The prediction of bone remodeling behaviour is a challenging factor in encouraging the long-term stability of hip arthroplasties. The presence of femoral components modifies the biomechanical environment of the bone and alters the bone growth process. Issues of bone loss and gait instability on both limbs are associated with the remodeling process. In this study, finite element analysis with an adaptive bone remodeling algorithm was used to predict the changes in bone mineral density following total hip and resurfacing hip arthroplasty. A three-dimensional model of the pelvis-femur was constructed from computed tomography (CT-based) images of a 79-year-old female patient with hip osteoarthritis. The prosthesis stem of the total hip arthroplasty was modelled with a titanium alloy material, while the femoral head had alumina properties. Meanwhile, resurfacing of the hip implant was completed with a cobalt-chromium material. Contact between the components and bone was designed to be perfectly bonded at the interface. Results indicate that the bone mineral density was modified over five years on all models, including hip osteoarthritis. The changes of BMD were predicted as being high between year zero and year one, especially in the proximal region. Changes were observed to be minimal in the following years. The bone remodeling process was also predicted for the non-operated femur. However, the adaptation was lower compared to the operated limbs. The reduction in bone mineral density suggested the bone loss phenomenon after a few years.
Neat cellulose acetate (CA) and CA/polysulfone (PSf) blend ultrafiltration membranes in the presence of polyvinylpyrrolidone as a pore former were prepared via a phase inversion technique. The prepared membranes were characterized by Fourier transform infrared, scanning electron microscopy, mechanical strength, water content, porosity, permeate flux and heavy metals (Pb2+, Cd2+, Zn2+ and Ni2+) rejection to comprehend the impact of polymer blend composition and additive on the properties of the modified membranes. The water flux expanded by increasing of PSf content in the polymer composition. CA/PSf (60/40) had the highest flux among prepared membranes. Prepared blend membranes were able to remove heavy metals from water in the following order: Pb2+ > Cd2+ > Zn2+ > Ni2+. The CA/PSf (80/20) blend membrane had great performance among prepared membranes due to the high heavy metals removal and permeate flux.
Removal of low-concentration ammonia (1-10 ppm) from aquaculture wastewater was investigated via polysulfone (PSf)/zeolite mixed matrix membrane. PSf/zeolite mixed matrix membranes with different weight ratios (90/10, 80/20, 70/30 and 60/40 wt.%) were prepared and characterized. Results indicate that PSf/zeolite (80/20) was the most efficient membrane for removal of low-concentration ammonia. The ammonia elimination by PSf/zeolite (80/20) from aqueous solution for 10, 7, 5, 3 and 1 ppm of ammonia was 100%, 99%, 98.8%, 96% and 95% respectively. The recorded results revealed that pure water flux declined in higher loading of zeolite in the membrane matrix due to surface pore blockage caused by zeolite particles. On the other hand, ammonia elimination from water was decreased in higher contents of zeolite because of formation of cavities and macrovoids in the membrane substructure.
Due to the continuous advancements in wireless communication in terms of quality of communication and affordability of the technology, the application area of Mobile Adhoc Networks (MANETs) significantly growing particularly in military and disaster management. Considering the sensitivity of the application areas, security in terms of detection of Denial of Service (DoS) and intrusion has become prime concern in research and development in the area. The security systems suggested in the past has state recognition problem where the system is not able to accurately identify the actual state of the network nodes due to the absence of clear definition of states of the nodes. In this context, this paper proposes a framework based on Finite State Machine (FSM) for denial of service and intrusion detection in MANETs. In particular, an Interruption Detection system for Adhoc On-demand Distance Vector (ID-AODV) protocol is presented based on finite state machine. The packet dropping and sequence number attacks are closely investigated and detection systems for both types of attacks are designed. The major functional modules of ID-AODV includes network monitoring system, finite state machine and attack detection model. Simulations are carried out in network simulator NS-2 to evaluate the performance of the proposed framework. A comparative evaluation of the performance is also performed with the state-of-the-art techniques: RIDAN and AODV. The performance evaluations attest the benefits of proposed framework in terms of providing better security for denial of service and intrusion detection attacks.
Non-uniformly sized activated carbons were derived from doum palm shell, a new precursor, by carbonization in air and activation using KOH, NaOH and ZnCl2. The activated carbon fibres were characterised by X-ray diffraction, N2 adsorption-desorption, scanning electron microscopy, particle size analysis and evaluated for Cd(II) and Pb(II) removal. The 40-50 nm size, less graphitic, mesoporous NaOH activated carbon yielded high adsorption efficiency, pointing largely to the influence surface area. The performance of the KOH based activated carbon was arguably explained for the first time in terms of crystallinity. The efficiencies of the mesoporous ZnCl2-formulated activated carbon diminished due to the presence of larger particles. Batch adsorption of divalent metals revealed dependence on adsorbent dose, agitation time, pH and adsorbate concentrations with high adsorption efficiencies at optimum operating parameters. The equilibrium profiles fitted Langmuir and Freundlich isotherms, and kinetics favoured pseudo-second order model. The study demonstrated the practicability of the removal of alarming levels of cadmium and lead ions from industrial effluents.
A significant proportion of the worldwide population is of the elderly people living with chronic diseases that result in high health-care cost. To provide continuous health monitoring with minimal health-care cost, Wireless Body Sensor Networks (WBSNs) has been recently emerged as a promising technology. Depending on nature of sensory data, WBSNs might require a high level of Quality of Service (QoS) both in terms of delay and reliability during data reporting phase. In this paper, we propose a data-centric routing for intra WBSNs that adapts the routing strategy in accordance with the nature of data, temperature rise issue of the implanted bio-medical sensors due to electromagnetic wave absorption, and high and dynamic path loss caused by postural movement of human body and in-body wireless communication. We consider the network models both with and without relay nodes in our simulations. Due to the multi-facet routing strategy, the proposed data-centric routing achieves better performance in terms of delay, reliability, temperature rise, and energy consumption when compared with other state-of-the-art.
Heavy metal pollution, such as lead, can cause contamination of water resources and harm human life. Many techniques have been explored and utilized to overcome this problem, with adsorption technology being the most common strategies for water treatment. In this study, carbon nanofibers, polyacrylonitrile (PAN)/sago lignin (SL) carbon nanofibers (PAN/SL CNF) and PAN/SL activated carbon nanofibers (PAN/SL ACNF), with a diameter approximately 300 nm, were produced by electrospinning blends of polyacrylonitrile and sago lignin followed by thermal and acid treatments and used as adsorbents for the removal of Pb(II) ions from aqueous solutions. The incorporation of biodegradable and renewable SL in PAN/SL blends fibers produces the CNF with a smaller diameter than PAN only but preserves the structure of CNF. The adsorption of Pb(II) ions on PAN/SL ACNF was three times higher than that of PAN/SL CNF. The enhanced removal was due to the nitric acid treatment that resulted in the formation of surface oxygenated functional groups that promoted the Pb(II) ions adsorption. The best-suited adsorption conditions that gave the highest percentage removal of 67%, with an adsorption capacity of 524 mg/g, were 40 mg of adsorbent dosage, 125 ppm of Pb(II) solution, pH 5, and a contact time of 240 min. The adsorption data fitted the Langmuir isotherm and the pseudo-second-order kinetic models, indicating that the adsorption is a monolayer, and is governed by the availability of the adsorption sites. With the adsorption capacity of 588 mg/g, determined via the Langmuir isotherm model, the study demonstrated the potential of PAN/SL ACNFs as the adsorbent for the removal of Pb(II) ions from aqueous solution.
Recently, Artificial Intelligence (AI) has been used widely in medicine and health care sector. In machine learning, the classification or prediction is a major field of AI. Today, the study of existing predictive models based on machine learning methods is extremely active. Doctors need accurate predictions for the outcomes of their patients' diseases. In addition, for accurate predictions, timing is another significant factor that influences treatment decisions. In this paper, existing predictive models in medicine and health care have critically reviewed. Furthermore, the most famous machine learning methods have explained, and the confusion between a statistical approach and machine learning has clarified. A review of related literature reveals that the predictions of existing predictive models differ even when the same dataset is used. Therefore, existing predictive models are essential, and current methods must be improved.
Background: Studies have acknowledged that social media enables students to connect with and learn from experts from different ties available in the students' personal learning environment (PLE). Incorporating experts into formal learning activities such as scaffolding problem-solving tasks through social media, allows students to understand how experts solve real-world problems. However, studies that evaluate experts' problem-solving styles on social media in relation to the tie strength of the experts with the students are scarce in the extant literature. This study aimed to explore the problem-solving styles that the experts portrayed based on their ties with the students in problem-based learning (PBL) on Facebook. Methods: This study employed a simultaneous within-subject experimental design which was conducted in three closed Facebook groups with 12 final year management students, six business experts, and one instructor as the participants. The experts were invited by the students from the weak and strong ties in their PLE. Hinging on the Strength of Weak Ties Theory (Granovetter, 1973) and problem-solving styles (Selby et al., 2004), this study employed thematic analysis using the ATLAS.ti qualitative data analysis software to map the experts' comments on Facebook. Results: The experts from strong and weak ties who had a prior relationship with the students showed people preference style by being more sensitive to the students' learning needs and demonstrating firmer scaffolding compared to the weak ties' experts who had no prior relationship with the students. Regardless of the types of ties, all experts applied all manner of processing information and orientation to change but the degree of its applications are correlated with the working experience of the experts. Conclusion: The use of weak or strong ties benefited the students as it expedited their problem-solving tasks since the experts have unique expertise to offer depending on the problem-solving styles that they exhibited.
Graphene's potential as material for wearable, highly sensitive and robust sensor in various fields of technology has been widely investigated until now in order to capitalize on its unique intrinsic physical and chemical properties. In the wake of Covid-19 pandemic, it has been noticed that there are various potentials roles that can be fulfilled by graphene-based temperature, humidity and strain sensor, whose roles has not been widely explored to date. This paper takes the liberty to mainly highlight the progress layout and characterization technique for graphene-based sensor while including a brief discussion on the possible strategy of sensing data analysis that can be employed to minimize and prevent the risk of Covid-19 infection within a living community. While majority of the reported sensor is still in the in-progress status, its highlighted role in this work may provide a brief idea on how the ongoing research in graphene-based sensor may lead to the future implementation of the device for routine healthcare check-up and diagnostic point-care during and post-pandemic era. On the other hand, the sensitivity and response time data against working temperature, humidity and strain range that are provided could serve as a reference for benchmarking purpose, which certainly would help enthusiast in the development of a graphene-based sensor with a better performance for the future.
Femoral bone fracture is one of the main causes for the failure of hip arthroplasties (HA). Being subjected to abrupt and high impact forces in daily activities may lead to complex loading configuration such as bending and sideway falls. The objective of this study is to predict the risk of femoral bone fractures in total hip arthroplasty (THA) and resurfacing hip arthroplasty (RHA). A computed tomography (CT) based on finite element analysis was conducted to demonstrate damage formation in a three dimensional model of HAs. The inhomogeneous model of femoral bone was constructed from a 79 year old female patient with hip osteoarthritis complication. Two different femoral components were modeled with titanium alloy and cobalt chromium and inserted into the femoral bones to present THA and RHA models respectively. The analysis included six configurations, which exhibited various loading and boundary conditions, including axial compression, torsion, lateral bending, stance and two types of falling configurations. The applied hip loadings were normalized to body weight (BW) and accumulated from 1 BW to 3 BW. Predictions of damage formation in the femoral models were discussed as the resulting tensile failure as well as the compressive yielding and failure elements. The results indicate that loading directions can forecast the pattern and location of fractures at varying magnitudes of loading. Lateral bending configuration experienced the highest damage formation in both THA and RHA models. Femoral neck and trochanteric regions were in a common location in the RHA model in most configurations, while the predicted fracture locations in THA differed as per the Vancouver classification.
This paper proposes an emergency Traffic Adaptive MAC (eTA-MAC) protocol for WBANs based on Prioritization. The main advantage of the protocol is to provide traffic ranking through a Traffic Class Prioritization-based slotted-Carrier Sense Multiple Access/Collision Avoidance (TCP-CSMA/CA) scheme. The emergency traffic is handled through Emergency Traffic Class Provisioning-based slotted-CSMA/CA (ETCP-CSMA/CA) scheme. The emergency-based traffic adaptivity is provided through Emergency-based Traffic Adaptive slotted-CSMA/CA (ETA-CSMA/CA) scheme. The TCP-CSMA/CA scheme assigns a distinct, minimized and prioritized backoff period range to each traffic class in every backoff during channel access in Contention Access Period (CAP). The ETCP-CSMA/CA scheme delivers the sporadic emergency traffic that occurs at a single or multiple BMSN(s) instantaneously, with minimum delay and packet loss. It does this while being aware of normal traffic in the CAP. Then, the ETA-CSMA/CA scheme creates a balance between throughput and energy in the sporadic emergency situation with energy preservation of normal traffic BMSNs. The proposed protocol is evaluated using NS-2 simulator. The results indicate that the proposed protocol is better than the existing Medium Access Control (MAC) protocols by 86% decrease in packet delivery delay, 61% increase in throughput, and a 76% decrease in energy consumption.
An optical DNA biosensor based on fluorescence resonance energy transfer (FRET) utilizing synthesized quantum dot (QD) has been developed for the detection of specific-sequence of DNA for Ganoderma boninense, an oil palm pathogen. Modified QD that contained carboxylic groups was conjugated with a single-stranded DNA probe (ssDNA) via amide-linkage. Hybridization of the target DNA with conjugated QD-ssDNA and reporter probe labeled with Cy5 allows for the detection of related synthetic DNA sequence of Ganoderma boninense gene based on FRET signals. Detection of FRET emission before and after hybridization was confirmed through the capability of the system to produce FRET at 680 nm for hybridized sandwich with complementary target DNA. No FRET emission was observed for non-complementary system. Hybridization time, temperature and effect of different concentration of target DNA were studied in order to optimize the developed system. The developed biosensor has shown high sensitivity with detection limit of 3.55 × 10(-9) M. TEM results show that the particle size of QD varies in the range between 5 to 8 nm after ligand modification and conjugation with ssDNA. This approach is capable of providing a simple, rapid and sensitive method for detection of related synthetic DNA sequence of Ganoderma boninense.
Recently sink mobility has been exploited in numerous schemes to prolong the lifetime of wireless sensor networks (WSNs). Contrary to traditional WSNs where sensory data from sensor field is ultimately sent to a static sink, mobile sink-based approaches alleviate energy-holes issues thereby facilitating balanced energy consumption among nodes. In mobility scenarios, nodes need to keep track of the latest location of mobile sinks for data delivery. However, frequent propagation of sink topological updates undermines the energy conservation goal and therefore should be controlled. Furthermore, controlled propagation of sinks' topological updates affects the performance of routing strategies thereby increasing data delivery latency and reducing packet delivery ratios. This paper presents a taxonomy of various data collection/dissemination schemes that exploit sink mobility. Based on how sink mobility is exploited in the sensor field, we classify existing schemes into three classes, namely path constrained, path unconstrained, and controlled sink mobility-based schemes. We also organize existing schemes based on their primary goals and provide a comparative study to aid readers in selecting the appropriate scheme in accordance with their particular intended applications and network dynamics. Finally, we conclude our discussion with the identification of some unresolved issues in pursuit of data delivery to a mobile sink.
Wireless Body Sensor Networks (WBSNs) constitute a subset of Wireless Sensor Networks (WSNs) responsible for monitoring vital sign-related data of patients and accordingly route this data towards a sink. In routing sensed data towards sinks, WBSNs face some of the same routing challenges as general WSNs, but the unique requirements of WBSNs impose some more constraints that need to be addressed by the routing mechanisms. This paper identifies various issues and challenges in pursuit of effective routing in WBSNs. Furthermore, it provides a detailed literature review of the various existing routing protocols used in the WBSN domain by discussing their strengths and weaknesses.
Photocatalytic degradation of p-cresol was carried out using ZnO under UV irradiation. The amount of photocatalyst, concentration of p-cresol and pH were studied as variables. The residual concentration and mineralization of p-cresol was monitored using a UV-visible spectrophotometer and total organic carbon (TOC) analyzer, respectively. The intermediates were detected by ultra high pressure liquid chromatography (UPLC). The highest photodegradation of p-cresol was observed at 2.5 g/L of ZnO and 100 ppm of p-cresol. P-cresol photocatalytic degradation was favorable in the pH range of 6-9. The detected intermediates were 4-hydroxy-benzaldehyde and 4-methyl-1,2-benzodiol. TOC studies show that 93% of total organic carbon was removed from solution during irradiation time. Reusability shows no significant reduction in photocatalytic performance in photodegrading p-cresol.
The effective removal of o-cresol is currently both an environmental and economic challenge. ZnO is not only an efficient photocatalyst but is also cost effective, as its photoabsorption can extend from the ultraviolet (UV) to the visible range thereby allowing the use of inexpensive visible light sources, such as sunlight. The principal objective of the present work is to investigate the visible light-driven removal of o-cresol from aqueous solution in the presence of 1.0 wt% Mn-doped ZnO. To measure the efficiency ofphotodegradation, the variables studied included the amount ofphotocatalyst, concentration of o-cresol, pH and irradiation time. The concentration ofo-cresol and residual organic carbon was monitored using a UV-visible spectrophotometer, ultra high-pressure liquid chromatography and a total organic carbon analyser. The optimum conditions under which the photodegradation of o-cresol was most favourable corresponded to 1.5 g/l ZnO, 35 ppm o-cresol and pH 9. The ZnO-1 wt% Mn photoprocess has demonstrated reusability for more than three times, which warrants its scale-up from laboratory- to in industrial-scale application.
This work reports the synthesis and characterization of a hybrid molecularly imprinted polymer (MIP) membrane for removal of methylene blue (MB) in an aqueous environment. MB-MIP powders were hybridized into a polymer membrane (cellulose acetate (CA) and polysulfone (PSf)) after it was ground and sieved (using 90 µm sieve). MB-MIP membranes were prepared using a phase inversion process. The MB-MIP membranes were characterized using Fourier Transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscope (SEM). Parameters investigated for the removal of MB by using membrane MB-MIP include pH, effect of time, concentration of MB, and selectivity studies. Maximum sorption of MB by PSf-MB-MIP membranes and CA-MB-MIP membranes occurred at pH 10 and pH 12, respectively. The kinetic study showed that the sorption of MB by MB-MIP membranes (PSf-MB-MIP and CA-MB-MIP) followed a pseudo-second-order-model and the MB sorption isotherm can be described by a Freundlich isotherm model.
Silver nanoparticles (Ag-NPs) have been successfully prepared with simple and "green" synthesis method by reducing Ag(+) ions in aqueous gelatin media with and in the absence of glucose as a reducing agent. In this study, gelatin was used for the first time as a reducing and stabilizing agent. The effect of temperature on particle size of Ag-NPs was also studied. It was found that with increasing temperature the size of nanoparticles is decreased. It was found that the particle size of Ag-NPs obtained in gelatin solutions is smaller than in gelatin-glucose solutions, which can be related to the rate of reduction reaction. X-ray diffraction, ultraviolet-visible spectra, transmission electron microscopy, and atomic force microscopy revealed the formation of monodispersed Ag-NPs with a narrow particle size distribution.