The excellent properties of carbon fibers, in combination with the high price of carbon fibers, makes it interesting to recycle these fibers. Pyrolysis is already an established recycling method to recover the carbon fibers, but in this process also the sizing is removed which could result in lower mechanical properties because of bad adhesion between the fiber and matrix. In this study, recycled carbon nonwoven reinforcements made from pyrolyzed carbon fibers were pre-treated in order to improve the mechanical properties of recycled carbon polyamide and recycled carbon polypropylene composites. The pre-treatment involves applying a to the matrix adapted primer coating to the nonwoven by spraying. Via compression molding, polyamide and polypropylene composites were prepared with and without pretreatment. The tensile and interlaminar shear strength of these composites were measured to determine the effect of the pretreatment. Results revealed that both strengths could be increased by pretreatment of the carbon nonwoven and the increase was largest for the PP composites.

This work seeks to approach the comparative analysis of the distribution of POFs (polymeric optical fibers) arranged in a random and sorted manner in the manufacture of translucent concretes. The following characteristics were analyzed: compressive strength, flexural tensile strength, capillary water absorption and light transmittance. Portland cement, water, fine aggregate (sand), silica fume, polycarboxylate ether-based superplasticizer and polymeric optical fiber were used in the production of the composites. Except the fiber content, the mixture of all other inputs was kept as a fixed parameter. Groups with the following levels of POFs were produced: 0%, 2%, 3.5% and 5%. The POF content is the sum of the areas of the fiber sections in the composite with the total area of the translucent surface. The results showed that for the analysis of mechanical behavior (flexural tensile and compressive strength) and durability (capillary water absorption), composites with random and sorted fibers within the 2% POF presented to belong to statistically distinct groups. For the other fiber contents, there was no pattern of behavior, that is, it cannot be said that there is a difference within 3.5% or 5% POF between sorted and random fibers in relation to the mechanical and durability characteristics analyzed. As for the light transmittance, it was attributed that the statistical difference between the fiber arrangements only within the 5% POF content can be a consequence of their accumulation in certain points of the material, thus influencing this characteristic measured by a light meter.

In this paper, the tensile behavior of unidirectional carbon/epoxy prepreg is experimentally analyzed at varying loads and temperatures, focusing on the considerable nonlinearity at the beginning of the stress-strain curve. The high viscosity of this material presented difficulties in securely holding specimens during tensile testing. As a result, modifications were made to the conventional gripping method to enable the acquisition of reliable test data. Additionally, a longer gauge length was chosen to minimize the impact of slippage on the elastic modulus measurement. To support the experiment, a micromechanical model of a prepreg tow with fiber waviness is proposed. An RVE model of periodically distributed unidirectional waved cylindrical fibers embedded within the matrix is developed to predict the effective material stiffness parameters. Numerical results are presented for different amplitude-to-wavelength ratios which indicate the fiber waviness reduces the tensile modulus of the composite. The simulation results are in good agreement with the uniaxial tensile test of the prepreg tow.

A methodology is proposed for designing the stabilization process of polyacrylonitrile (PAN) fibers. In its core, this methodology is based on a model that describes the characteristic fiber length change during the treatment, through the de-convolution of the three main contributors (i.e. entropic shrinkage, creep, and chemical shrinkage). The model has the additional advantage of offering further insight into the physical and chemical phenomena taking place during the treatment. Validation of PAN-model prediction performance for different processing parameters was achieved as demonstrated by FTIR and DSC. Τensile testing revealed the effect of processing parameters on fiber quality, while model prediction demonstrated that ladder polymer formation is accelerated at temperatures over 200oC. Additionally, according the DSC and FTIR measurements predictions from the application of the model during stabilization seem to be more precise at high-temperature stabilization stages. It was shown that mechanical properties could be enhanced preferably by including a treatment step below 200oC, before the initiation of cyclization reactions. Further confirmation was provided via Raman spectroscopy, which demonstrated that graphitic like planes are formed upon stabilization above 200oC, and thus multistage stabilization is required to optimize synthesis of carbon fibers. Optical Microscopy proved that isothermal stabilization treatment did not severy alter the cross section geometry of PAN fiber monofilaments.

Prebiotic dietary fiber supplements are commonly consumed to help meet fiber recommendations and improve gastrointestinal health by stimulating beneficial bacteria and the production of short-chain fatty acids (SCFAs), molecules beneficial to host health. The objective of this research project was to compare potential prebiotic effects and fermentability of five commonly consumed fibers using an in vitro fermentation system measuring changes in fecal microbiota, total gas production and formation of common SCFAs. Fecal donations were collected from three healthy volunteers. Materials analyzed included: pure beta-glucan, Oatwell (commercially available oat-bran containing 22% oat β-glucan), xylooligosaccharides (XOS), WholeFiber (dried chicory root containing inulin, pectin, and hemi/celluloses), and pure inulin. Oatwell had the highest production of propionate at 12 h (4.76 μmol/mL) compared to inulin, WholeFiber and XOS samples (p<0.03). Oatwell’s effect was similar to those of the pure beta-glucan samples, both samples promoted the highest mean propionate production at 24 h. XOS resulted in a significant increase in the genus Bifidobacterium after 24 h of fermentation (0 h: 0.67 OTUs; 24 h: 5.22 OTUs; p = 0.038). Inulin and WholeFiber increased the beneficial genus Collinsella, consistent with findings in clinical studies. All analyzed compounds were fermentable and promoted the formation of beneficial SCFAs.

Ocean wave energy is a significantly well-liked renewable energy source. The Internet of Things (IoT) offers a great opportunity for development of the ocean wave energy research. The IoT technology significantly enhanced the performance of the ocean wave energy converter (WEC). The data obtained from IoT devices reduce the risk of using WEC. However, Integrating IoT devices with the WEC is a daunting task because controlling the WEC needs real-time data. This paper investigated the performance of WEC and estimate the lifetime of the modules. IoT devices integrated with various sensors determine different parameters and conditions of the ocean. The IoT platform is used for wireless voltmeters, wireless AC current meters, wireless voltage detection, wireless resistance sensors, wireless temperature sensor, wireless accelerometer, wireless pressure meters, and wireless water level sensors to determine the real-time condition of the ocean wave. These devices are also proven to be reliable and accurate.

Underwater wireless optical communication (UWOC) is acknowledged as a useful way to transmit data in ocean for short distance application. Carrying UWOC device on mobile platform is quite practical in ocean engineering, which is helpful to exploit its advantages. In application, such platform needs camera to observe surroundings and guide its action. Since the majority of ocean is always dark, active illumination is necessary to imaging. Once UWOC worked in such environment, its performance is affected by the illumination light noise. In this paper, we study the influence of underwater LED illumination on bidirectional UWOC with Monte Carlo method. We simulate forward noise from the LED illumination to the opposite receiver in the cooperative terminal, and the backscattering noise on the adjacent receiver in the same terminal. The results show that the forward noise is reduced with the increase of absorption coefficient, scattering coefficient, transmitting distance, and separated distance between receiver and the optical axis of LED. But it becomes greater with FOV of receiver. The backscattering noise is reduced with the increase of absorption coefficient and separated distance between receiver and LED. But it becomes greater with FOV and scattering coefficient, while it has little relation with transmitting distance. In order to reduce such two kind noises, besides inserting optical filter in the receivers and narrow their field, the optical axis of LED light should keep away from the receivers. The results in this paper is helpful for UWOC application.

The main objective of this work is the design and implementation of self-adaptive capabilities in wireless sensors by applying control engineering and model-based design methodologies. It has been addressed the problem related to the changes in the flow of data packets through the network connection and the excess energy consumption that this causes in these devices. To design the solution, a systemic characterization of the scheduling and execution process of embedded tasks on the device has been carried out. This means defining cause-effect relationships in the system and its modelling theoretically and/or experimentally. In turn, these models facilitate the design of control strategies to improve the dynamic behavior of the system. As a solution, a self-adaptation strategy based on feedforward control algorithm has been designed and developed, which has been applied to improve the dynamic behavior and resource consumption. The developed solution has been satisfactorily evaluated experimentally.

A The agri-food sector is in full renovation, continuously demanding new systems that allow farmers to facilitate their work. Efficient agricultural practices are essential for increasing farm profitability. Efficient agricultural practices can be increased by understanding and managing water neeeds. However, real-time monitoring of water needs is currently slow, and irrigation decisions are based on previous data or physical evidence. Furthermore, the prices of automatic systems for collecting data from several sources (soil and climate) are expensive and the autonomy is very low. Emerging Internet of Things (IoT) technologies such as wireless sensor networks can be used to collect vast amounts of data recorded via apps. By means of an LPWAN communication the farmer can know in real time the state of his crops thanks to a large number of sensors connected wirelessly and distributed across his farm. This paper presents a low consumption solution based on LoRaWAN technology. The wireless sensor node, called BoX, exhibits very low power since it has been optimized both in terms of hardware and software. The result is a higher degree of autonomy than commercial motes. That will allow the farmer to have all the information necessary to achieve an efficient management of his crops with full autonomy.

Continuous object tracking in WSNs, such as monitoring of mud-rock flows, forest fires etc., is a challenging task due to characteristic nature of continuous objects. They can appear randomly in the network field, move continuously, and can change in size and shape. Monitoring such objects in real-time generally require tremendous amount of messaging between sensor nodes to synergistically estimate object’s movement and track its location. In this paper, we propose a novel twofold-sink mechanism, comprising of a mobile and a static sink node. Both sink nodes gather information about boundary sensor nodes, which is then used to uniformly distribute energy consumption across all network nodes, thus helping in saving residual energy of network nodes. Numerous object tracking schemes, using mobile sink, have been proposed in the literature. However, existing schemes employing mobile sink cannot be applied to track continuous objects, because of momentous variation of network topology. Therefore, we present in this paper a mechanism, transformed from K-means algorithm, to find the best sensing location of the mobile sink node. It helps to reduce transmission load on the intermediate network nodes situated between static sink node and the ordinary network sensing nodes. The simulation results show that the proposed scheme can distinctly improve life time of the network, compared to one-sink protocol employed in continuous object tracking.

An existing power grid is going through a massive transformation. Smart grid technology is a radical approach for improvisation in prevailing power grid. Integration of electrical and communication infrastructure is inevitable for the deployment of Smart grid network. Smart grid technology is characterized by full duplex communication, automatic metering infrastructure, renewable energy integration, distribution automation and complete monitoring and control of entire power grid. Wireless sensor networks (WSNs) are small micro electrical mechanical systems which are accomplished to collect and communicate the data from surroundings. WSNs can be used for monitoring and control of smart grid assets. Security of wireless sensor based communication network is a major concern for researchers and developers. The limited processing capabilities of wireless sensor networks make them more vulnerable to cyber-attacks. The countermeasures against cyber-attacks must be less complex with an ability to offer confidentiality, data readiness and integrity. The address oriented design and development approach for usual communication network requires a paradigm shift to design data oriented WSN architecture. WSN security is an inevitable part of smart grid cyber security. This paper is expected to serve as a comprehensive assessment and analysis of communication standards, cyber security issues and solutions for WSN based smart grid infrastructure.

Electronic devices are sensitive to electromagnetic (EM) emissions requiring electromagnetic shielding protection to assure good operation, preventing noise, malfunctioning, or even burning. To assure protection, it is important to develop suitable material and design solutions for electronic enclosures. Most common enclosures are made with metal alloys by traditional manufacturing methods. However, resourcing to thermoplastic composites combined with additive manufac-turing (AM) technologies emerges as an alternative that enables to fabricate complex parts that are lightweight, consolidated and oxidation and corrosion resistant. In this research, an AM technique based in material extrusion was used to print 2 mm thick specimens with a multi-material made of micro-carbon fiber (CF) filled polyamide, reinforced, at specific layers, by continuous carbon fibers stacked with a 90° rotation to each other. Specimens electromagnetic shielding effectiveness (EMSE) was evaluated in the frequency band of 0.03 – 3 GHz by coaxial transmission line method. De-pending on the number of CF layers, the EM shielding obtained can up to 70 dB, with a specific shielding up to 60 dB.cm3/g, predominantly by absorption mechanism, being 22 times higher that without the CF layers. These findings fundament this innovative approach for lightweight cus-tomizable solutions for EM shielding applications.

RFID based technology innovated a new field of wireless sensing, which has been applied in posture recognition, object localization and the other sensing fields, the existing sensing methods often require tags to be attached to dynamic targets (because RFID signals are more sensitive to moving target), significantly limiting their applications. It is a challenging task to sensing a static target without tag attached in NLOS (Non-Line-of-Sight). We utilized RFID technologies to sense the static foreign objects in agricultural products, and taken metal, rock, rubber and clod as sensing targets that are common in agricultural. By deploying a tag matrices to create a sensing region, we observed the signal variations before and after the appearance of the targets in this sensing region, determined the targets’ positions and their types. Here, we buried the targets in the media of seedless cotton and wheat, and detected static targets with a non-contact method in the NLOS. Researches illustrated that by deploying appropriate tag matrices and adjusting the angle of a single RFID antenna, the matrices signals can be sensitive to the static targets’ positions and their properties,i.e. matrices signals vary with different targets and their positions. Specifically, we achieved a 100% success rate in locating metallic targets, while the success rate for clods was the lowest at 86%. We achieved a 100% recognition rate for the types of all the four objects.

This research refers to the creation of a method of medical technology such as a device that can collect, encode, temporarily store, and transfer electroencephalographic signals from epileptic patients for study and evaluation. For applying the specific apparatus related to neurostimulation technologies such as Deep Brain Stimulation (DBS) and Responsive Neurostimulation (RNS) the approaches followed concern three basic levels. The first level is concerned with initial modelling and creating the template for the following two stages. Further on, the second level is based on developing code for programming integrated circuits and simulation with the appropriate software. The third and final stage is the most substantial, as the transmitter’s construction is attempted at the evaluation level. In particular, more than one software and device are involved in this phase for the most realistic performance of the desired result. However, it is worth noting that the principal goal of this study is to achieve low consumption rates for the device’s complete and smooth operation. As a result, this research aims to evolve this device so that it can send data wirelessly and simultaneously provide energy efficiency.

In this work, a new flexible antenna integrated with OLED light sources is presented for WiMAX wireless communication systems. The proposed antenna was placed on a 100% polyester base with a thickness of 1.5 mm and achieved a high gain. We evaluated and tested its performance, including reflection coefficient, radiation pattern and gain. The flexible and simple patch antenna has been designed to operate at 3.5 GHz for WiMAX wireless communication systems with a gain value of 5.38 dB. This article proves the applicability of the proposed material for the integration of flexible antennas in OLEDs while maintaining gain performance similar to conventional flat antennas.

Landslides are a frequent and recurrent problem in hilly regions of India and predicting them is always a challenging task. In this paper, an attempt was made to deal with this problem using advanced physical and numerical modeling methods. Detailed understanding of the initial slope failures is very interesting, and challenging at the same time, in the design and development of wireless sensor network based on early warning of landslide monitoring. A small scale physical model was developed to assess the instability through a sensor network with variable rain fall intensity. This was achieved by increasing the simulated rain water flow intensity in different time spans (dry condition, at t=0 to t= 30 min, 0.5 mm/min at t=30 to t= 60 min, 0.75 mm/min at t=60 to t=91 min and 1 mm/min at t=91 to t= 120 min). The water level and movement in the slope was recorded by rainfall sensor, vibration sensor, soil moisture sensor and a digital camera. The following changes were observed during the slope failure: a) movement of small particles at top of the slope; b) initial failure of medium size soil particle; c) scouring of soil mass; d) whole slope collapse. The obtained results clearly indicated the superiority and effectiveness of the proposed system in providing a factor of safety for the progressive slope.

To investigate the structural behavior of simply supported concrete beams with steel and polypropylene fiber under low velocity impact loading. In all twenty-four beams (150X200X1800 mm) with simply supported boundary condition were modeled and analyzed using ABAQUS software. Steel and polypropylene fibers of aspect ratio of 60 and 231 respectively are used. The total volumes of fibers are maintained at 1% by volume of specimen. A 100 kg hammer with tip diameter 16 mm (hemispherical contact area = 201 mm2) with four different velocities (3.13 m/s, 4.42 m/s, 5.43 m/s and 6.11 m/s) were used in the analysis. It is observed that with the addition of hybrid fibers the deflection in beams was reduced. The beams with 1% PP and 0% steel fiber shows the maximum deflection values due to low modulus of elasticity. Beams with 0.9% steel and 0.1% polypropylene fibers was less affected in terms of deflection as compared to all other beams, it is due to presence of high tensile strength fibers.

The purpose of this study was to analyze the influence of Chitosan 0.2% in various final cleaning methods on the bond strength of fiberglass post (FP) to intrarradicular dentin. Ninety bovine incisors were sectioned to obtain root remnants measuring 18 mm in length. The roots were divided: G1: EDTA 17%; G2: EDTA 17% + PUI; G3: EDTA 17% + EA; G4: EDTA 17% + XPF; G5: Chitosan 2%; G6: Chitosan 2% + PUI; G7: Chitosan 2% + EA; G8: Chitosan 2% +XPF. After carrying out the cleaning methods, the posts were installed, and the root cleaved to to generate two disks from each root third. Bond strength values (MPa) obtained from the micro push-out test data were assessed by Kruskal-Wallis and Dwass-Steel-Critchlow-Fligner tests for multiple comparisons (α = 5%). Differences were observed in the cervical third between G1 and G8 (p=0.038), G4 and G8 (p=0.003), G6 and G8 (p=0.049), and Control and G8 (p=0.019). The final cleaning method influenced the adhesion strength of cemented FP to intrarradicular dentin. Chitosan 0.2% + XPF positively influenced adhesion strength, with the highest values in the cervical third.

With the development of the volume of information exchange and perception increases, the demands for intelligent, miniaturized and integrated optical devices for information acquisition are also increasing. As the core component of optical networks for transmitting information, how to further optimize its structural characteristics to generate richer optical characteristics and apply them to information exchange and optical field control has become a key research hotspot. The introduction of chiral twist characteristics has led to new phenomena and applications in optical field transmission and transformation for traditional optical fibers or microstructured optical fibers (MOF). Therefore, this review mainly starts from the principle of chiral optical fibers, introduces their preparation and latest application scenarios, and finally looks forward to their potential future development prospects.

The reinforcing effect of boehmite nanoparticles (BNP) in epoxy resins for fiber composite lightweight construction is related to the formation of a soft but bound interphase between filler and polymer. The interphase is able to dissipate crack propagation energy and consequently increases the fracture toughness of the epoxy resin. Usually, the nanoparticles are dispersed in the resin and then mixed with the hardener to form an applicable mixture to impregnate the fibers. If one wishes to locally increase the fracture toughness at particularly stressed positions of the fiber-reinforced polymer composites (FRPC), this could be done by spraying nanoparticles from a suspension. However, this would entail high costs for removing the nanoparticles from the ambient air. We propose that a fiber fleece containing bound nanoparticles be inserted at exposed locations. For the present proof-of-concept study, an electrospun polycarbonate nonwoven and taurine modified BNP are proposed. After fabrication of suitable PC/EP/BNP composites, the thermomechanical properties were tested by dynamic mechanical analysis (DMTA). Comparatively, the local nano-mechanical properties such as stiffness and elastic modulus were determined by atomic force microscopy (AFM). An additional investigation of the distribution of the nanoparticles in the epoxy matrix, which is a prerequisite for an effective nanocomposite, is carried out by scanning electron microscopy in transmission mode (TSEM). From the results it can be concluded that the concept of carrier fibers for nanoparticles is viable.

The aim of this paper is to create a sensor model based on optical crystal fibers (PCF). The aim of this model is to find and identify zinc cadmium. This thesis looked at three different categories of concentrations. For sensor architecture, PCF was generated using single-mode fiber-to-end split fusion (SM-PCF-SM). In this experiment, a specific wavelength spectrum was used to alter the concentration of materials covering the fiber in order to demonstrate the fiber's sensing capability. The 550nm wavelength has been used as the optical source for the fiber. The change in the output power of the external light was monitored and changes were observed for each concentration of the concentrations around the fiber. It has been found that the fiber is sensitive to small changes in concentrations. The absorption of the fiber has been calculated for the incoming capacity, as well as the losses in the capacity outside the fiber.

Mandibular critical size defect (CSD) due to pathological conditions, trauma, and congenital disease can not heal spontaneously and predominantly filled with fibrous tissue. Therefore, a Guided Bone Regeneration (GBR) combined with bone grafting can be performed. The researchers considered using Demineralized Dentin Material Membrane (DDMM) from bovine dentine as an alternative GBR. This study aimed to determine the amount of fibroblast and collagen density after DDMM and bone graft implantation on CSD. Thirty-six Rattus norvegicus rats were used as samples. Mandibular bone defect 5x5 mm was made, then filled with bone graft and covered with Bovine Pericardium Collagen Membrane (BPCM) in the control group and DDMM in the treatment group. Six samples were sacrificed on 7, 14, and 21 days post-surgical for histology examination. There were no significant differences in the amount of fibroblast and collagen density (p-value > 0,05). The amount of fibroblast is lower and the collagen density is higher in treatment group. DDMM has microporosity to prevent connective tissue ingrowth and dentine tubules to allow growth factors release. DDMM and bone graft implantation can reduce the amount of fibroblasts and increase collagen density of CSD which potentially being used as a CSD alternative treatment for bone regeneration.

In this work, we report the carbon fiber-based wire-type asymmetric supercapacitors (ASCs). The highly conductive carbon fibers were prepared by the carbonized and graphitized process using the polyimide (PI) as a carbon fiber precursor. To assemble the ASC device, the CoMnO2-coated and Fe2O3-coated carbon fibers were used as the cathode and the anode materials, respectively. FE-SEM analysis confirmed that the CoMnO2-coated carbon fiber electrode exhibited the porous hierarchical interconnected nanosheet structures, depending on the added amounts of ammonium persulfate (APS) as an oxidizing agent, and Fe2O3-coated carbon fiber electrode showed a uniform distribution of porous Fe2O3 nanorods over the surface of carbon fibers. The nanostructured CoMnO2 were directly deposited onto carbon fibers by a chemical oxidation route without high temperature treatments. In particular, the electrochemical properties of the CoMnO2-coated carbon fiber with the concentration of 6 mmol APS presented the enhanced electrochemical activity, probably due to its porous morphologies and good conductivity. Further, to reduce the interfacial contact resistance as well as improve the adhesion between transition metal nanostructures and carbon fibers, the carbon fibers were pre-coated with the Ni layer as a seed layer using an electrochemical deposition method. The fabricated ASC device delivered a specific capacitance of 221 F g-1 at 0.7 A g-1 and good rate capability of 34.8% at 4.9 A g-1. Moreover, the wire-type device displayed the superior energy density of 60.16 Wh kg-1 at a power density of 490 W kg-1 and excellent capacitance retention of 95% up to 3,000 charge/discharge cycles.

The electrical, mechanical and thermal conductivity of ethylene butene copolymer (EBC) composites with carbon fibers were studied. EBC/carbon-fiber composites can be utilized as an electro-mechanical material which is capable of changing it electric resistance with mechanical strain. Carbon fibers were introduced to EBC with different concentrations (5-25 wt%). The results showed that the addition of carbon fibers to EBC could increase the electric resistance up to 10 times. Increasing the load to 2.9 MPa could increase the electric resistance change by 4500% compared 25% fiber sample with pure EBC. It is also noted that the electric resistance of the EBC/CF composites underwent a dramatic increase with raising the strain, for example, the resistance change was around 13 times more at 15% strain in comparison to 5% of strain; The thermal conductivity tests showed that the addition of carbon fibers could increase the thermal conductivity by 40%, from 0.19 to 0.27 (Wm-1K-1). It was also observed that the addition of carbon fibers to EBC could increase the thermal conductivity.

Blending lignin as the second most abundant polymer in nature with nanostructured compounds such as dendritic polymers will not only add value to lignin, but also increase its application in various fields. In this study, softwood Kraft lignin/polyamidoamine dendritic polymer (PAMAM) blends were fabricated by solution electrospinning method to produce bead-free nanofiber mats. The mats were characterized by scanning electron microscopy (SEM), Fourier transform infrared (FTIR), zeta potential, and thermogravimetry analysis (TGA). The chemical intermolecular interactions between lignin functional groups and abundant amino groups in PAMAM were investigated by FTIR and viscosity measurement. These interactions enhanced the mechanical and thermal characteristics of lignin/PAMAM mats, providing further potential applications at industry level.

Twelve overnight fasted, healthy, male volunteers received on separate days a test breakfast consisting of (A) 100 g fresh white bread (providing 50 g starch) and 250 mL drinking water, (B) the same bread with a supplement of 10 g alpha-cyclodextrin dissolved in the drinking water (250 mL), and (C) 250 mL drinking water containing 25 g alpha-cyclodextrin. Capillary and venous blood samples were collected before breakfast and at regular intervals for a period of 3 hours thereafter. Plasma glucose was determined in capillary blood and plasma insulin in venous blood samples. Breakfast (A) let to the expected rise in blood glucose and insulin concentrations. Breakfast (C) did not produce a significant glycemic and insulinemic response, demonstrating that alpha-cyclodextrin is not hydrolyzed to glucose in the human digestive tract. Mild intestinal symptoms after the ingestion of alpha-cyclodextrin were reported by 4 subjects. The postprandial rises of plasma glucose and insulin were significantly smaller after breakfast (B) than (A). Under the conditions of this study, alpha-cyclodextrin reduced the glycemic and insulinemic index of white bread by 57 and 55 %, respectively. The postprandial time profile of plasma glucose and insulin suggests that, in an initial phase, the digestion of starch is inhibited by alpha-cyclodextrin almost completely. Yet, despite the delayed and reduced digestion of starch, the intake of breakfast (B) was not associated with flatulence or any other gastrointestinal symptoms.

In this paper, first the Self-Written Waveguide (SWW) process in wet photopolymer media (liquid solutions), are examined for three examples: single-, counter-, and co-fibers exposure. Then the SWWs formed inside solid material are examined including the effects of manipulating the alignment of the fibers. In all cases high precision measurements are used to position the fiber optic cables (FOCs) before exposure using a microscope. The self-writing process is indirectly monitored by observing (imaging) the light emerging from the side of the material sample during SWW formation. In this way the optical waveguide trajectories formed in an Acrylamide/Polyvinyl Alcohol (AA/PVA) a photopolymer material (sensitized at 532 nm) are examined. First the transmission of light by this material is characterized. Then the bending and merging of the waveguides which occur are investigated. The predictions of our model are shown to qualitatively agree with the observed trajectories. The largest index changes taking place at any time during the exposure, i.e. during SWW formation, are shown to take place at the positions where the largest exposure light intensity is present. Typically, such maxima exist close to the input face and the first maximum is referred to as the location of the Primary Eye. Other local maxima also appear further along the SWW and are referred to as Secondary Eyes, i.e. deeper within the material.

The paper describes preliminary studies on the influence of humidity on the electrical resistance of a textile sensor made of carbon fibers. The concept of the sensor refers to externally bonded fiber reinforcement commonly used to strengthen building structures. However, the zig-zag arrangement of carbon fiber tow allows measuring strains, as it is done in popular resistive strain gauges. The sensor tests proved its effectiveness in the measurement of strains, but also showed a high sensitivity to changes in the temperature and humidity which unfavorably affects the readings and their interpretation. The influence of these factors must be compensated. Due to the size of the sensor, there is not possible electrical compensation by the combining of several sensors into the half or full Wheatstone bridge circuit. Only mathematical compensation based on known humidity resistance functions is possible. The described research is the first step to develop such relations. The tests were carried out at temperatures of 10 °C, 20 °C and 30 °C, with changing the humidity in the range of 30-90%.

The proper hydrogenation of Hyper-coal (HPC) using 1, 2, 3, 4-tetrahydroquinoline (THQ) was able to decrease the oxygen content and adjust the molecular structure of HPC for preparing the spinnable pitch with high softening point (SP). The spinnable pitch prepared from the THQ-soluble (QS) fraction of HPC as a precursor consisted more naphthenic carbon groups than that prepared from the 1-methylnaphthalene (1-MN) soluble (MNS) fraction of HPC. The HPC-QS derived pitch showed excellent spinnability even the SP of 260°C, and the tensile strength of the resultant carbon fiber was up to 1350 MPa with a diameter around 8 µm by only heat treatment at 800°C for 5 min.

Polymer-derived SiC-polycrystalline fiber (Tyranno SA) shows excellent heat-resistance up to 2000^oC, and relatively high strength. Up to now, through our research, the relationship between the strength and residual defects of the fiber, which were formed during the production processes (degradation and sintering), has been clarified. In this paper, we addressed the relationship between the production condition and the surface roughness of the obtained SiC-polycrystalline fiber, using three different raw fibers (Elementary ratio: Si₁Al_0.01C_1.5O_0.4~0.5) and three different types of reactor (Open system, Partially-open system, and Closed system). With increase in the oxygen content in the raw fiber, the degradation during the production process easily proceeded. In this case, the degradation reactions (SiO+2C=SiC+CO and SiO₂+3C=SiC+2CO) in the inside of each filament become faster, and then the CO partial pressure on the surface of each filament is considered to be increased. In consequence, according to Le Chatelier’s principle, the surface degradation reaction and grain growth of formed SiC crystals would be considered to become slower. That is to say, using the raw fiber with higher oxygen content and closed system (highest CO content in the reactor), much smoother surface of the SiC-polycrystalline fiber could be achieved.

The use of plant fibers as reinforcement in composites with the aim of totally or partially replacing synthetic fibers has received significant attention in the last years. However, one of the disadvantages of the use of these fibers in polymeric composites is associated to the fact that they are hydrophilic, resulting in poor adhesion with most matrices when in the presence of moisture. In addition, another problem encountered is the lower strength of this type of fiber and, as a solution to minimize these problems, the composite can be hybridized by adding layers of natural and synthetic fibers and the use of resin protection along the thickness of the composite. (Lateral protection) to reduce moisture absorption by the laminate. The objective of this work is to obtain composites formed by five layers of reinforcement and terephthalic polyester matrix, one of which is reinforced only with short glass fiber-E blanket, another reinforced only with jute fiber and a third hybrid containing the fibers. Two types of reinforcements with interlayer layers. Afterwards, the loss of mechanical properties was observed when these materials were immersed in distilled water, with and without lateral protection, until reaching saturation. We evaluated parameters such as the influence of configuration type and environmental conditions, such as the amount of water absorption. The obtained results show that the hybrid composite obtained a behavior close to the composite containing only fiberglass, and better than the one containing only jute fiber and that the absorption was smaller in the samples with side protection.

The present study investigates the failure mechanisms of industrial fiber materials, using a custom designed fiber cutting performance test bench. The fracture morphologies of single PA6 fibers are examined by scanning electron microscopy. The analysis reveals that fiber cutting can be distinguished according to four distinct stages of fiber failure represented by shearing, cutting, brittle fracture, and tensile failure, which are the result of different mechanisms active during the processes of crack initiation, extension and fracture. The results of fractographic analysis are further verified by an analysis of the blade assembly speed with respect to time over the entire fracture failure process based on high-speed camera data. The results of fractographic analysis and blade assembly speed are fully consistent.

: This study was aimed at assessing adaptation and bonding of discontinuous (short) glass fiber-reinforced composite to intraradicular dentin EverX Flow (GC Corporation, Tokyo, Japan), when used as intracanal composite filling and anchorage instead of traditional fiber posts. (2) Methods: Seventy intact extracted human teeth were endodontically treated and randomly divided into 6 groups (n=10), depending on the materials used in the post space. In Group 1, a 2-bottle universal adhesive G2 Bond Universal + EverX Flow were tested. In group 2, a single-component universal adhesive G-Premio Bond + EverX Flow were used. In groups 3 and 4 the same materials are tested, but after cleaning of the canal walls with 17% EDTA and final irrigation with 5.25% NaOCl Ultrasound Activated. In the last three Groups (5-7) traditional prefabricated GC Fiber Posts 1.6 mm silanized with G-Multi Primer for 1 minute are cemented with a dual-cured composite resin cement (GradiaCore), after ultrasonic irrigation in the groups 6 and 7. In each group, 1 mm-thick slices from each sample (n=10) were cut for light microscope and SEM inspection for study materials adaption to the dentin and for measuring push-out strength of post / cemement material to the dentin / prefabricated post. These results were statistically analyzed: as the data distribution was not normal, the Kruskal-Wallis Analysis of Variance by Ranks had to be applied. The level of significance was set at p<0.05. Results: Push-out forces varied between 6.66-8.37 MPa. No statistically significant differences were recorded among the groups. Microscopic examination showed that ultrasonic irri-gation increased adaptation of the materials to the dentin surface. There was a trend of higher bond strength among the tested groups when EverX Flow was used. Also, the type of failure was more often cohesive when ultrasonic irrigation and two-step adhesive system were used. Conclusions: Within the limitations of this in vitro study, it may be concluded that when EverX Flow was used for intracanal anchorage in the post-endodontic recon-struction, similar push-out retentive forces and strength to those of traditional fiber posts cemented with particulate filler resin composite cements were achieved. Although further studies are necessary, EverX Flow represents an effective alternative to traditional fiber post adhesion in particular when used in combination with the two-step adhesive system and ultrasonic activation.

The high-speed railway operation environment monitoring network system has a wide variety of sensors and inconsistent business requirements, which have certain requirements for data transmission delay and network life. Most of the previous research focuses only on prolonging network lifetime or reducing data transmission delays when designing or optimizing routing protocols, without co-designing the two. In addition, due to the harsh operating environment of high-speed railways, when the network changes dynamically, the traditional routing algorithm will generate unnecessary redesigns and lead to high overhead. Based on the actual needs of high-speed railway operation environment monitoring, this paper proposes a novel Double Q-values adaptive model combined with the existing reinforcement learning method, which considers the energy balance of the network and real-time data transmission, and constructs energy saving and delay. The two-dimensional reward avoids the extra overhead of maintaining a global routing table while capturing network dynamics. In addition, the adaptive weight coefficient is used to ensure the adaptability of the model to each business of the high-speed railway operation environment monitoring system. Finally, simulations and performance evaluations are carried out and compared with previous studies.Finally, simulations and performance evaluations are carried out and compared with previous studies. The results show that the proposed routing algorithm successfully extends the network’s life cycle and gets good real-time data performance. It also saves energy and has fewer delays than the other three routing protocols in different situations.

The Unmanned Aerial Vehicles (UAVs), used in civilian applications such as emergency medical deliveries, precision agriculture, wireless communication provisioning, etc., face the challenge of limited flight time due to their reliance on the on-board battery. Therefore, developing efficient mechanisms for in-situ power transfer to recharge UAV batteries hold potential in extending their mission time. In this paper, we study the use of far-field wireless power transfer (WPT) technique from specialized, transmitter UAVs (tUAVs) carrying Multiple Input Multiple Output (MIMO) antennas for transferring wireless power to receiver UAVs (rUAVs) in a mission. The tUAVs can fly and adjust their distance to the rUAVs to maximize energy transfer. The use of MIMO antennas further boost the energy reception by narrowing the energy beam toward the rUAVs. The complexity of their dynamic operating environment increases with the growing number of tUAVs, and rUAVs with varying levels of energy consumption and residual power. We propose an intelligent trajectory selection algorithm for the tUAVs based on a deep reinforcement learning model called Proximal Policy Optimization (PPO) to optimize the energy transfer gain. Simulation results demonstrate that with the use of PPO, the system achieves a tenfold flight time extension compared to no wireless recharging. Further, PPO outperforms the benchmark movement strategies of ’Traveling Salesman Problem’ and ’Low Battery First’ when used by the tUAVs.

The monitoring of maternal and child health, using wearable devices made with wireless sensor technologies, is expected to reduce maternal and child death rates. Wireless sensor technologies have been used in wireless sensor networks to enable the acquisition of data for monitoring machines, smart cities, transportation, asset tracking, and tracking of human activity. Applications based on wireless body area network (WBAN) have been used in healthcare for measuring and monitoring of patient health and activity through integration with wearable devices. Wireless sensors used in WBAN can be cost-effective, enable remote availability, and can be integrated with electronic health record (EHR) management systems. Interoperability of WBAN sensor data with other linked data has the potential to improve health for all, including maternal and child health through the improvement of data access, data quality and healthcare access. This paper presents a survey of the state-of-the-art techniques for managing WBAN sensor data interoperability. The findings in this study will provide reliable support to enable policymakers and health care providers to take action to enhance the use of e-health to improve maternal-child health and reduce the mortality rates of women and children.

Wireless Sensor Networks (WSN) is the network of the resource-constrained network which forms the foundation of the Internet of Things (IoT). The Routing Protocol for Low-power and Lossy Networks (RPL) is responsible for generating and managing data routing paths. Nodes implementing RPL uses the mechanics of Objective Function (OF) to select the preferred next-hop node – parent node, and optimal routing path to the destination node. If routing decisions are not efficiently made, this results in increased collision domain, leading to packet losses and packet retransmission which impairs the network operational lifetime. In this study, we present the Contiki Operating System (OS), a state-of-the-art OS for IoTs, ContikiRPL; Contiki variant of RPL. We investigated the performance of RPL with respect to its two OFs; Objective Function Zero (OF0) and the Minimum Rank with Hysteresis Objective Function (MRHOF). The performance of these OFs was evaluated on the following metrics; Packet Delivery Ratio (PDR), Power consumption, and network latency. The result shows that MRHOF outperformed OF0 on all metrics with an overall average PDR of 91.5%, a latency of 44ms, and power consumption of 1.72mW across all nodes. This results in optimal network performance with improved network operational lifetime.

The development of a remote sensing system is proposed in the present study for monitoring of the electrical resistance of concrete in real time. The sensor is embedded in the concrete bulk, and the data are sent via a gateway to a computer for the data analysis. The sensibility of the sensors to the effect of the presence of a crystalline admixture has been also assessed in the study. Different cycles of drying and water penetration have been considered to assess the sensor performance in different water content conditions. Sensors have shown to capable of detecting changes in electrical resistance when humidity changes. The sensitive of the sensors to the action of waterproofing admixtures in the mortar has been also confirmed. The contribution of the temperature plays a critical role on the sensor response, and its simultaneous monitoring is recommended.

Wireless Sensor Networks (WSNs) is considered to be a promising research area since it entails sensing capabilities. WSNs are confronted by fabricated explosion injection attacks and in return results into draining of vitality on sensor nodes routing mainly because of increased capabilities in a broad range of applications where sensor nodes use a battery as the power source. In this paper, we reveal and claim a state-of-the-art model to minimize vitality depletion of nodes within the network in return increases network period to more realistic stretch. It is revealed that the main cause is vitality consumption unbalances in different parts of the network direct resulting from having a static sink. More still, the network nodes neighboring the sink insistently partake in progressing data of other nodes to the sink. Consequently, the network nodes are supplementarily subjected to untimely vitality exhaustion. This paper mainly provides a novel movable (mobile) fuzzy logic sink approach and an intelligent system like expect systems that are able to scrutinize network situation, and make the superlative choice for spreading the network period robotically.

The landscape of centralized cloud computing is now changing to distributed and decentralized clouds with promising impacts on energy consumption, resource availability, resilience, and customer experience. This research highlights the impacts of emerging IT trends, namely, 5G wireless technology, blockchain, and industrial Artificial Intelligence (AI) in development and realization of the next generation of cloud computing. Integration of these technologies in cyber-physical system and cloud manufacturing paradigms is explained and a unified edge-fog-cloud architecture is proposed for successful implementation in manufacturing systems.

A decade ago, non-radiative wireless power transmission reemerged a promising alternative to deliver electrical power to devices where a physical wiring proved to be unfeasible. However, conventional coupling-based approaches are neither scalable nor efficient when multiple devices are involved, as they are restricted by factors like coupling and external environments. Zenneck waves are excited at interfaces, like surface plasmons and have the potential to deliver electrical power to devices placed on a conducting surface. Here, we demonstrate, efficient and long range delivery of electrical power by exciting non-radiative waves over metal surfaces to multiple loads.Our modeling and simulation using Maxwells equation with proper boundary conditions shows Zenneck type behavior for the excited waves and are in excellent agreement with experimental results. In conclusion, we physically realize a radically different power transfer system, based on a wave, whose existence has been fiercely debated for over a century.

Pipelines are widely used for transportation of hydrocarbon fluids over millions of miles over the world. The structures of the pipelines are designed to withstand several environmental loading conditions to ensure safe and reliable distribution from point of production to the shore or distributions deport. However, leaks in pipeline networks are one of the major causes of innumerable losses in pipeline operators and nature. Incidents of pipeline failure can result in serious ecological disasters, human casualties and financial loss. In order to avoid such menace and maintain safe and reliable pipeline infrastructure, substantial research efforts have been devoted to implementing pipeline leak detection and localisation using different approaches. This paper discusses on pipelines leakage detection technologies and summarises the state-of-the-art achievements. Different leakage detection and localisation in pipeline systems are reviewed and their strengths and weaknesses are highlighted. Comparative performance analysis is performed to provide a guide in determining which leak detection method is appropriate for particular operating settings. In addition, research gaps and open issues for development of reliable pipeline leakage detection systems are discussed.

When an earthquake or a large fire has occurred, it is difficult to secure communication networks for rescue in the building due to the destruction of commercial communication networks. Although analog radio systems such as VHF (very high frequency) and UHF (ultra-high frequency) are used for rescue operation in general, communication failure occurs in closed spaces, causing difficulties in smooth rescue operations. When the communication infrastructures have been destroyed in a building in the disaster, an emergency wireless telecommunication environment should be constructed to secure a safer disaster response environment. In this study, along with comparison of the performances of diverse communication frequencies, UWB (Ultra-Wide Band) wireless telecommunication networks were evaluated under five building indoor environment conditions including open spaces. UWB communication modules were fabricated to satisfy the IEEE (The Institute of Electrical and Electronics Engineers) 802.15.4a standard performance to measure distances in which communications are possible according to the indoor environment for each of six channels with different UWB communication frequencies. The results indicated that the distances in which communications are possible for each the six channels were average 15.5 m, maximum 20 m in open spaces; average 17.33 m, maximum 20 m in corridors; average 15.3 m, maximum 20 m in indoor office environments with office fixtures; average 4.33 m, maximum 6 m in vertical spaces of stairs; and average 6.5 m, maximum 17 m in closed horizontal spaces with a fire door. In this case, the communication performance and distance performance were shown to be the most excellent at a frequency (Centre Frequency) of 6489.6 and a band of 5980.3 – 6998.9 MHz, which is UWB 7ch. In conclusion, it is judged that if UWB communication modules are installed in the disaster area at intervals of 20 m and multi-channels are used, communication environments can be constructed even in closed spaces

To address the insufficient mechanical properties of calcined phosphogypsum, this research aims to investigate the utilization of basalt fiber and calcium carbonate whiskers as reinforcing agents. The study examines their impact on the flexural and compressive strength, toughness, water resistance, and tensile strength of calcined phosphogypsum. In the individual tests, basalt fibers with different lengths (3 mm, 6 mm, 9 mm, and 18 mm) were added at dosages of 0%, 0.5%, 1.0%, and 1.5% respectively. The findings demonstrate that basalt fiber effectively enhances the flexural and compressive strength, toughness, and tensile strength of calcined phosphogypsum, albeit potentially compromising water resistance. Among the various fiber lengths, the 6 mm fibers exhibit the most advantageous influence on the performance of calcined phosphogypsum. A subsequent test was conducted to investigate the impact of cross-scale fibers on the properties of calcined phosphogypsum by mixing 6 mm basalt fibers and calcium carbonate whiskers. The results illustrate that calcium carbonate whisker refines the pores, thereby improving the flexural strength and toughness of calcined phosphogypsum. Furthermore, it compensates for the water resistance limitations associated with the sole utilization of basalt fiber while further augmenting the tensile strength and strain capacity. However, it should be noted that increasing the dosage of both calcium carbonate whiskers and basalt fibers concurrently leads to increased porosity of phosphogypsum and reduced compressive strength.

Conventional methods for pathogen detection in water rely on time-consuming enrichment steps followed by biochemical identification strategies, which require assay times ranging from 24 hours to up to a week. However, in recent years, significant efforts have been made towards the development of biosensing technologies enabling rapid and close-to-real-time detection of waterborne pathogens. In previous studies, we developed a plastic optical fiber (POF) immunosensor using an optoelectronic configuration consisting of a U-Shape probe connected to an LED and a photodetector. Bacterial detection was evaluated with the immunosensor immersed in a bacterial suspension in water with a known concentration. Here, we report on the sensitivity of a new optoelectronic configuration consisting of two POF U-Shape probes, one as the reference and the other as the immunosensor, for the detection of Escherichia coli. In addition, another way of detection was tested where the sensors were calibrated in the air, before immersed in bacterial suspension and then read in the air, making the immunosensor more sensitive and with a faster detection time. This new sensor detected the presence of E. coli at 104 CFU/mL in less than 10 minutes. Currently sub 10 minutes is faster than previous studies using fiber-optic based biosensors. It is also a much simpler and quicker methodology when compared with conventional laboratory technology.

Dental polymers are often advertised and selected for use in restorations based upon the flexural strength of prefabricated discs, which may not accurately reflect their performance in dental applications. The objectives of this study were, therefore, to determine whether the three-point bending (3PB) test for flexural strength would be predictive of the “crunch-the-crown” CTC test for the failure load. Three brands of polymers (Trilor, Juvora, and Pekkton) were fabricated into rectangular bars and fully contoured crowns (10 specimens of each polymer brand, 30 specimens of each shape). Bars were tested in 3PB to determine flexural strength, and crowns were CTC tested to determine failure load after luting to resin abutments. Statistical significance was evaluated by one-way ANOVA ( = 0.05) and Pearson’s correlation coefficient. The fracture mechanisms were characterized by scanning electron microscopy (SEM). There were significant differences (p < 0.05) in the mean crown failure loads (Trilor [7,033 N] > Juvora [5,217 N] > Pekkton [3,023 N]) and mean flexural strengths of the bars (Trilor [468 MPa] > Juvora [197 MPa] = Pekkton [192 MPa]). There were no correlations between flexural strength and failure load. The mode of crown fracture was different between the polymers, and included deformation (Juvora), ductile-to-brittle fracture (Pekkton), and a combination of cracks and deformation (Trilor). The flexural strength was not correlated with the corresponding crown failure load. Dental practitioners should not rely on the value of flexural strength obtained from the three-point bending test, as advertised from the manufacturer, to predict the performance of polymeric crowns.

A total internal reflection photonic crystal fiber (PCF) based on hexagonal core is proposed for gas sensing in a specific wavelength range. The higher sensitivity and lower confinement loss were realized by the structure of the proposed PCF consists of two layers with circular holes rotated hexagonally around a core region and six slotted air-hole in the cladding based on numerical analysis. The simulation results show that the enhancement of the relative sensitivity has been done by enhancing the diameter of the hexagonal shape air-hole cladding (d1) and the hexagonal arranged holes around the central solid core (d0) in this design. Also, the confinement loss has been reduced by enhancing the ratio of length to width of slotted holes (l/w) and decreasing the cladding air-hole diameters (d1). As the refractive index increases, the wavelength shifts toward the long wavelength. And in a certain temperature range, the transmission characteristics of the device does not change with the temperature. The results are helpful for designing high performance PCF for gas sensing applications.

Dietary fiber has been associated with health benefits, therefore, the availability of validated tools to assess food consumption associated with high-fiber foods would allow the quantification of the intake of this functional nutrient, the identification of risk groups and target populations, and the development of public policies and/or programs aimed at improving the health of the population. In this study, a fiber intake short food frequency questionnaire (FFQ) was translated into Spanish and its content validity was determined by a group of experts, to subsequently conduct a pilot test including 198 subjects aged 36+12.5 years, residing in Chile (46 men and 150 women), with the purpose of quantifying dietary fiber intake. The global assessment of the FFQ revealed a validity coefficient of 0.98+0.02; after the application of the pilot, mean dietary fiber intake in adult Chilean residents was of 13 g per day, with similar results to those found in the National Food Consumption Survey 2010 (12.5 g per day in men, and 11.5 g in women). The FFQ is a quick and valid tool to classify people on the basis of their habitual dietary fiber intake.

UHPC is a cement-based composite that is used in new construction and/or renovation of existing structures to increase their service life. It is a unique composite material that may be used as an alternative to concrete in harsh conditions. Following decades of research and development, a wide range of commercial UHPC compositions are now accessible across the world to fulfill the growing number of applications and demand for high-quality construction materials. Although UHPC has significant advantages over conventional concrete, its use is limited because of rigid design restrictions and excessive pricing. As a consequence, a detailed analysis of UHPC's durability qualities is necessary to provide critical information for material testing requirements and methods, as well as to widen its practical applications. The goal of this study is to learn more about UHPC and to encourage more research and use of UHPC.

Cytochrome P450 (CYPs) is a functionally diversified third-largest gene family that exploded in the plant kingdom. Their role in different organ development has been illustrated by the intervention of phytohormone. Cotton is a model organism for cell differentiation and cell elongation. To decipher the participation of CYPs in different cotton fiber developmental stages, we identified and characterized 2460 CYPs in three diploids and two allotetraploid cottons. Furthermore, In-silico expression and cluster analysis of cotton CYPs was conducted to distinguish the fiber stage-specific clusters that have the determining role in different stages of fiber development. The subgenome expression of two conserved Gossypium hirsutum CYPs, namely, GhCYP78A197 and GhCYP78A198 contributed to fiber initiation at an early stage of fiber development, governed by the co-occurrence of TATA and MYB TFs binding sites. Coexpression network partners of these two GhCYP78A annotated as auxin, kinases, chromatin remodeler, epigenetic regulator and cyclin-related genes that possibly induce the endoreduplication and cell proliferation for fiber cell initiation to define the high yield and biomass.

Fabry-Perot air chamber was constructed at the melting point (splicing location) of two single-mode fibers by glycerin assisted self-expansion method. The morphology of the Fabry-Perot air chamber was fabricated and optimized by modulating the splicing parameters (drawing process, discharging location, time and intensity) and the fibers’ end-face (plane or arc). The in-line or reflected Fabry-Perot cavities have been applied to determine the tensile strain in the range of 0-1.2 N. The train sensing performance of the spherical shaped FP cavity has been experimentally demonstrated with the best sensitivity of 3.628 nm/N, corresponding to the resolution of ~0.005 N. The proposed FP fiber sensor has the advantages of low cost, fast fabrication and easy-integration with the common fiber system.

Consumption of prebiotic fibers to modulate the human gut microbiome is a promising strategy to positively impact health. Nevertheless, given the compositional complexity of the microbiome and its inter-individual variances, generalized recommendations on the source or amount of fiber supplements remain vague. This problem is further compounded by availability of tractable in vitro and in vivo models to validate certain fibers. We employed a gnotobiotic mouse model containing an a priori characterized 14-member synthetic human gut microbiome (SM) for their ability to metabolize a suit of fibers in vitro; the SM contains 14 different strains belonging to five distinct phyla. Since soluble purified fibers have been a common subject of studies, we specifically investigated the effects of concentrated raw fibers (CRFs)—containing fibers from pea, oat, psyllium, wheat and apple—on the compositional and functional alterations in the SM. We demonstrate that, compared to a fiber-free diet, CRF supplementation increased the abundance of fiber-degraders namely Eubacterium rectale, Roseburia intestinalis and Bacteroides ovatus and decreased the abundance of the mucin-degrader Akkermansia muciniphila. These results were corroborated by a general increase of bacterial fiber-degrading α-glucosidase enzyme activity. Overall, our results highlight the ability of CRFs to enhance the microbial fiber-degrading capacity.

The distributed long-range sensing system using the standard telecommunication single-mode optical fiber in a function of a distributed sensor for sensing of mechanical vibrations is described. Various events generating vibrations such as walking or running person, moving cars, trains and others can be detected, localized and classified. The sensor and related sensing system components were designed and constructed and the system was tested both in the laboratory and in the real situation with 88 km telecom optical link, and the results are presented.

In the past decades, Fiber Reinforced Concrete has been gaining more attention in the concrete research development. There are many advantages of the inclusion of fiber into reinforced concrete structures. It was found that the inclusion of fibers in concrete, be it synthetic or natural, resulted in the improvement of the thermal properties of concrete, as well as its strength to some extent. However, the inclusion of fibers in concrete does affects its thermo-mechanical properties. The objective of this study is to identify the potential of the addition Polypropylene and Kenaf fibers in cement mortar at different compositions (0.1%, 0.2%, and 0.3%). Eight mixes were analyzed for this purpose. Upon investigating the flow ability, compressive strength, tensile strength, and thermal conductivity of the mortar samples, it was found that the incorporation of PP and Kenaf fibers reduced the flow ability. Cement mortar samples containing 0.1% addition of PP and Kenaf fibers show the highest compressive strength compared to other percentages, while samples containing 0.3% addition of PP and Kenaf fibers show the highest tensile strength compared to other percentages. The thermal conductivity of mortar samples shows reduction when high percentages of both fibers were used.

Extinction of natural resources builds up pressure on governments to invest in research to find more sustainable resources for construction sector. Earlier studies on mortar and concrete show that bottom ash and basalt fiber are independently alternative binder in the concrete sector. This study aims to use bottom ash and basalt fiber blends as alternative novel-based composites in pure cement paste. Strength and durability properties of two different percentages of bottom ash (40% and 50%) and three volume fractions of basalt fiber (0.3%, 0.75%, and 1.5%) were used at three curing periods (7, 28, and 56 days). In order to measure physical properties of the basalt-reinforced bottom ash cement paste composites flowability, dry unit weight, porosity and water absorption measurements at 7, 28, and 56 days of curing were performed. Furthermore, mechanical properties of composites determined by unconfined compressive strength and flexural strength tests. Finally, to assess the durability sulfate-resistance and seawater-resistance tests have been performed on composites at 28 and 56 days of curing. Results showed that addition of basalt fiber improves physical, mechanical and chemical stability properties of paste up to a limiting basalt fiber addition (0.3% volume fraction) where above an adverse effect have been monitored. It is clear that observed results can lead to development of sustainability strategies in the concrete industry by utilizing bottom ash and basalt fiber as an alternative binder.

Type-2 fuzzy sets were introduced by L. Zadeh aiming at modelling some settings in which fuzzy sets (usually called type-1 fuzzy sets) are not sufficient to reflect certain uncertainty degrees - loosely speaking, they are fuzzy sets whose membership degrees are ordinary fuzzy sets. On the other hand, fiber bundles are topological entities of extreme importance in Mathematics itself and many other scientific areas, like Physics (General Relativity, Field Theory etc.), finance modelling, and statistical inference. The present work introduces a conceptual link between the two ideas and conjectures about the potential mutual benefits that can be obtained from this viewpoint.As an objective and usable product of the presented ideas, it is described a framework for defining type-2 fuzzy hedges, proper to operate on interval type-2 fuzzy sets.

A multiscale modelling approach was developed in order to estimate the effect of defects on the strength of unidirectional carbon fiber composites. The work encompasses a micromechanics approach, where the known reinforcement and matrix properties are experimentally verified and a 3D finite element model is meshed directly from micrographs. Boundary conditions for loading the micromechanical model are derived from macroscale finite element simulations of the component in question. Using a microscale model based on the actual microstructure, material parameters and load case allows realistic estimation of the effect of a defect. The modelling approach was tested with a unidirectional carbon fiber composite beam, from which the micromechanical model was created and experimentally validated. The effect of porosity was simulated using a resin-rich area in the microstructure and the results were compared to experimental work on samples containing pores.

The addition of flaxseed and amaranth on the physicochemical, functional and microstructural changes of instant-extruded cereals was evaluated. Six different mixtures were made with additions of amaranth (30%–50%) and flaxseed (10% and 15%) using maize grits and minor additives as supplementary ingredients and then extruded in a twin-screw extruder. The extrudates evaluated, had insoluble and soluble fiber contents increased with the proportion of amaranth and flaxseed. The mixture 4 (higher flaxseed content) presented highest soluble fiber percentage (1.9%). Extruded cereals had the lowest viscosity (<99.5 cp) and highest hardness values (5.2 N) whereas the dietary fiber content was highest. Fiber content increase, resulted in a higher water solubility index (WSI) (0.5) and decrease the water absorption index (WAI) (2.5). Amaranth and flaxseed incorporation increased crystallinity, resulting in a larger, and more compact laminar structure. Amaranth and flaxseed addition resulted in extruded cereals with acceptable physicochemical and functional properties.

Two isotropic pitches were prepared by air blowing and nitrogen distillation method using ethylene tar (ET) as a raw material. And correspondent carbon fibers were obtained through conventional melt spinning, stabilization and carbonization. The structures and properties of resultant pitches and fibers were characterized and their differences were discussed in this work. The results showed that introduction of the oxygen by air blowing method could quickly increase the yield and softening point of pitch. Moreover, the air blown pitch (ABP) composed of linear methylene chains of aromatic molecules while the nitrogen distilled pitch (NDP) mainly contained polycondensed aromatic rings, which was due to the oxygen containing functional groups existed in ABP could impede order stack of pitch molecules and form methylene bridge structure, instead of aromatic condensed structure like NDP. Meanwhile, the spinnability of ABP was not decreased even containing 2.31 wt% oxygen. In contrast, ABP had narrower molecular weight distribution, which contributed to better stabilization properties and higher tensile strength of carbon fiber. The tensile strength of carbon fibers from ABP was reached to 860 MPa with fiber diameter of about 10 μm, which was higher than that of NDP-derived carbon fibers of 640 MPa.

Being able to forecast events is of great importance in many fields, from brain behavior to earthquakes or stock markets. Because each dynamical system has intrinsic features, different statistical tools have to be used for each system. Here we study the time series of the output intensity of a fiber laser with an ordinal patterns analysis, and we look for temporal correlations in order to statistically forecast the most intense events. We set two thresholds, a low one and a high one, to distinguish between low intensity versus high intensity events. We find that when the time series is performing events below the low threshold it shows some preferred temporal patterns before performing events above a high threshold.

A novel 8-channel demux device based on multicore photonic crystal fiber (PCF) structures that operate at C-band range (1530-1565nm) has been demonstrated. The PCF demux design is based on replacing some air-holes areas with lithium niobate and silicon nitride materials over the PCF axis alongside with the appropriate optimizations of the PCF structure. The beam propagation method (BPM) combined with Matlab codes were used to modeled the demux device and to optimized the geometrical parameters of the PCF structure. Simulation results show that 8-channel can be demultiplexing after light propagation of 5 cm with large bandwidth (4.03-4.69nm) and crosstalk ((-16.88)-(-15.93) dB). Thus, the proposed device has a great potential to be integrated in dense wavelength division multiplexing (DWDM) technology for increasing performances in networking systems.

In this article, bio-composites derived from starch-glycerol biodegradable matrix reinforced with jute fibers have been fabricated using the wet hand lay-up and compression moulding techniques. Samples having different weight percentages of jute fiber in the starch matrix have been analysed. The fibers surface was chemically treated by alkaline sodium hydroxide for improving the interphase bonding between fiber and matrix. Tensile test for the composites were done and the sample with highest tensile strength was selected for further tests that included water absorption, scanning electron microscopy and thermal analysis. It has been concluded that the ultimate tensile strength was found to be maximum for the composition of 15% fiber by weight composite as 7.547 MPa without epoxy coating and 10.43 MPa with epoxy coating. The major disadvantage of bio-composite is its high water absorption property, which in this study has been inhibited by the epoxy resin layer. Herein, the results of various tests done disclose a noteworthy improvement in the overall properties of bio-composite, in comparison to the neat biodegradable starch matrix.

The rapid evolution of technology has given rise to a connected world, where billions of devices interact seamlessly, forming what is known as the Internet of Things (IoT). While IoT offers incredible convenience and efficiency, it presents a significant challenge in cybersecurity and is characterized by various power, capacity, and computational process limitations. Machine learning techniques are employed within Intrusion Detection Systems (IDS) to enhance their capabilities in identifying and responding to security threats. The key features selected to improve IDS efficiency and reduce dataset size, thereby decreasing the time required for attack detection, are drawn from the extensive network dataset. This paper introduces an enhanced feature selection method designed to reduce the computational overhead on IoT resources while simultaneously strengthening intrusion detection capabilities within the IoT environment. Experimental results based on the InSDN dataset demonstrate that our proposed methodology achieves the highest accuracy with the fewest number of features and low computational cost. Specifically, we attain a 99.99% accuracy with 11 features and a computational time of 0.8599 seconds.

The proliferation of radio frequency devices in today's society, especially in smart homes, Internet of Things devices, and smartphones, underscores the urgent need for robust identification methods to strengthen cybersecurity. This paper delves into the field of radio frequency fingerprinting to propose a Bluetooth device identification method based on the application of the Jensen-Shannon divergence to the statistical distribution of noise in Bluetooth signals. A detailed case study is performed to investigate the Bluetooth radio frequency noise recorded at 5 Gsps from different devices is investigated to define a statistical radio frequency fingerprint for each Bluetooth device. A noise model is used to extract a unique, universal, persistent, recoverable, and robust statistical radio frequency fingerprint that identifies each Bluetooth device. Then, using the Jensen-Shannon divergence, different noise signals provided by each Bluetooth device are compared with the statistical radio frequency fingerprint of all devices and a membership resolution is declared. The study shows that the proposed method can discriminate between devices of the same brand and model, achieving an identification effectiveness of 99.5 \%. By leveraging the statistical radio frequency fingerprint of Bluetooth devices, this research not only contributes to the advancement of the field of implicit device authentication systems based on wireless communication but also provides valuable insights into the practical implementation of radio frequency identification techniques that could be useful in forensic processes.

In recent years, wireless power transfer (WPT) has progressed rapidly in both theory and commercialization abroad. However, existing research into WPT coil design for low-power devices is limited. This paper investigates coil structure using printed circuit board (PCB) for magnetic resonant coupling WPT to address this gap. Specifically, the impacts of key geometric parameters on the coil quality factor and coupling coefficient are analysed through models and simulations. Equivalent PCB coils were formed for mutual inductance models, and four basic compensation circuits were analysed. The impacts of changes in coil thickness, line width, turn spacing, and number of turns on the quality factor of PCB coils were analysed with a fixed outer diameter of the coil. In this paper, to mitigate the coil offset while retaining PCB manufacturing simplicity for practical uses, a dual layer PCB coil structure is proposed. The structure optimizated PCB coil could offer remarkable improvements in the WPT system for low power electronic devices.

This study aimed to simulate dynamic irrigation management zones (MZs) in two maize fields for a variable rate hose-reel fertigation machine (VRFM) with a 4-section boom control. Soil moisture content was measured from nine and four soil moisture sensors in Field 1 (8.2 ha) and Field 2 (2.5 ha), respectively in different dates during the 2022 crop season. Three- and five-MZs scenarios were simulated per irrigation and the theoretical maps were processed for implementation. The application maps fitted to the VRFM showed significant spatiotemporal variations in irrigation requirements. For instance, in Field 1, 3-MZs modelling showed that the areas requiring High (H), Medium (M), and Low (L) level irrigation on July 21 were 1.60, 4.84, and 1.85 ha, respectively, whereas the farmer applied uniform rate over the whole field. H level sub-areas ranged between 1.22 ha (July 25) and 3.25 ha (July 7), showing a coefficient of variation (CV) of 43.32% for the 3-MZs, whereas H level sub-areas for 5-MZs varied from 0.41 ha (July 2) to 1.49 ha (July 7) with a CV value of 48.84%. High levels of within-field variability can be addressed using precise and dynamic irrigation MZs fitted to the irrigation technology used.

A new power receiving unit (PRU) is proposed in this paper for the resonant wireless power transfer (WPT), which is characterized by the capability of attracting high power from the power transmitting unit (PTU). The resonant WPT is designed for delivering the electrical power to the PRU attached on an electrical vehicle (EV) chassis 50cm away from a PTU installed on the ground. The proposed PRU uses only the passive elements such as inductors, diodes and the capacitors, which needs no initial power from the EV. It is then applicable for charging a battery to several hundred volts for even a first-time charging battery. At a switching frequency of the resonant WPT in the experiment being 4MHz, the proposed PRU behaves itself as a negative impedance converter (NIC) in the subharmonics of 4MHz. The NIC effect plus the subharmonic oscillation causes an instability current charging the battery connected to the PRU. In this paper, we simulated the PRU and performed the experiment. The experiment demonstrates a battery charging of 150W from 50cm away using three D-mode GaN HEMT transistors via the instability current ramp. The power transfer efficiency (PTE) improved as the power delivered to load (PDL) goes higher. The best power transfer efficiency (PTE) is 65% in the present findings. The simulation analysis shows that the circuit allows itself be used to much higher power transfer when it is implemented with more GaN HEMT transistors connected in parallel. The theoretical derivation of the PRU circuit is also used to support both the experimental and simulation results.

Stevia Rebaudiana Bertoni Morita II, a perennial plant native to Paraguay and Brazil, is also widely cultivated in the state of Colima, Mexico, for its use as a sweetener in food and beverages. The op-timization of soil parameters is crucial for maximizing biomass production and stevioside levels in stevia crops. This research presents the development and implementation of a monitoring system to track essential soil parameters, including pH, temperature, humidity, electrical conductivity, ni-trogen, phosphorus, and potassium. The system employs a wireless sensor network to collect qua-si-real-time data, which is transmitted and stored in a web-based platform. A Mamdani-type fuzzy logic model is utilized to process the collected data and provide to farmers an integrated assessment of soil quality. By comparing the quality data output of the fuzzy logic model with a line-ar-regression model, the system demonstrated acceptable performance, with a determination coef-ficient of 0.532 for random data and 0.906 for gathered measurements. The system enables farmers to gain insights into the soil quality of their stevia crops and empowers them to take preventive and corrective actions to improve the soil quality specifically for stevia crops.

With the dramatic increase in the number of mobile users and wireless devices accessing the network, the performance of the fifth generation (5G) wireless communication systems has been severely challenged. Reconfigurable intelligent surfaces (RIS), one of the potential technologies for the sixth generation (6G), has received a lot of attention. Since it is easier to deploy, consumes less power, and is inexpensive. RIS is an electromagnetic metamaterial that serves to reconfigure the wireless environment by adjusting the phase, amplitude and frequency of the wireless signal. To maximize channel transmission efficiency and improve the reliability of communication systems, the acquisition of channel state information (CSI) is essential. Therefore, an effective channel estimation method guarantees the achievement of excellent RIS performance. This paper conducts a comprehensive investigation of the existing channel estimation methods of RIS, analysis and comparison of channel model building and CSI acquisition schemes in different frequency bands, in addition to a comprehensive description of generic channel estimation methods, with a focus on the application of deep learning. Finally, we conclude the paper and provide an outlook in the future development of RIS channel estimation.

Optimizing the magnetic coupling of two coils of a dynamic wireless charging power supply for electric vehicles (EVs) is a challenging and crucial task. This article examines three situations of the magnetic coupling between two identical rectangular spiral coils with the same number of turns as a function of both the horizontal (X axis) and vertical (Z axis) alignment. In the first one, the analysis of the magnetic coupling between two copper air coils is presented. However, the obtained coupling coefficient was very low with a high leakage flux which affected the performance of the charging system. In the second case, a straightforward shielding method that involves inserting a magnetic material of the ferrite type is proposed to circumvent the aforementioned problems. Unfortunately, the obtained results show that simple shielding is still only a partial and insufficient solution. In the third situation, an aluminum sheet was consequently placed on the top of the ferrite to provide an adequate shielding structure. Additionally, a 3D analysis of the proper and mutual induction parameters separating the two coils as well as a magnetic field or induction distribution is also performed using the ANSYS Maxwell software. The results highlight the significance of the enhanced structure.

Landslides are a global and frequent natural hazard, affecting many communities and infrastructure networks. Technological solutions are needed for long-term, large-scale condition monitoring of infrastructure earthworks, or natural slopes. However, current instruments for slope stability monitoring are often costly, require a complex installation process and/or data processing schemes, or have poor resolution. Wireless sensor networks comprising low-power, low-cost sensors have been shown to be a crucial part of landslide early warning systems. Here, we present the development of a novel sensing approach that uses linear arrays of three-axis accelerometers, used for monitoring soil deformation. By combining these deformation measurements with depth-resolved temperature measurements, we can link our data to subsurface thermal-hydrological regimes where relevant. In this research, we present a configuration of cascaded I2C sensors that (i) have ultra-low power consumption and (ii) enable an adjustable probe length. From an electromechanical perspective, we developed a novel board-to-board connection method that enables narrow, semi-flexible sensor arrays and a streamlined assembly process. The low-cost connection method relies on a specific FR4 printed circuit board design that allows board-to-board press-fitting without using electromechanical components or solder connections. The sensor assembly is placed in a thin, semi-flexible tube (inner diameter 6.35 mm) that is filled with an epoxy compound. The resulting sensor probe is connected to a AA battery powered data logger with wireless connectivity. We characterize the system's electromechanical properties and investigate the accuracy of deformation measurements. Our experiments performed with probes up to 1.8 m long demonstrate long-term connector stability, as well as probe mechanical flexibility. Furthermore, our accuracy analysis indicates that deformation measurements can be performed with a 0.390 mm resolution and a 95% confidence interval of ±0.73 mm per meter of probe length. This research shows the suitability of low-cost accelerometer arrays for distributed soil stability monitoring. In comparison to emerging low-cost measurements of surface displacement, our approach provides depth-resolved deformation, which can inform about shallow sliding surfaces.

Disease-related data and information collected by physicians, patients, and researchers seem insignificant at first glance. Still, the same unorganized data contain valuable information that is often hidden. The task of data mining techniques is to extract patterns to classify the data accurately. One of the various Data mining and its methods have been used often to diagnose various diseases. In this study, a machine learning (ML) technique based on distributed computing in the Apache Spark computing space is used to diagnose diabetics or hidden pattern of the illness to detect the disease using a large dataset in real-time. Implementation results of three ML techniques of Decision Tree (DT) technique or Random Forest (RF) or Support Vector Machine (SVM) in the Apache Spark computing environment using the Scala programming language and WEKA show that RF is more efficient and faster to diagnose diabetes in big data.

Unmanned aerial vehicles (UAVs)-based communication system is a promising solution to meet coverage and capacity requirements of future wireless networks. However, UAV-enabled communications is constrained with its coverage, energy consumption, and flying regulations, and the number of works focusing on the sustainability aspect of UAV-assisted networking has been limited in the literature so far. In this paper, we propose a solution to this limitation; particularly, we design a $Q$-learning-based UAV positioning scheme for sustainable wireless connectivity considering key constraints, that are, altitude regulations, non-flight zones, and transmit power. The objective is to find the optimal position of the UAV base station (BS) and minimize the energy consumption while maximizing the number of users covered. Moreover, a weighting mechanism is developed, where the energy consumption and number of users covered can be prioritized according to network/battery conditions. The proposed Q-learning-based solution is compared to the baseline k-means clustering method, where the UAV BS is positioned at the centroid location that minimizes the cumulative distance between the UAV BS and the users. The results demonstrate that the proposed solution outperforms the baseline k-means clustering-based method in terms of the number of users covered while achieving the desired minimization of the energy consumption.

In this study, the external magnetic field emitted by a wireless power transfer (WPT) system and the internal electric field induced into human body models during recharging operations of a compact electric vehicle (EV) are evaluated. To this aim an ad-hoc formulation for the source modeling is coupled with a commercial software that performs numerical dosimetry. Specifically, two realistic anatomical models both in a driving position and in a standing posture are considered, and the chassis of the EV is modeled either as a currently employed aluminum alloys and as a futuristic carbon fiber composite panel. Aligned and misaligned coil configurations of the WPT system are considered as well. The analysis of the obtained results shows that the ICNIRP reference levels are exceeded in the driving position, especially for the carbon fiber chassis, whereas no exceedance is observed in terms of basic restrictions, at least for the considered scenarios.

The IEEE 802.15.4-2015 standard includes the SUN (Smart Utility Networks) modulations, i.e., SUN-FSK, SUN-OQPSK and SUN-OFDM, which provide long range communications and allow to trade data rate, occupied bandwidth and reliability. However, given the constraints of low-power devices and the challenges of the wireless channel, communication reliability cannot still meet the PDR (Packet Delivery Ratio) requirements of industrial applications, i.e., PDR>99%. Hence, in this paper we evaluate the benefits of improving communication reliability by combining packet transmissions with modulation diversity using multiple IEEE 802.15.4g SUN modulations. The results derived from a real-world deployment show that going from 1 to 3 packet transmissions with the same SUN modulation can increase PDR from 85.0/84.6/71.3% to 94.2/94.1/86.0% using SUN-FSK, SUN-OQPSK and SUN-OFDM, respectively. Combining the same number of packet transmissions with modulation diversity allows to further increase the average PDR to 97.1%, indicating its potential as a tool to help meeting the reliability requirements of industrial applications.

Fire accidents are causing a huge human death as well as economic losses throughout the world every year. But a novel fire detection and extinguishing system could reduce these losses to a great extent. We are proposing a cost effective and yet very efficient system which has been developed in our laboratory and evaluated while in operation. Our system consists of two units: detection unit and extinguishing unit. For detection purposes we used smoke, IR and temperature sensors. While for extinguishing purposes we used both foam and water. We used a PC to process and control our system through LabVIEW software of National Instrument, USA. The detection unit will send signal through a wireless module to PC if fire is detected. Then PC (LabVIEW) will process the signal and using relay module first of all the electric power and gas lines will be turned off. The extinguishing unit will then release foam or water to extinguish the fire. The system will send SMS to the predefined numbers using GSM module. Our system is location independent as it uses GSM and can be operated from remote location using wireless module. After performance evaluation it was found to be fast and reliable.

Wireless Sensor Networks (WSN) is designed to collect information across a large number of limited battery sensor nodes. Therefore, it is important to minimize the energy consumption of each node, which leads to the extension of the network life. Our goal is to design an intelligent WSN that collects as much information as possible to process it intelligently. To achieve this goal, an agent has been migrated to each node in order to process the information and to cooperate with these neighboring nodes while Mobile Agents (MA) can be used to reduce information between nodes and send those to the base station (Sink). This work proposes to use communication architecture for wireless sensor networks based on the Multi Agent System (MAS) to ensure optimal information collection. The collaboration of these agents generates a simple message that summarizes the important information in order to transmit it by a mobile agent. To reduce the size of the MA, the nodes of the network have been grouped into sector. As for each MA, we have established an optimal itinerary, consuming a minimum amount of energy with the data aggregation efficiency in a minimum time. Successive simulations in large scale wireless sensor networks through the SINALGO simulator show the performance of our proposal, in terms of energy consumption and package delivery rate.

Wireless sensor networks can provide a cheap and flexible infrastructure to support the measurement of noise pollution. However, the processing of the gathered data is challenging to implement on resource-constrained nodes, because each node has its own limited power supply, low-performance and low-power micro-controller unit and other limited processing resources, as well as limited amount of memory. We propose a sensor node for monitoring of indoor ambient noise. The sensor node is based on a hardware platform with limited computational resources and utilizes a number of simplifications to approximate more complex and costly signal processing stage. Furthermore, to reduce the communication between the sensor node and a sink node, as well as the power consumed by the IEEE 802.15.4 (ZigBee) transceiver, we perform digital A-weighting filtering and non-calibrated calculation of the sound pressure level on the node. According to experimental results, the proposed sound level meter can accurately measure the noise levels of up to 100~dB, with the mean difference of less than 2~dB compared to Class 1 sound level meter. The proposed device can continuously monitor indoor noise for several days. Despite the limitations of the used hardware platform, the presented node is a promising low-cost and low-power solution for indoor ambient noise monitoring.

The use of unmanned aerial vehicle (UAV) during emergency response of a disaster has been widespread in recent years and the terrain images captured by the cameras on board these vehicles are significant sources of information for such disaster monitoring operations. Thus, analyzing such images are important for assessing the terrain of interest during such emergency response operations. Further, these UAVs are mainly used in disaster monitoring systems for the automated deployment of sensor nodes in real time. Therefore, deploying and localizing the wireless sensor nodes optimally, only in the regions of interest that are identified by segmenting the images captured by UAVs, hold paramount significance thereby effecting their performance. In this paper, the highly effective nature-inspired Plant Growth Simulation Algorithm (PGSA) has been applied for the segmentation of such terrestrial images and also for the localization of the deployed sensor nodes. The problem is formulated as a multi-dimensional optimization problem and PGSA has been used to solve it. Furthermore, the proposed method has been compared to other existing evolutionary methods and simulation results show that PGSA gives better performance with respect to both speed and accuracy unlike other techniques in literature.

Knowing the mechanical properties of fibrous composite materials used in aeronautical industry from the design phase is a primary objective for designers. There are many methods for determining them, but they are laborious and require a long calculation time. And some of the methods are very approximate, giving only upper and lower bounds for these values. Experimental measurements also consume time and others resources. A method for sufficiently accurate and quickly obtained estimation of the engineering constants of the homogenized material is presented in the work. FEM is used to determine the natural frequencies of a standard bar, for which there are sufficiently precise classical methods for expressing these constants according to the properties of the homogenized material. In this way, these sought constants can be determined. In the work, Young's modulus will be determined for such a material, using the relationships that provide the proper pulsations for the longitudinal vibrations. Within the adopted model, transverse and torsional vibrations will be eliminated by blocking the nodes on the surface of the bars. In this way, more longitudinal self-pulsations can be obtained, so the precision in calculating the Young's modulus will increase.

As environmental regulations become stricter, weight- and cost-effective fiber-reinforced polymer com-posites are being considered as alternative materials in the automobile industry. Rapid impregnation of the resin into the reinforcing fibers is critical during liquid composite molding, and the optimization of resin impregnation is related to the cycle time and quality of the products. In this review, various resins capable of rapid impregnation, including thermoset and thermoplastic resins, are discussed for manu-facturing fiber-reinforced composites used in the automobile industry, along with their advantages and disadvantages. Finally, vital factors and perspectives for developing rapidly impregnated resin-based fiber-reinforced composites for automobile applications are discussed

A novel simplifying Volterra structure algorithm is proposed for intensity modulation direct detection (IM-DD) optical fiber short distance communication system by using the decision feedback equalization algorithm (DFE). Based on this algorithm, the signal damage for four-level pulse amplitude modulation signal (PAM-4) is compensated, which is caused by device bandwidth limitation and dispersion during transmission. Experiments have been carried out using a 25GHz Electro-absorption Modulated Laser (EML), showing that PAM-4 signals can transmit over 10km in standard single-mode fiber (SSMF). The 112Gbps and 128Gbps signals can reach the error rate threshold of KP4-FEC (BER=2*10-4) and HD-FEC (BER=3.8*10-3), respectively. The simplified principle and process of proposed Volterra-based equalization algorithm are presented. Experimental results show that the algorithm complexity is greatly reduced by 75%, which provides an effective theoretical support for the commercial application of this algorithm.

Carbon fiber insole (CFI), which is lightweight and stiff to reduce energy loss and help wearers perform better in sports, has recently been introduced. However, there are scarce reports on the effects of CFI on sports performance, muscle fatigue and wearing comfort. This study investigat-ed the short-term effects of CFI on sports performance, lower extremity muscle activity, and sub-jective comfort. Thirty young healthy males performed various sports tasks and treadmill runs with wearable sensors under two experimental insole conditions (benchmark insole as a baseline, CFI). The results showed that compared to the benchmark insole, CFI significantly improved sports performance in terms of power generation and agility. However, it activated more of the Tibialis Anterior and Gastrocnemius Medialis muscles and was perceived stiffer, and less com-fortable. These findings suggested that CFI can improve sports performance, but it could cause more lower extremity muscle fatigue and subjective discomfort.

For the numerical simulation of components made of short fiber-reinforced composites the correct prediction of the deformation including the elastic and plastic behavior and its spatial distribution is essential. When using purely deterministic modeling approaches the information of the probabilistic microstructure is not included in the simulation process. One possible approach for the integration of stochastic information is the use of random fields. In this study numerical simulations of tensile test specimens are conducted utilizing a finite deformation elastic-ideal plastic material model. A selection of the material parameters covering the elastic and plastic domain are represented by cross-correlated second-order Gaussian random fields to incorporate the probabilistic nature of the material parameters. To validate the modeling approach tensile tests until failure are carried out experimentally, that confirm the assumption of spatially distributed material behavior in both the elastic and plastic domain. Since the correlation lengths of the random fields cannot be determined by pure analytic treatments, additionally numerical simulations are performed for different values of the correlation length. The numerical simulations endorse the influence of the correlation length on the overall behavior. For a correlation length of 5mm a good conformity with the experimental results is obtained. Therefore, it is concluded, that the presented modeling approach is suitable to predict the elastic and plastic deformation of a set of tensile test specimens made of short fiber-reinforced composite sufficiently.

As use of composite materials increases, the search for suitable automated processes gains relevance to guarantee production quality by ensuring uniformity of the process, minimizing the amount of generated scrap and reducing time and energy consumption. Limitations on production by traditional means such as hand lay-up, vacuum bagging and in-autoclave methods, tend not to be as efficient when the size and shape complexity of the part being produced increases, motivating the search for alternative processes such as the Automated Tape Laying (ATL). This work aims to describe the process of modelling and simulating a composite ATL with in situ consolidation by characterizing the machine elements, using the finite differences method in conjunction with energy balances, in order to create a digital twin of the process for further control design. The modelling approach implemented is able to follow the process dynamics when changes to the heating element are imposed as well as to predict the composite material temperature response, making it suitable to work as a digital twin of a production process using an ATL machine.

The booming wearable market and recent advances in material science has led to the rapid development of the various wearable sensors, actuators, and devices that can be worn, embedded in fabric or accessories, or tattoos directly onto the skin. Wearable actuators, a subcategory of wearable technology, have attracted enormous interest from researchers in various disciplines and many wearable actuators and devices have been developed in the past few decades to assist and improve people's everyday lives. In this paper, we review the actuation mechanisms, structures, applications, and limitations of recently developed wearable actuators including pneumatic and hydraulic actuators, shape memory alloys and polymers, thermal and hygroscopic materials, dielectric elastomers, ionic and conducting polymers, piezoelectric actuators, electromagnetic actuators, liquid crystal elastomers, etc. Examples of the recent applications such as wearable soft robots, haptic devices, and personal thermal regulation textiles are highlighted. Finally, we point out the current bottleneck and suggest the prospective future research directions for wearable actuators.

Lignocellulosic fibers are widely applied as composite reinforcement due to their properties. The thermal degradation behavior determines the maximum temperature in which the fiber can be applied without significant mass loss. It is possible to determine these temperatures using Thermogravimetric Analysis (TG). In particular, when curves are obtained at different heating rates, kinetic parameters can be determined and more detailed characteristics of the material are obtained. However, every curve obtained at a distinct heating rate demands material, cost, and time. Methods to predict thermogravimetric curves can be very useful in the materials science field and in this sense mathematical approaches are powerful tools if well employed. For this reason, in the present study, curaua TG curves were obtained at three different heating rates (5, 10, 20, and 40 °C.min-1) and Vyazovkin kinetic parameters were obtained. After, the experimental curves were fitted using an artificial neural network (ANN) approach followed by a Surface Response Methodology (SRM). Curves at any heating rate between the minimum and maximum experimental heating rates were obtained with high reliability. Finally, Vyazovkin kinetic parameters were tested again with the new curves showing similar kinetic parameters from the experimental ones. In conclusion, due to the capability to learn from the own data, ANN combined with SRM seems to be an excellent alternative to predict TG curves that do not test experimentally, opening the range of applications.

Abstract: This study was aimed to determine the influence of the volume fraction of steel fibers and on fracture parameters of concrete. Fifty notched steel fiber reinforced concrete (SFRC) beams and ordinary concrete beams with dimensions of 100mm×100mm×515mm were cast and tested via three-point bending test. Among them, the type of steel fiber is milling type (MF), and the volume fraction of steel fiber added is 0%, 0.5%, 0.5%, 1.5%, 1.5%, 2%, respectively. The effects of the steel fiber volume fraction (VF) on the critical stress intensity factor (KIC), fracture energy (GF), the deflection at failure(δ0), the critical crack mouth opening displacement (CMODC) and the critical crack tip opening displacement (CTODC)were studied. Through the analysis of test phenomena and test data such as load-deflection (P-δ) curve, load-crack mouth opening displacement (P-CMOD) curve and load-crack tip opening displacement (P-CTOD) curve following conclusions are drawn: With the increase of steel fiber volume fraction, some fracture parameters increase gradually and maintain a certain linear growth. The gain ratio of fracture parameters increases significantly, and the gain effect is obvious. Through this law of growth, the experimental statistical formulas of fracture energy and critical stress intensity factor are summarized.

A new covered yarn system is proposed in this manuscript by controlling the tension of the spandex elastic yarn drawing.. By analyzing the relationship between the draw ratio and yarn tension, it has been verified that the new tension controlled drawing system is feasible and results in yarns with superior quality and process stability.

The damage caused by global warming is rapidly increasing, and its adverse effects become more evident with each passing day. Although it is known that the use of alternative binder materials in concrete would decrease this negative effect, reluctance to new composites continues. Waste use plays a vital role in sustainability studies. In this study, pure cement paste was prepared and enriched with carbon fiber. This study investigated the wide range of volume fraction of carbon fiber in cement-based composites. Two different industrial wastes, marble dust, and bottom ash were chosen and mixed with cement and four different (0.3%, 0.75%, 1.5%, and 2.5%) carbon fiber volume fractions. Based on physical, mechanical, and durability tests at 7, 28, and 56-days of curing, the composites were resistant to sulfate and seawater attack. The 0.75% carbon fiber addition seems to be an optimum volume percentage beyond which both physical and mechanical properties were adversely affected. The composites with 0.75% carbon fiber have reached 48.4 MPa and 47.2 MPa at 56-days of curing for marble dust and bottom ash mixture groups, respectively.

We propose a 10-Gb/s 64-quadrature amplitude modulation (QAM) signal-based Radio over Fiber (RoF) system for 50 km of standard single mode fiber length which utilizes Reinforcement Learning (RL) SARSA based decision method to indicate an effective decision which mitigates nonlinearity. By utilizing RL-SARSA algorithm, the results demonstrate that significant reduction can be obtained in terms of bit error rate.

Machine learning (ML) methodologies have been looked upon recently as a potential candidate for mitigating nonlinearity issues in optical communications. In this paper, we experimentally demonstrate a 40-Gb/s 256-quadrature amplitude modulation (QAM) signal-based Radio over Fiber (RoF) system for 50 km of standard single mode fiber length which utilizes support vector machine (SVM) decision method to indicate an effective nonlinearity mitigation. The influence of different impairments in the system is evaluated that includes the influences of Mach-Zehnder Modulator nonlinearities, in-phase and quadrature phase skew of the modulator. By utilizing SVM, the results demonstrated in terms of bit error rate and eye linearity suggest that impairments are significantly reduced and licit input signal power span of 5dBs is enlarged to 15 dBs.

Expansive soil shows dual swell-shrink which is not suitable for the construction. Several mitigating techniques exist to counteract the problem promulgate by expansive clayey soils. This paper explored the penitential mecho-chemical reinforcement of expansive clayey soil to mitigate the effect of upward swelling pressure and heave. The polypropylene fiber is randomly distributed in the soil for mechanical stabilization, and the industrial residual silica fume is used as a chemical stabilizer. The experimental analysis is made in three phases which involved the tests on mechanical reinforced expansive soil using randomly distributed polypropylene fibers with different percentages (0.25%, 0.50%, and 1.00%), and 12mm length. The second phase of experiments carried out on chemical stabilized expansive soil with different percentages (2%, 4% and 8%) of silica and next phase of the experimental focused in the combination of mecho-chemical stabilization of the expansive soil with different combination of silica (i.e., 2%, 4% and 8%) and polypropylene fibers (i.e., 0.25%, 0.50% and 1.00%). Maximum dry density (MDD), optimum moisture content (OMC), liquid limit (LL), plastic limit (PL), plastic index (PI) grain size, and constant volume swelling pressure test were performed on unreinforced and reinforced expansive soil to investigate the effect of polypropylene fiber and silica fume on the engineering properties of expansive clayey soil. The experimental results illustrate that the inclusion of polypropylene fiber has a significant effect on the upward swelling pressure and expansion property of expansive soil. The reduction in the upward swelling pressure and expansion is a function of fiber content. These results also indicated that the use of silica fume caused a reduction in upward swelling potential, and its effect was considerably more than the influence of fiber.

Adding steel fibers to concrete improves the capacity in tension-driven failure modes. An example is the shear capacity in steel fiber reinforced concrete (SFRC) beams with longitudinal reinforcement and without shear reinforcement. Since no mechanical models exist that can fully describe the behavior of SFRC beams without shear reinforcement failing in shear, a number of empirical equations have been suggested in the past. This paper compiles the existing empirical equations and code provisions for the prediction of the shear capacity of SFRC beams failing in shear as well as a database of 487 experiments reported in the literature. The experimental shear capacities from the database are then compared to the prediction equations. This comparison shows a large scatter on the ratio of experimental to predicted values. The practice of defining the tensile strength of SFRC based on different experiments internationally makes the comparison difficult. For design purposes, the code prediction methods based on the Eurocode shear expression provide reasonable results (with coefficients of variation on the ratio of tested to predicted results of 27% - 29%). None of the currently available methods properly describe the behavior of SFRC beams failing in shear. As such, this work shows the need for studies that address the different shear-carrying mechanisms in SFRC and its crack kinematics.

An ethanol vapor sensor based on a microfiber with quantum-dots (QDs) gel coating is proposed and demonstrated. The QDs gel was made from UV glue as the gel matrix and the CdSe/ZnS QDs with a concentration of 1mg/mL. The drawing and coating process were conducted by using a simple and low-cost home-made system. The bending, ethanol sensing, temperature response and time response tests were carried out, alternatively. The experimental results show that the fabricated sensor has a high sensitivity of -3.3%/ppm, a really low temperature cross-sensitivity of 0.17 ppm/℃ and a fast response time of 1.1s. The robust structure with ease of fabrication and excellent sensing performance render it a promising platform for real ethanol sensing application.

Acoustic emission (AE) has proven to be a very useful technique for determining damage in ceramic matrix composites (CMCs). CMCs rely on various cracking mechanisms which enable non-linear stress-strain behavior with ultimate failure of the composite due to fiber failure. Since these damage mechanisms are all micro-fracture mechanisms, they emit stress waves ideal for AE monitoring. These are typically plate waves since for most specimens or applications one dimension is significantly smaller than the wavelength of the sound waves emitted. By utilizing the information of the sound waveforms captured on multiple channels from individual events, the location and identity of the sources can often be elucidated. The keys to the technique are the use of wide-band frequency sensors, digitization of the waveforms (modal AE), strategic placement of sensors to sort the data and acquire important contents of the waveforms pertinent for identification, and familiarity with the material as to the damage mechanisms occurring at prescribed points of the stress history. The AE information informs the damage progression in a unique way which adds to the understanding of the process of failure for these composites. The AE methodology was applied to composites tested in fatigue at different frequencies where identification of when and where AE occurred coupled with waveform analysis leads to source identification and failure progression.

In this paper, a geometric body-centered model to simulate the periodic structure of unidirectional fibrous composites is presented. To this end, three prescribed configurations are introduced to predict in a deterministic manner the arrangement of internal and neighboring fibers inside the matrix. Thus, three different representative volume elements (RVEs) are established. Furthermore, the concept of the interphase has been taken into account, stating that each individual fiber is encircled by a thin layer of variable thermomechanical properties. Next, these three unit cells are transformed in a unified manner to a coaxial multilayer cylinder model. This advanced model includes the influence of fiber contiguity in parallel with the interphase concept on the thermomechanical properties of the overall material. Then, by the use of this model, the authors propose explicit expressions to evaluate the longitudinal and transverse thermal conductivity of this type of composite. The theoretical predictions were compared with experimental results, as well as with theoretical values yielded by some reliable formulae derived from other workers, and a reasonable agreement was found.

The interest in random fiber lasers (RFLs), first demonstrated one decade ago, is still growing and their basic characteristics have been studied by several authors. RFLs are open systems that present instabilities in the intensity fluctuations due to the energy exchange among their non-orthogonal quasi-modes. In this work, we present a review of the recent investigations on the output characteristics of a continuous-wave erbium-doped RFL, with emphasis on the statistical behavior of the emitted intensity fluctuations. A progression from the Gaussian to Lévy and back to the Gaussian statistical regime was observed by increasing the excitation laser power from below to above the RFL threshold. By analyzing the RFL output intensity fluctuations, the probability density function of emission intensities was determined, and its correspondence with the experimental results was identified, enabling a clear demonstration of the analogy between the RFL phenomenon and the spin-glass phase transition. A replica-symmetry-breaking phase above the RFL threshold was characterized and the glassy behavior of the emitted light was established. We also discuss perspectives for future investigations on RFL systems.

A single mode waveguide grating coupler based on multiple Si-SiO₂ pairs onto Si substrate has been designed. Numerical analysis has been carried out to calculate optimum thickness of the layers of Si-SiO₂ that ensures the constructive interference between reflected waves and actual guided wave for high coupling efficiency. Based on the results, an optimal design is developed and modeled by using a 2-D finite difference time domain (2-D FDTD) simulator that dictates a coupling efficiency of as much as 78% (-1.07 dB) at the wavelength of 1550 nm, and a 1-dB bandwidth of 77 nm. The numerical method will be useful to calculate the optimum thicknesses of the layers for any reflector based grating coupler of different materials.

Fiber reinforced thermoplastics (FRTP), which is reinforced with glass or carbon fibers, are used to improve the mechanical strength of injection-molded products. However, FRTP has problems such as the formation of weld lines, the deterioration of the appearance due to the exposure of fibers on the molded product surface, and the deterioration of the strength of molded products due to the fiber orientation in the molded products. We have designed and fabricated an injection mold capable of melt flow control and induction heating and cooling that has the functions of both heating and cooling the injection mold as well as the function of controlling the melt flow direction using a movable core pin. In this study, the above-mentioned mold was used for the molding of carbon fiber reinforced semi-aromatic polyamide. As a result, we found that increasing the heating temperature of the mold and increasing melt flow control volume contribute to the prevention of the generation of a weld line and the exposure of fibers on the molded product surface, as well as to the formation of a flat surface and increased bending strength. The relationships of these results with the carbon fiber orientation in the molded products and the crystallization of semi-aromatic polyamide were also examined in this study.