. A redundant residue number system (RRNS) is an efficient and innovative number system that inherits the interesting properties of both residue number system (RNS) and redundant number systems. It breaks the operands into residues by considering a moduli-set and then signifies the residues by a redundant representation. So, by limiting the carry propagation chain inside and outside the moduli, RRNS proposes more efficient arithmetic units which could be employed in digital signal processing (DSP) applications. Despite the applicability of RRNS, there is not well-organized teaching on RRNS covering the recent achievements. Besides, there is an important question for students and researchers what is the most appropriate number representation for each application category? In this paper, we present a step-by-step education process for RRNS that includes basic concepts of RNS and the redundant number system. Then we address characteristics of different applications that RRNS is suitable to be employed for them. So, the method gives a well-organized proceeding to computer arithmetic designers and students.

Innovative Industrial Use of Bamboo as Key “Green” Material

This study investigates the use of bamboo in different industrial sectors, including construction and energy, to highlight its mechanical properties, resources, and innovative use through information gathered from Ethiopia, Guinea, and Georgia (Caucasus) as study cases. Research shows that bamboo is a common plant and an easily accessible material possessing remarkable characteristics for different applications in different countries. The main goal of this study is to highlight the properties of bamboo that make it an interesting material with applications in several economic branches as a green material positively influencing the environment. The results of this study show a utilitarian use of bamboo in industries where production is based on bamboo or bamboo-related materials and wide possibilities for using bamboo in innovative and creative ways. Bamboo’s mechanical and physicochemical properties are discussed as well as its potential as a raw material for use in composites or for the production and processing of semi-finished products and parts of end devices, all with a view to its positive environmental impact.

Recent Progress in Biopolymer-Based Hydrogel Materials for Biomedical Applications.

Hydrogels from biopolymers are readily synthesized, can possess various characteristics for different applications, and have been widely used in biomedicine to help with patient treatments and outcomes. Polysaccharides, polypeptides, and nucleic acids can be produced into hydrogels, each for unique purposes depending on their qualities. Examples of polypeptide hydrogels include collagen, gelatin, and elastin, and polysaccharide hydrogels include alginate, cellulose, and glycosaminoglycan. Many different theories have been formulated to research hydrogels, which include Flory-Rehner theory, Rubber Elasticity Theory, and the calculation of porosity and pore size. All these theories take into consideration enthalpy, entropy, and other thermodynamic variables so that the structure and pore sizes of hydrogels can be formulated. Hydrogels can be fabricated in a straightforward process using a homogeneous mixture of different chemicals, depending on the intended purpose of the gel. Different types of hydrogels exist which include pH-sensitive gels, thermogels, electro-sensitive gels, and light-sensitive gels and each has its unique biomedical applications including structural capabilities, regenerative repair, or drug delivery. Major biopolymer-based hydrogels used for cell delivery include encapsulated skeletal muscle cells, osteochondral muscle cells, and stem cells being delivered to desired locations for tissue regeneration. Some examples of hydrogels used for drug and biomolecule delivery include insulin encapsulated hydrogels and hydrogels that encompass cancer drugs for desired controlled release. This review summarizes these newly developed biopolymer-based hydrogel materials that have been mainly made since 2015 and have shown to work and present more avenues for advanced medical applications.

Study on Capacity Estimation Methods of Second-Life Application Batteries

For the capacity estimation problem of cells in series-retired battery modules, this paper proposed three different methods from the perspective of data-driven, battery curve matching and recession characteristics for different applications. Firstly, based on the premise that the battery history data are available, the features of the IC curve are selected as input for the linear regression models. To avoid multicollinearity among features, we apply a filter-based feature selection method to eliminate redundant features. The results show that the average errors with Multiple Linear Regression are within 1.5%. Secondly, for the situation with a lack of historical operating data, the battery-curve-matching-based method is proposed based on the Dynamic Time Warping algorithm. This method could achieve the curve matching between the reference cell and target cell, and then the curve contraction coefficients can be obtained. The result shows that the method’s average error is 2.34%. Thirdly, whereas the tougher situation is that only part of the battery curve is available, we present a substitute method based on the battery degradation mechanism. This method can estimate most of the battery plant capacity through the partial battery curve. The result shows that the method’s average error is within 2%. Lastly, we contrast the applicability and limitations of every method based on the retired battery test data after deep cycling aging.

Intelligent Rehabilitation Assistance Tools for Distal Radius Fracture: A Systematic Review Based on Literatures and Mobile Application Stores.

Objective To systematically analyze the existing intelligent rehabilitation mobile applications (APPs) related to distal radius fracture (DRF) and evaluate their features and characteristics, so as to help doctors and patients to make evidence-based choice for appropriate intelligent-assisted rehabilitation. Methods Literatures which in regard to the intelligent rehabilitation tools of DRF were systematic retrieved from the PubMed, the Cochrane library, Wan Fang, and VIP Data. The effective APPs were systematically screened out through the APP markets of iOS and Android mobile platform, and the functional characteristics of different APPs were evaluated and analyzed. Results A total of 8 literatures and 31 APPs were included, which were divided into four categories: intelligent intervention, angle measurement, intelligent monitoring, and auxiliary rehabilitation games. These APPs provide support for the patients' home rehabilitation guidance and training and make up for the high cost and space limitations of traditional rehabilitation methods. The intelligent intervention category has the largest download ratio in the APP market. Angle measurement tools help DRF patients to measure the joint angle autonomously to judge the degree of rehabilitation, which is the most concentrated type of literature research. Some of the APPs and tools have obtained good clinical verification. However, due to the restrictions of cost, geographic authority, and applicable population, a large number of APPs still lack effective evidence to support popularization. Conclusion Patients with DRF could draw support from different kinds of APPs in order to fulfill personal need and promote self-management. Intelligent rehabilitation APPs play a positive role in the rehabilitation of patients, but the acceptance of the utilization for intelligent rehabilitation APPs is relatively low, which might need follow-up research to address the conundrum.

Effect of Plasma-Activated Zinc Oxide Surface on Liquid Stability

The ZnO is an essential material in material science, agriculture, food industry, cosmetics, medicine etc. Most applications exploit ZnO physicochemical properties such as optical, electrical, mechanical and thermal. In material science, ZnO is commonly used in gas sensors, light-emitting diodes, field-effect transistors, UV lasers, photodetectors, solar cells, photo and heterogeneous catalysis. The ZnO characteristics for different applications can be controlled by size and morphology of particles with numerous techniques.In this work, we study the effect of UV light and plasma treatment on ZnO surface morphology, crystallography and effect on its other intrinsic properties. For study, the UV-A/C light is used and compared to atmospheric pressure plasma generated in Ar or He as well as low-pressure RF – ICP plasma generated in oxygen gas. The research is focused on how UV or other plasma related changes influence the material intrinsic properties and change stability of liquid organic compounds in low ppm concentrations. The resulting interaction between stable liquid and modified material namely result in creation of other unstable molecules and compounds as well as reactive species. This approach enables improved design of catalytic performance of nanomaterials by designing their surface properties by plasma, beyond mere enhancement of surface area. The targeted liquids for modifications are thiophens in organic solvents, where we need to look at interactions of this liquids with material. To unravel these interactions, various analyses are used including UV-Vis, HPLC, and NMR. Further for surface characterisation of materials, the analyses including XPS, FTIR, UV-Vis, BET, SEM and TEM are used. The obtained results give then systematic explanation, how UV or plasma changes of material intrinsic properties translate into targeted liquid interactions and modifications.

Intentional Forgetting in Socio-Digital Work Systems

Future work environments offer numerous technical applications to manage increasing amounts of information for organizations, teams, and individuals. Psychological concepts of intentional forgetting (IF) can be applied to improve the performance of work systems or to extend cognitive capacities of humans in technical systems. Different IF mechanisms have been suggested for assisting technology-aided IF, such as: (1) filtering of irrelevant or distressful information (e.g., by suppressing, deleting, or selecting), (2) delegating tasks from human to digital agents, changing roles, and reorganizing socio-digital work systems, or (3) systematic (re-)placement of retrieval cues or triggers to generate or suppress behavior. Due to these different underlying IF mechanisms, the implementation of IF at individual, team, and organizational level will differ substantially between work areas or systems. In order to gain a better understanding of how socio-digital applications of IF impact human behavior and reactions, it is necessary to (a) differentiate between relevant characteristics of socio-digital IF systems and (b) gain an understanding of how these characteristics impact users’ attitudes and performance. Thus, the present paper aims to classify and compare these characteristics of different applications of IF and introduces variables and methods to study psychological effects on users’ behavior, experience, and affective reactions.

Memory Request Priority Based Warp Scheduling for GPUs

High performance of GPGPU comes from its super massive multithreading, which makes it more and more widely used especially in the field of throughputoriented. Data locality is one of the important factors affecting the performance of GPGPU. Although GPGPU can exploit intra/inter-warp locality by itself in part, there is still large improvement space for that. In our work, we analyze the characteristics of different applications and propose memory request based warp scheduling to better exploit inter-warp spatial locality. This method can make some warps with good inter-warp locality run faster, which is beneficial to improve the whole performance. Our experimental results show that our proposed method can achieve 24.7% and 11.9% average performance improvement over LRR and MRPB respectively.

New CSMA/CA prioritisation based on fuzzy control mechanism

Wireless sensor networks (WSNs) consist of several small nodes that use different types of sensors to gather different types of data and to communicate with each other through several protocols. The IEEE 802.15.4 presents a soft medium access control (MAC) protocol that provides good efficiency for data transmission by adapting its parameters according to characteristics of different applications. The main idea of this paper is to apply a dynamic allocation of priority level for nodes that compete for the access to the medium through tuning parameters in the carrier sense multiple access/collision avoidance (CSMA/CA) algorithm. A priority scheduling is achieved using a fuzzy logic mechanism exploiting queue level and traffic rate of each node in order to ensure adequate dynamic allocation. This paper demonstrates various advantages of priority-based CSMA/CA for quality of service (QoS). Results show significant improvements achieved by our approach among the IEEE 802.15.4 MAC standards.

New CSMA/CA prioritisation based on fuzzy control mechanism

Wireless sensor networks (WSNs) consist of several small nodes that use different types of sensors to gather different types of data and to communicate with each other through several protocols. The IEEE 802.15.4 presents a soft medium access control (MAC) protocol that provides good efficiency for data transmission by adapting its parameters according to characteristics of different applications. The main idea of this paper is to apply a dynamic allocation of priority level for nodes that compete for the access to the medium through tuning parameters in the carrier sense multiple access/collision avoidance (CSMA/CA) algorithm. A priority scheduling is achieved using a fuzzy logic mechanism exploiting queue level and traffic rate of each node in order to ensure adequate dynamic allocation. This paper demonstrates various advantages of priority-based CSMA/CA for quality of service (QoS). Results show significant improvements achieved by our approach among the IEEE 802.15.4 MAC standards.

Precipitation and Growth Mechanism of Diverse Sr5(PO4)3F Particles

Strontium fluorapatite particles with tunable morphologies and geometries were successfully synthesized via a precipitation system by adjusting the pH value and temperature. Several analysis techniques were used to investigate and characterize the particles. The surface energy was calculated using first‐principle calculations based on density functional theory. Capsule‐like nanosized primary grains with axial growth directions parallel to the c‐axis were synthesized at higher pH values, resulting from the difference in surface energy for the different planes of the Sr5(PO4)3F lattice. Bundle‐like clusters were obtained at a pH value of ~7, which was attributed to a combination of the difference in surface energy and the phenomenon of heterogeneous nucleation occurring at low degrees of supersaturation. The study determined the approaches necessary to manufacture Sr5(PO4)3F powders with specific characteristics for different applications.

DASH

Modern SoCs integrate multiple CPU cores and hardware accelerators (HWAs) that share the same main memory system, causing interference among memory requests from different agents. The result of this interference, if it is not controlled well, is missed deadlines for HWAs and low CPU performance. Few previous works have tackled this problem. State-of-the-art mechanisms designed for CPU-GPU systems strive to meet a target frame rate for GPUs by prioritizing the GPU close to the time when it has to complete a frame. We observe two major problems when such an approach is adapted to a heterogeneous CPU-HWA system. First, HWAs miss deadlines because they are prioritized only when close to their deadlines. Second, such an approach does not consider the diverse memory access characteristics of different applications running on CPUs and HWAs, leading to low performance for latency-sensitive CPU applications and deadline misses for some HWAs, including GPUs. In this article, we propose a Deadline-Aware memory Scheduler for Heterogeneous systems (DASH), which overcomes these problems using three key ideas, with the goal of meeting HWAs’ deadlines while providing high CPU performance. First, DASH prioritizes an HWA when it is not on track to meet its deadline any time during a deadline period, instead of prioritizing it only when close to a deadline. Second, DASH prioritizes HWAs over memory-intensive CPU applications based on the observation that memory-intensive applications’ performance is not sensitive to memory latency. Third, DASH treats short-deadline HWAs differently as they are more likely to miss their deadlines and schedules their requests based on worst-case memory access time estimates. Extensive evaluations across a wide variety of different workloads and systems show that DASH achieves significantly better CPU performance than the best previous scheduler while always meeting the deadlines for all HWAs, including GPUs, thereby largely improving frame rates.

Architectural support for task scheduling: hardware scheduling for dataflow on NUMA systems

To harness the compute resource of many-core system with tens to hundreds of cores, applications have to expose parallelism to the hardware. Researchers are aggressively looking for program execution models that make it easier to expose parallelism and use the available resources. One common approach is to decompose a program into parallel `tasks' and allow an underlying system layer to schedule these tasks to different threads. Software-only schedulers can implement various scheduling policies and algorithms that match the characteristics of different applications and programming models. Unfortunately with large-scale multi-core systems, software schedulers suffer significant overheads as they synchronize and communicate task information over deep cache hierarchies. To reduce these overheads, hardware-only schedulers like Carbon have been proposed to enable task queuing and scheduling to be done in hardware. This paper presents a hardware scheduling approach where the structure provided to programs by task-based programming models can be incorporated into the scheduler, making it aware of a task's data requirements. This prior knowledge of a task's data requirements allows for better task placement by the scheduler which result in a reduction in overall cache misses and memory traffic, improving the program's performance and power utilization. Simulations of this technique for a range of synthetic benchmarks and components of real applications have shown a reduction in the number of cache misses by up to 72 and 95 % for the L1 and L2 caches, respectively, and up to 30 % improvement in overall execution time against FIFO scheduling. This results not only in faster execution and in less data transfer with reductions of up to 50 %, allowing for less load on the interconnect, but also in lower power consumption.

A Mac Protocol Implementation for Wireless Sensor Network

IEEE 802.15.4 is an important standard for Low Rate Wireless Personal Area Network (LRWPAN). The IEEE 802.15.4 presents a flexible MAC protocol that provides good efficiency for data transmission by adapting its parameters according to characteristics of different applications. In this research work, some restrictions of this standard are explained and an improvement of traffic efficiency by optimizing MAC layer is proposed. Implementation details for several blocks of communication system are carefully modeled. The protocol implementation is done using VHDL language. The analysis gives a full understanding of the behavior of the MAC protocol with regard to backoff delay, data loss probability, congestion probability, slot effectiveness, and traffic distribution for terminals. Two ideas are proposed and tested to improve efficiency of CSMA/CA mechanism for IEEE 802.15.4 MAC Layer. Primarily, we dynamically adjust the backoff exponent (BE) according to queue level of each node. Secondly, we vary the number of consecutive clear channel assessment (CCA) for packet transmission. We demonstrate also that slot compensation provided by the enhanced MAC protocol can greatly avoid unused slots. The results show the significant improvements expected by our approach among the IEEE 802.15.4 MAC standards. Synthesis results show also hardware performances of our proposed architecture.

Thermal and morphology characterization study of bio‐active poly(amide‐imide)‐based nanocomposites reinforced with modified SiO2nanoparticle with poly(vinyl alcohol)

Among the nanoparticles (NPs), the amorphous SiO2NPs are very useable, because of their important characteristics for different applications, such as mechanical performance, thermal properties, and biodegradability effects. For this manifest features SiO2NPs were used as filler in this study. Firstly, these NPs were modified with poly(vinyl alcohol) (PVA). Then, the poly(amide‐imide) (PAI) was synthesized from reaction betweenN‐trimellitylimido‐l‐methionine and 4,4′‐diaminodiphenylether in the presence of ionic liquid and triphenyl phosphite. Next, the modified SiO2NPs with PVA (SiO2‐PVA) were incorporated into the PAI matrix for the preparation of PAI‐SiO2‐PVA nanocomposites (PSiPNs). Finally, the resulting SiO2‐PVA and PSiPNs were characterized by different analyses like field emission scanning electron microscopy, Fourier transform infrared spectroscopy, X‐ray diffraction, transmission electron microscopy, and thermogravimetric analysis (TGA). TGA showed high thermal stability of the obtained PSiPNs compared to the pure PAI. POLYM. COMPOS. 37:1231–1237, 2016. © 2014 Society of Plastics Engineers

Differentiated Bandwidth Guarantees for Cloud Data Centers

By means of virtualization, computing and storage resources are effectively multiplexed by different applications in cloud data centers. However, there lacks useful approaches to share the internal network resource of cloud data centers. Invalid network sharing not only degrade the performance of applications, but also affect the efficiency of data center operation. To guarantee network performance of applications and provide fine-grained service differentiation, in this paper, we propose a differentiated bandwidth guarantee scheme for data center networks. Utility functions are constructed according to the throughput and delay sensitive characteristics of different applications. Aiming to maximize the utility of all applications, the problem is formulated as a multi-objective optimization problem. We solve this problem using a heuristic algorithm: the elitist Non-Dominated Sorted Genetic Algorithm-II(NSGA-II), and we make a multi-attribute decision to refine the solutions. Extensive simulations are conducted to show that our scheme provides minimum band-width guarantees and achieves more fine-grained service differentiation than existing approaches. The simulation also verifies that the proposed mechanism is suitable for arbitrary data center architectures.

Bioorthogonal chemistries for nanomaterial conjugation and targeting

AbstractBioorthogonal chemistries are covalent reaction pairs that proceed in the presence of biological components with complete specificity. A suite of reactions has been described to date that provides scientists and engineers with diverse operational characteristics for different applications. Nanomaterials in particular have benefitted from these new capabilities, resulting in improved coupling efficiencies and multifunctionality. In this review, we will discuss the application of bioorthogonal chemistries to different nanomaterial systems, highlighting the advantages and limitations for use in bioconjugation. We will also describe how recent improvements in the reaction speed of catalyst-free bioorthogonal chemistries have enabled the successful coupling of nanomaterials directly to live cells. Using a recently developed reaction pair, tetrazine and trans-cyclooctene, the direct covalent coupling to cells has been shown to occur on time-scales that are relevant for biological studies and diagnostic applications and can even amplify nanomaterial binding greater than tenfold relative to traditional immunoconjugates. This powerful technique still maintains exquisite specificity, however, yielding robust results in clinical diagnostic applications using human tissue and blood samples. Future work will likely focus on further advancement of the in situ amplification technique, such as increasing nanomaterial binding, enabling multiplexed detection through the use of orthogonal reaction systems and extension to applications in vivo.