Search results for: structural bone allograft

Authors: Yalçın Bozkurt

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Prediction models were developed for accurate prediction of bodyweight (BW) by using Digital Images of beef cattle body dimensions by Artificial Neural Networks (ANN). For this purpose, the animal data were collected at a private slaughter house and the digital images and the weights of each live animal were taken just before they were slaughtered and the body dimensions such as digital wither height (DJWH), digital body length (DJBL), digital body depth (DJBD), digital hip width (DJHW), digital hip height (DJHH) and digital pin bone length (DJPL) were determined from the images, using the data with 1069 observations for each traits. Then, prediction models were developed by ANN. Digital body measurements were analysed by ANN for body prediction and R2 values of DJBL, DJWH, DJHW, DJBD, DJHH and DJPL were approximately 94.32, 91.31, 80.70, 83.61, 89.45 and 70.56 % respectively. It can be concluded that in management situations where BW cannot be measured it can be predicted accurately by measuring DJBL and DJWH alone or both DJBD and even DJHH and different models may be needed to predict BW in different feeding and environmental conditions and breeds

Keywords: artificial neural networks, bodyweight, cattle, digital body measurements

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Authors: Khair Al-Deen Bsisu, Osama Mahmoud Abuzeid

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Significant technological advances have been achieved in the design and building construction of steel and glass in the last two decades. The metal glass support frame has been replaced by further sophisticated technological solutions, for example, the point fixed glazing systems. The minimization of the visual mass has reached extensive possibilities through the evolution of technology in glass production and the better understanding of the structural potential of glass itself, the technological development of bolted fixings, the introduction of the glazing support attachments of the glass suspension systems and the use for structural stabilization of cables that reduce to a minimum the amount of metal used. The variability of solutions of tension structures, allied to the difficulties related to geometric and material non-linear behavior, usually overrules the use of analytical solutions, letting numerical analysis as the only general approach to the design and analysis of tension structures. With the characteristics of low stiffness, lightweight, and small damping, tension structures are obviously geometrically nonlinear. In fact, analysis of cable truss is not only one of the most difficult nonlinear analyses because the analysis path may have rigid-body modes, but also a time consuming procedure. Non-linear theory allowing for large deflections is used. The flexibility of supporting members was observed to influence the stresses in the pane considerably in some cases. No other class of architectural structural systems is as dependent upon the use of digital computers as are tensile structures. Besides complexity, the process of design and analysis of tension structures presents a series of specificities, which usually lead to the use of special purpose programs, instead of general purpose programs (GPPs), such as ANSYS. In a special purpose program, part of the design know how is embedded in program routines. It is very probable that this type of program will be the option of the final user, in design offices. GPPs offer a range of types of analyses and modeling options. Besides, traditional GPPs are constantly being tested by a large number of users, and are updated according to their actual demands. This work discusses the use of ANSYS for the analysis and design of tension structures, such as cable truss structures under wind and gravity loadings. A model to describe the glass panels working in coordination with the cable truss was proposed. Under the proposed model, a FEM model of the glass panels working in coordination with the cable truss was established.

Keywords: Glass Construction material, Facades, Finite Element, Pre-Tensioned Cable Truss

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Authors: Nur Fathin Alia Che Wahab, Thirumulu Ponnuraj Kannan, Zuliani Mahmood, Ismail Ab. Rahman, Hanafi Ismail

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Locally produced Biphasic Calcium Phosphate (BCP) consists of hydroxyapatite (HA) and β-tricalcium phosphate (β-TCP) which is a promising material for dentin and bone regeneration as well as in tissue engineering applications. The study was carried out to investigate the mutagenic effect of locally produced BCP using Ames test. Mutagenicity was evaluated with and without the addition of metabolic activation system (S9). This study was performed on Salmonella typhimurium TA98, TA102, TA1537, and TA1538 strains using preincubation assay method. The doses tested were 5000, 2500, 1250, 625, 313 µg/plate. Negative and positive controls were also included. The bacteria were incubated for 48 hours at 37 ± 0.5 °C. Then, the revertant colonies were counted. Data obtained were evaluated using non-statistical method. The mean number of revertant colonies in strains with and without S9 mix treated with locally produced BCP was less than double when compared to negative control for all the tested concentrations. The results from this study indicate that the locally produced BCP is non-mutagenic under the present test conditions.

Keywords: ames test, biphasic calcium phosphate, dentin regeneration, mutagenicity

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Authors: Sarah Mueller-Saegebrecht, André Brendler

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Business model innovation (BMI) as an intentional change of an existing business model (BM) or the design of a new BM is essential to a firm's development in dynamic markets. The relevance of BMI is also evident in the ongoing COVID-19 pandemic, in which start-ups, in particular, are affected by limited access to resources. However, first studies also show that they react faster to the pandemic than established firms. A strategy to successfully handle such threatening dynamic changes represents BMI. Entrepreneurship literature shows how and when firms should utilize BMI in times of crisis and which barriers one can expect during the BMI process. Nevertheless, research merging BMI barriers and crises is still underexplored. Specifically, further knowledge about antecedents and the effect of moderators on the BMI process is necessary for advancing BMI research. The addressed research gap of this study is two-folded: First, foundations to the subject on how different crises impact BM change intention exist, yet their analysis lacks the inclusion of barriers. Especially, entrepreneurship literature lacks knowledge about the individual perception of BMI barriers, which is essential to predict managerial reactions. Moreover, internal BMI barriers have been the focal point of current research, while external BMI barriers remain virtually understudied. Second, to date, BMI research is based on qualitative methodologies. Thus, a lack of quantitative work can specify and confirm these qualitative findings. By focusing on the crisis context, this study contributes to BMI literature by offering a first quantitative attempt to embed BMI barriers into a structural equation model. It measures managers' perception of BMI development and implementation barriers in the BMI process, asking the following research question: How does a manager's perception of BMI barriers influence BMI development and implementation in times of crisis? Two distinct research streams in economic literature explain how individuals react when perceiving a threat. "Prospect Theory" claims that managers demonstrate risk-seeking tendencies when facing a potential loss, and opposing "Threat-Rigidity Theory" suggests that managers demonstrate risk-averse behavior when facing a potential loss. This study quantitively tests which theory can best predict managers' BM reaction to a perceived crisis. Out of three in-depth interviews in the German chemical industry, 60 past BMIs were identified. The participating start-up managers gave insights into their start-up's strategic and operational functioning. After, each interviewee described crises that had already affected their BM. The participants explained how they conducted BMI to overcome these crises, which development and implementation barriers they faced, and how severe they perceived them, assessed on a 5-point Likert scale. In contrast to current research, results reveal that a higher perceived threat level of a crisis harms BM experimentation. Managers seem to conduct less BMI in times of crisis, whereby BMI development barriers dampen this relation. The structural equation model unveils a mediating role of BMI implementation barriers on the link between the intention to change a BM and the concrete BMI implementation. In conclusion, this study confirms the threat-rigidity theory.

Keywords: barrier perception, business model innovation, business model innovation barriers, crises, prospect theory, start-ups, structural equation model, threat-rigidity theory

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Authors: Sayyed-javad Ziaolhagh, Ali-Reza Saadatifar

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Introduction: Athletes frequently perform anabolic steroid resistance exercise, but the effects of medical doses and abuse along with resistance exercise on structural damage to the Pancreases and also jujube extract are unknown. The aim of this study was to investigate the effects of resistance training on body weight and hip fractures induced by boldenone injection in male rats. Materials and methods: In this experimental study, 30 male Wistar rats aged 8-12 weeks (weight 202±9.34 g) were randomly divided into five groups: control, boldenone, extract of iujuba+boldenone, boldenone+resistance training and boldenone+resistance training +extract of jujuba. The resistance training program included climbing the ladder for 8 weeks, 3 days a week, 1 session training in a day and each session consisted of the 3 sets and 5 repetitions. Injection was conducted in depth in the hamstring once a week on an appointed day. After anesthesia, autopsy was performed, and the cardiac tissue was isolated. Results: Results showed that boldenone caused tissue damage, congestion, and nuclei unclear and diffuse. In the group "resistance + Boldenone," The Pancreases tissue showed a high degree of hyperemia, and the muscle cells were somewhat abnormal. In boldenone + jujube, the appearance of the tissue was normal, and the rejuvenating effect was visible. Conclusion: Boldenone appears to cause structural damage to the Pancreases tissue. Strength training with Jujube Extract can reduce part of the pancreatic system disorders (necrosis and inflammation) caused by anabolic steroid use.

Keywords: boldenone, Jujube extract, pancreases tissue, resistance training

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Authors: Sweta Das

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This case report is a 15-year-old male who presented with painless unilateral vision loss from left optic nerve compression due to juvenile nasopharyngeal angiofibroma. JNA is a rare, benign neoplasm that causes intracranial and intraorbital bone destruction and extends aggressively into surrounding soft tissues. It accounts for <1% of all head and neck tumors, is predominantly found in pediatric males and tends to affect indigenous population disproportionately. The most common presenting symptom for JNA is epistaxis and nasal obstruction. However, it can invade orbit, chiasm and pituitary gland, causing loss of vision and field. Visual acuity and function near normalized following surgical excision. Optometry plays an important role in the diagnosis and co-management of JNA with optic nerve compression by closely monitoring afferent optic nerve function and structure, and extraocular motility. Visual function and acuity in patients with short-term compressive neuropathy may drastically improve following surgical resection as this case demonstrates.

Keywords: orbital mass, painless monocular vision loss, compressive optic neuropathy, pediatric tumor

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Authors: Eray Ozbek, Ilker Kalkan, S. Oguzhan Akbas, Sabahattin Aykac

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The contribution of the infill walls to the overall earthquake response of a structure is limited and this contribution is generally ignored in the analyses. Strengthening of the infill walls through different techniques has been and is being studied extensively in the literature to increase this limited contribution and the ductilities and energy absorption capacities of the infill walls to create non-structural components where the earthquake-induced energy can be absorbed without damaging the bearing components of the structural frame. The present paper summarizes an extensive research project dedicated to investigate the effects of strengthening the brick infill walls of a reinforced concrete (RC) frame on its lateral earthquake response. Perforated steel plates were used in strengthening due to several reasons, including the ductility and high deformation capacity of these plates, the fire resistant, recyclable and non-cancerogenic nature of mild steel, and the ease of installation and removal of the plates to the wall with the help of anchor bolts only. Furthermore, epoxy, which increases the cost and amount of labor of the strengthening process, is not needed in this technique. The individual behavior of the strengthened walls under monotonic diagonal and lateral reversed cyclic loading was investigated within the scope of the study. Upon achieving brilliant results, RC frames with strengthened infill walls were tested and are being tested to examine the influence of this strengthening technique on the overall behavior of the RC frames. Tests on the wall and frame specimens indicated that the perforated steel plates contribute to the lateral strength, rigidity, ductility and energy absorption capacity of the wall and the infilled frame to a major extent.

Keywords: infill wall, strengthening, external plate, earthquake behavior

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Authors: Khin Thanda Win, Chunying Zhang, Sanghyeob Lee

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Mildew resistance locus o (Mlo), a plant-specific gene family with seven-transmembrane (TM), plays an important role in plant resistance to powdery mildew (PM). PM caused by Podosphaera xanthii is a widespread plant disease and probably represents the major fungal threat for many Cucurbits. The recent Cucurbita maxima genome sequence data provides an opportunity to identify and characterize the MLO gene family in this species. Total twenty genes (designated CmaMLO1 through CmaMLO20) have been identified by using an in silico cloning method with the MLO gene sequences of Cucumis sativus, Cucumis melo, Citrullus lanatus and Cucurbita pepo as probes. These CmaMLOs were evenly distributed on 15 chromosomes of 20 C. maxima chromosomes without any obvious clustering. Multiple sequence alignment showed that the common structural features of MLO gene family, such as TM domains, a calmodulin-binding domain and 30 important amino acid residues for MLO function, were well conserved. Phylogenetic analysis of the CmaMLO genes and other plant species reveals seven different clades (I through VII) and only clade IV is specific to monocots (rice, barley, and wheat). Phylogenetic and structural analyses provided preliminary evidence that five genes belonged to clade V could be the susceptibility genes which may play the importance role in PM resistance. This study is the first comprehensive report on MLO genes in C. maxima to our knowledge. These findings will facilitate the functional analysis of the MLOs related to PM susceptibility and are valuable resources for the development of disease resistance in pumpkin.

Keywords: Mildew resistance locus o (Mlo), powdery mildew, phylogenetic relationship, susceptibility genes

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Authors: Mohammed Alanazi, Dimitrios Tsagdis

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Established Business Excellence Models (BEMs), like the Malcolm Baldrige National Quality Award (MBNQA) model and the European Foundation for Quality Management (EFQM) model, have been adopted by firms all over the world. They exist alongside more recent country-specific BEMs; e.g. the Australian, Canadian, China, New Zealand, Singapore, and Taiwan quality awards that although not as widespread as MBNQA and EFQM have nonetheless strong national followings. Regardless of any differences in their following or prestige, the emergence and development of all BEMs have been shaped both by their local context (e.g. underlying socio-economic dynamics) as well as by global best practices. Besides such similarities, that render them into objects (i.e. models) of the same class (i.e. BEMs), BEMs exhibit non-trivial differences in their criteria, relations, and emphasis. Given the evolution of BEMs (e.g. the MBNQA underwent seven evolutions since its inception in 1987 while the EFQM five since 1993), it is unsurprising that comparative studies of their validity are few and far in between. This poses challenges for practitioners and policy makers alike; as it is not always clear which BEM is to be preferred or better fitting to a particular context. Especially, in contexts that differ substantially from the original context of BEM development. This paper aims to fill this gap by presenting a research design and measurement model for comparing BEMs using quantitative methods (e.g. structural equations). Three BEMs will be focused upon in particular for illustration purposes; the MBNQA, the EFQM, and the King Abdul Aziz Quality Award (KAQA) model. They have been selected so to reflect the two established and widely spread traditions as well as a more recent context-specific arrival promising a better fit.

Keywords: Baldrige, business excellence, European Foundation for Quality Management, Structural Equation Model, total quality management

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Authors: Larisa Gheber

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Mitosis is an essential process by which duplicated genetic information is transmitted from mother to daughter cells. Incorrect chromosome segregation during mitosis can lead to genetic diseases, chromosome instability and cancer. This process is mediated by a dynamic microtubule-based intracellular structure, the mitotic spindle. One of the major factors that govern the mitotic spindle dynamics are the kinesin-5 biological nano motors that were believed to move unidirectionally on the microtubule filaments, using ATP hydrolysis, thus performing essential functions in mitotic spindle dynamics. Surprisingly, several reports from our and other laboratories have demonstrated that some kinesin-5 motors are bi-directional: they move in minus-end direction on the microtubules as single-molecules and can switch directionality under a number of conditions. These findings broke a twenty-five-years old dogma regarding kinesin directionality (1, 2). The mechanism of this bi-directional motility and its physiological significance remain unclear. To address this unresolved problem, we apply an interdisciplinary approach combining live cell imaging, biophysical single molecule, and structural experiments to examine the activity of these motors and their mutated variants in vivo and in vitro. Our data shows that factors such as protein phosphorylation (3, 4), motor clustering on the microtubules (5, 6) and structural elements (7, 8) regulate the bi-directional motility of kinesin motors. We also show, using Cryo-EM, that bi-directional kinesin motors obtain non-canonical microtubule binding, which is essential to their special motile properties and intracellular functions. We will discuss the implication of these findings to mechanism bi-directional motility and physiological roles in mitosis.

Keywords: mitosis, cancer, kinesin, microtubules, biochemistry, biophysics

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Authors: Ming-Hsiang Shih, Wen-Pei Sung, Shih-Heng Tung

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Semi-active control system for structure under excitation of earthquake provides with the characteristics of being adaptable and requiring low energy. DSHD (Displacement Semi-Active Hydraulic Damper) was developed by our research team. Shake table test results of this DSHD installed in full scale test structure demonstrated that this device brought its energy-dissipating performance into full play for test structure under excitation of earthquake. The objective of this research is to develop a new AIC (Active Interaction Control Device) and apply shake table test to perform its dissipation of energy capability. This new proposed AIC is converting an improved DSHD (Displacement Semi-Active Hydraulic Damper) to AIC with the addition of an accumulator. The main concept of this energy-dissipating AIC is to apply the interaction function of affiliated structure (sub-structure) and protected structure (main structure) to transfer the input seismic force into sub-structure to reduce the structural deformation of main structure. This concept is tested using full-scale multi-degree of freedoms test structure, installed with this proposed AIC subjected to external forces of various magnitudes, for examining the shock absorption influence of predictive control, stiffness of sub-structure, synchronous control, non-synchronous control and insufficient control position. The test results confirm: (1) this developed device is capable of diminishing the structural displacement and acceleration response effectively; (2) the shock absorption of low precision of semi-active control method did twice as much seismic proof efficacy as that of passive control method; (3) active control method may not exert a negative influence of amplifying acceleration response of structure; (4) this AIC comes into being time-delay problem. It is the same problem of ordinary active control method. The proposed predictive control method can overcome this defect; (5) condition switch is an important characteristics of control type. The test results show that synchronism control is very easy to control and avoid stirring high frequency response. This laboratory results confirm that the device developed in this research is capable of applying the mutual interaction between the subordinate structure and the main structure to be protected is capable of transforming the quake energy applied to the main structure to the subordinate structure so that the objective of minimizing the deformation of main structural can be achieved.

Keywords: DSHD (Displacement Semi-Active Hydraulic Damper), AIC (Active Interaction Control Device), shake table test, full scale structure test, sub-structure, main-structure

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Authors: Wajih Abbassi, Zouhaier Ben Khelifa

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The present research points towards the empirical validation of three options valuation models, the ad-hoc Black-Scholes model as proposed by Berkowitz (2001), the constant elasticity of variance model of Cox and Ross (1976) and the Kou jump-diffusion model (2002). Our empirical analysis has been conducted on a sample of 26,974 options written on three indexes, the S&P 500, Nasdaq 100 and the Russell 2000 that were negotiated during the year 2007 just before the sub-prime crisis. We start by presenting the theoretical foundations of the models of interest. Then we use the technique of trust-region-reflective algorithm to estimate the structural parameters of these models from cross-section of option prices. The empirical analysis shows the superiority of the Kou jump-diffusion model. This superiority arises from the ability of this model to portray the behavior of market participants and to be closest to the true distribution that characterizes the evolution of these indices. Indeed the double-exponential distribution covers three interesting properties that are: the leptokurtic feature, the memory less property and the psychological aspect of market participants. Numerous empirical studies have shown that markets tend to have both overreaction and under reaction over good and bad news respectively. Despite of these advantages there are not many empirical studies based on this model partly because probability distribution and option valuation formula are rather complicated. This paper is the first to have used the technique of nonlinear curve-fitting through the trust-region-reflective algorithm and cross-section options to estimate the structural parameters of the Kou jump-diffusion model.

Keywords: jump-diffusion process, Kou model, Leptokurtic feature, trust-region-reflective algorithm, US index options

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Authors: Syed Basit Ali Shah Bukhari, Yan Qiang, Saad Abdul Rauf, Syed Saqlaina Bukhari

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Text Classification is the methodology to classify any given text into the respective category from a given set of categories. It is highly important and vital to use proper set of pre-processing , feature selection and classification techniques to achieve this purpose. In this paper we have used different ensemble techniques along with variance in feature selection parameters to see the change in overall accuracy of the result and also on some other individual class based features which include precision value of each individual category of the text. After subjecting our data through pre-processing and feature selection techniques , different individual classifiers were tested first and after that classifiers were combined to form ensembles to increase their accuracy. Later we also studied the impact of decreasing the classification categories on over all accuracy of data. Text classification is highly used in sentiment analysis on social media sites such as twitter for realizing people’s opinions about any cause or it is also used to analyze customer’s reviews about certain products or services. Opinion mining is a vital task in data mining and text categorization is a back-bone to opinion mining.

Keywords: Natural Language Processing, Ensemble Classifier, Bagging Classifier, AdaBoost

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Authors: Lavanya Annadi, Fahimeh Jafari

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Transportation brings immense benefits to society, but it also has its costs. Costs include such as the cost of infrastructure, personnel and equipment, but also the loss of life and property in traffic accidents on the road, delays in travel due to traffic congestion and various indirect costs in terms of air transport. More research has been done to identify the various factors that affect road accidents, such as road infrastructure, traffic, sociodemographic characteristics, land use, and the environment. The aim of this research is to predict the probabilistic crash prediction of vehicles using machine learning due to natural and structural reasons by excluding spontaneous reasons like overspeeding etc., in the United States. These factors range from weather factors, like weather conditions, precipitation, visibility, wind speed, wind direction, temperature, pressure, and humidity to human made structures like road structure factors like bump, roundabout, no exit, turning loop, give away, etc. Probabilities are dissected into ten different classes. All the predictions are based on multiclass classification techniques, which are supervised learning. This study considers all crashes that happened in all states collected by the US government. To calculate the probability, multinomial expected value was used and assigned a classification label as the crash probability. We applied three different classification models, including multiclass Logistic Regression, Random Forest and XGBoost. The numerical results show that XGBoost achieved a 75.2% accuracy rate which indicates the part that is being played by natural and structural reasons for the crash. The paper has provided in-deep insights through exploratory data analysis.

Keywords: road safety, crash prediction, exploratory analysis, machine learning

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Authors: Nancy Mackin

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Historically, architects from Aalto to Gaudi to Wright have looked to the architectural knowledge of long-resident peoples for forms and structural principles specifically adapted to the regional climate, geology, materials availability, and culture. In this research, structures traditionally built by Inuit peoples in a remote region of the Canadian high Arctic provides a folio of architectural ideas that are increasingly relevant during these times of escalating carbon emissions and climate change. ‘Green architecture from the Thawing Arctic’ researches, draws, models, and reconstructs traditional buildings of Inuit (Eskimo) peoples in three remote, often inaccessible Arctic communities. Structures verified in pre-contact oral history and early written history are first recorded in architectural drawings, then modeled and, with the participation of Inuit young people, local scientists, and Elders, reconstructed as emergency shelters. Three full-sized building types are constructed: a driftwood and turf-clad A-frame (spring/summer); a stone/bone/turf house with inwardly spiraling walls and a fan-shaped floor plan (autumn); and a parabolic/catenary arch-shaped dome from willow, turf, and skins (autumn/winter). Each reconstruction is filmed and featured in a short video. Communities found that the reconstructed buildings and the method of involving young people and Elders in the reconstructions have on-going usefulness, as follows: 1) The reconstructions provide emergency shelters, particularly needed as climate change worsens storms, floods, and freeze-thaw cycles and scientists and food harvesters who must work out of the land become stranded more frequently; 2) People from the communities re-learned from their Elders how to use materials from close at hand to construct impromptu shelters; 3) Forms from tradition, such as windbreaks at entrances and using levels to trap warmth within winter buildings, can be adapted and used in modern community buildings and housing; and 4) The project initiates much-needed educational and employment opportunities in the applied sciences (engineering and architecture), construction, and climate change monitoring, all offered in a culturally-responsive way. Elders, architects, scientists, and young people added innovations to the traditions as they worked, thereby suggesting new sustainable, culturally-meaningful building forms and materials combinations that can be used for modern buildings. Adding to the growing interest in bio-mimicry, participants looked at properties of Arctic and subarctic materials such as moss (insulation), shrub bark (waterproofing), and willow withes (parabolic and catenary arched forms). ‘Green Architecture from the Thawing Arctic’ demonstrates the effective, useful architectural oeuvre of a resilient northern people. The research parallels efforts elsewhere in the world to revitalize long-resident peoples’ architectural knowledge, in the interests of designing sustainable buildings that reflect culture, heritage, and identity.

Keywords: architectural culture and identity, climate change, forms from nature, Inuit architecture, locally sourced biodegradable materials, traditional architectural knowledge, traditional Inuit knowledge

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Authors: Sayed M. Soleimani, Nader H. Ghareeb, Nourhan H. Shaker, Muhammad B. Siddiqui

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Honeycomb sandwich panels have been widely used as protective structural elements against blast loading. The main advantages of these panels include their light weight due to the presence of voids, as well as their energy absorption capability. Terrorist activities have imposed new challenges to structural engineers to design protective measures for vital structures. Since blast loading is not usually considered in the load combinations during the design process of a structure, researchers around the world have been motivated to study the behavior of potential elements capable of resisting sudden loads imposed by the detonation of explosive materials. One of the best candidates for this objective is the honeycomb sandwich panel. Studying the effects of explosive materials on the panels requires costly and time-consuming experiments. Moreover, these type of experiments need permission from defense organizations which can become a hurdle. As a result, modeling and simulation using an appropriate tool can be considered as a good alternative. In this research work, the finite element package ABAQUS® is used to study the behavior of hexagonal and squared honeycomb steel sandwich panels under the explosive effects of different amounts of trinitrotoluene (TNT). The results of finite element modeling of a specific honeycomb configuration are initially validated by comparing them with the experimental results from literature. Afterwards, several configurations including different geometrical properties of the honeycomb wall are investigated and the results are compared with the original model. Finally, the effectiveness of the core shape and wall thickness are discussed, and conclusions are made.

Keywords: Abaqus, blast loading, finite element modeling, steel honeycomb sandwich panel

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Authors: Behrang Tavousi Tehrani, Mohammad-Zaman Kabir

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Shape memory alloys (SMA) are often implemented in smart structures as the active components. Their ability to recover large displacements has been used in many applications, including structural stability/response enhancement and active structural acoustic control. SMA wires or fibers can be embedded with composite cylinders to increase their critical buckling load, improve their load-deflection behavior, and reduce the radial deflections under various thermo-mechanical loadings. This paper presents a semi-analytical investigation on the non-linear load-deflection response of SMA-reinforced composite circular cylindrical shells. The cylinder shells are under uniform external pressure load. Based on first-order shear deformation shell theory (FSDT), the equilibrium equations of the structure are derived. One-dimensional simplified Brinson’s model is used for determining the SMA recovery force due to its simplicity and accuracy. Airy stress function and Galerkin technique are used to obtain non-linear load-deflection curves. The results are verified by comparing them with those in the literature. Several parametric studies are conducted in order to investigate the effect of SMA volume fraction, SMA pre-strain value, and SMA activation temperature on the response of the structure. It is shown that suitable usage of SMA wires results in a considerable enhancement in the load-deflection response of the shell due to the generation of the SMA tensile recovery force.

Keywords: airy stress function, cylindrical shell, Galerkin technique, load-deflection curve, recovery stress, shape memory alloy

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Authors: N. O. Muniz, F. A. Vechietti, L. Treccani, K. Rezwan, Luis Alberto dos Santos

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Developing new technologies in the manufacture of biomaterials is a major challenge for researchers in the tissue engineering area. Many in vitro and in vivo studies have revealed the significance of the porous structure of the biomaterials on the promotion of bone ingrowth. The use of Rapid Prototyping in the manufacture of ceramics in the biomedical area has increased in recent years and few studies are conducted on obtaining alumina pieces. The aim of this work was the study of alumina pieces obtained by 3D printing and uniaxial dry pressing (DP) in order to evaluate porosity achieved by this two different techniques. Also, the influence of the powder drying process was determined. The row alumina powders were drying by freeze drying and oven. Apparent porosity, apparent density, retraction after thermal treatment were evaluated. The porosity values obtained by DP, regardless of method of drying powders, were much lower than those obtained by RP as expected. And for the prototyped samples, the method of powder drying significantly influenced porosities, reached 48% for drying oven versus 65% for freeze-drying. Therefore, the method of 3D printing, using different powder drying, allows a better control over the porosity.

Keywords: rapid prototyping, freeze-drying, porosity, alumina

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Authors: Przemyslaw Nogly, Tobias Weinert, Daniel James, Sergio Carbajo, Dmitry Ozerov, Antonia Furrer, Dardan Gashi, Veniamin Borin, Petr Skopintsev, Kathrin Jaeger, Karol Nass, Petra Bath, Robert Bosman, Jason Koglin, Matthew Seaberg, Thomas Lane, Demet Kekilli, Steffen Brünle, Tomoyuki Tanaka, Wenting Wu, Christopher Milne, Thomas A. White, Anton Barty, Uwe Weierstall, Valerie Panneels, Eriko Nango, So Iwata, Mark Hunter, Igor Schapiro, Gebhard Schertler, Richard Neutze, Jörg Standfuss

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Ultrafast isomerization of retinal is the primary step in a range of photoresponsive biological functions including vision in humans and ion-transport across bacterial membranes. We studied the sub-picosecond structural dynamics of retinal isomerization in the light-driven proton pump bacteriorhodopsin using an X-ray laser. Twenty snapshots with near-atomic spatial and temporal resolution in the femtosecond regime show how the excited all-trans retinal samples conformational states within the protein binding pocket prior to passing through a highly-twisted geometry and emerging in the 13-cis conformation. The aspartic acid residues and functional water molecules in proximity of the retinal Schiff base respond collectively to formation and decay of the initial excited state and retinal isomerization. These observations reveal how the protein scaffold guides this remarkably efficient photochemical reaction.

Keywords: bacteriorhodopsin, free-electron laser, retinal isomerization mechanism, time-resolved crystallography

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

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Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by density-based time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., mean value, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one class classifier (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, a new anomaly detector strategy is proposed, namely one class classifier neural network two (OCCNN2), which exploit the classification capability of standard classifiers in an anomaly detection problem, finding the standard class (the boundary of the features space in normal operating conditions) through a two-step approach: coarse and fine boundary estimation. The coarse estimation uses classics OCC techniques, while the fine estimation is performed through a feedforward neural network (NN) trained that exploits the boundaries estimated in the coarse step. The detection algorithms vare then compared with known methods based on principal component analysis (PCA), kernel principal component analysis (KPCA), and auto-associative neural network (ANN). In many cases, the proposed solution increases the performance with respect to the standard OCC algorithms in terms of F1 score and accuracy. In particular, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 96% with the proposed method.

Keywords: anomaly detection, frequencies selection, modal analysis, neural network, sensor network, structural health monitoring, vibration measurement

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Authors: Sara Przetocka, Krzysztof Żak, Grzegorz Dubin, Tadeusz Holak

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Toll-like receptors (TLRs) play central role in the innate immune response and inflammation by recognizing pathogen-associated molecular patterns (PAMPs). A fundamental basis of TLR signalling is dependent upon the recruitment and association of adaptor molecules that contain the structurally conserved Toll/interleukin-1 receptor (TIR) domain. MyD88 (myeloid differentiation primary response gene 88) is the universal adaptor for TLRs and cooperates with Mal (MyD88 adapter-like protein, also known as TIRAP) in TLR4 response which is predominantly used in inflammation, host defence and carcinogenesis. Up to date two possible models of MyD88, Mal and TLR4 interactions have been proposed. The aim of our studies is to confirm or abolish presented models and accomplish the full structural characterisation of TIR domains interaction. Using molecular cloning methods we obtained several construct of MyD88 and Mal TIR domain with GST or 6xHis tag. Gel filtration method as well as pull-down analysis confirmed that recombinant TIR domains from MyD88 and Mal are binding in complexes. To examine whether obtained complexes are homo- or heterodimers we carried out cross-linking reaction of TIR domains with BS3 compound combined with mass spectrometry. To investigate which amino acid residues are involved in this interaction the NMR titration experiments were performed. 15N MyD88-TIR solution was complemented with non-labelled Mal-TIR. The results undoubtedly indicate that MyD88-TIR interact with Mal-TIR. Moreover 2D spectra demonstrated that simultaneously Mal-TIR self-dimerization occurs which is necessary to create proper scaffold for Mal-TIR and MyD88-TIR interaction. Final step of this study will be crystallization of MyD88 and Mal TIR domains complex. This crystal structure and characterisation of its interface will have an impact in understanding the TLR signalling pathway and possibly will be used in development of new anti-cancer treatment.

Keywords: cancer, MyD88, TIR domains, Toll-like receptors

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Authors: Azin Shakibabarough, Mojtaba Valinejadshoubi, Ashutosh Bagchi

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Catastrophic bridge failure happens due to the lack of inspection, lack of design and extreme events like flooding, an earthquake. Bridge Management System (BMS) is utilized to diminish such an accident with proper design and frequent inspection. Visual inspection cannot detect any subsurface defects, so using Non-Destructive Evaluation (NDE) techniques remove these barriers as far as possible. Among all NDE techniques, Ground Penetrating Radar (GPR) has been proved as a highly effective device for detecting internal defects in a reinforced concrete bridge deck. GPR is used for detecting rebar location and rebar corrosion in the reinforced concrete deck. GPR profile is composed of hyperbola series in which sound hyperbola denotes sound rebar and blur hyperbola or signal attenuation shows corroded rebar. Interpretation of GPR images is implemented by numerical analysis or visualization. Researchers recently found that interpretation through visualization is more precise than interpretation through numerical analysis, but visualization is time-consuming and a highly subjective process. Automating the interpretation of GPR image through visualization can solve these problems. After interpretation of all scans of a bridge, condition assessment is conducted based on the generated corrosion map. However, this such a condition assessment is not objective and precise. Condition assessment based on structural integrity and strength parameters can make it more objective and precise. The main purpose of this study is to present an automated interpretation method of a reinforced concrete bridge deck through a visualization technique. In the end, the combined analysis of the structural condition in a bridge is implemented.

Keywords: bridge condition assessment, ground penetrating radar, GPR, NDE techniques, visualization

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Authors: Gabrielle Robertson, Matthew Downs, Joseph Dagher

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Iron deposition in the brain has been linked with a host of neurological disorders such as Alzheimer’s, Parkinson’s, and Multiple Sclerosis. While some treatment options exist, there are no objective measurement tools that allow for the monitoring of iron levels in the brain in vivo. An emerging Magnetic Resonance Imaging (MRI) method has been recently proposed to deduce iron concentration through quantitative measurement of magnetic susceptibility. This is a multi-step process that involves repeated modeling of physical processes via approximate numerical solutions. For example, the last two steps of this Quantitative Susceptibility Mapping (QSM) method involve I) mapping magnetic field into magnetic susceptibility and II) mapping magnetic susceptibility into iron concentration. Process I involves solving an ill-posed inverse problem by using regularization via injection of prior belief. The end result from Process II highly depends on the model used to describe the molecular content of each voxel (type of iron, water fraction, etc.) Due to these factors, the accuracy and repeatability of QSM have been an active area of research in the MRI and medical imaging community. This work aims to estimate iron concentration in the brain via a single step. A synthetic numerical model of the human head was created by automatically and manually segmenting the human head on a high-resolution grid (640x640x640, 0.4mm³) yielding detailed structures such as microvasculature and subcortical regions as well as bone, soft tissue, Cerebral Spinal Fluid, sinuses, arteries, and eyes. Each segmented region was then assigned tissue properties such as relaxation rates, proton density, electromagnetic tissue properties and iron concentration. These tissue property values were randomly selected from a Probability Distribution Function derived from a thorough literature review. In addition to having unique tissue property values, different synthetic head realizations also possess unique structural geometry created by morphing the boundary regions of different areas within normal physical constraints. This model of the human brain is then used to create synthetic MRI measurements. This is repeated thousands of times, for different head shapes, volume, tissue properties and noise realizations. Collectively, this constitutes a training-set that is similar to in vivo data, but larger than datasets available from clinical measurements. This 3D convolutional U-Net neural network architecture was used to train data-driven Deep Learning models to solve for iron concentrations from raw MRI measurements. The performance was then tested on both synthetic data not used in training as well as real in vivo data. Results showed that the model trained on synthetic MRI measurements is able to directly learn iron concentrations in areas of interest more effectively than other existing QSM reconstruction methods. For comparison, models trained on random geometric shapes (as proposed in the Deep QSM method) are less effective than models trained on realistic synthetic head models. Such an accurate method for the quantitative measurement of iron deposits in the brain would be of important value in clinical studies aiming to understand the role of iron in neurological disease.

Keywords: magnetic resonance imaging, MRI, iron deposition, machine learning, quantitative susceptibility mapping

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Authors: Shivani Singla, Om Prakash Pandey, Gopi Sharma

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Metallic nanoparticle doped glasses has lead to rapid development in the field of optics. Large third order non-linearity, ultrafast time response, and a wide range of resonant absorption frequencies make these metallic nanoparticles more important in comparison to their bulk material. All these properties are highly dependent upon the size, shape, and surrounding environment of the nanoparticles. In a quest to find a suitable material for optical applications, several efforts have been devoted to improve the properties of such glasses in the past. In the present study, bismuth borate glass doped with different size gold nanoparticles (AuNPs) has been prepared using the conventional melt-quench technique. Synthesized glasses are characterized by X-ray diffraction (XRD) and Fourier Transformation Infrared spectroscopy (FTIR) to observe the structural modification in the glassy matrix with the variation in the size of the AuNPs. Glasses remain purely amorphous in nature even after the addition of AuNPs, whereas FTIR proposes that the main structure contains BO₃ and BO₄ units. Field emission scanning electron microscopy (FESEM) confirms the existence and variation in the size of AuNPs. Differential thermal analysis (DTA) depicts that prepared glasses are thermally stable and are highly suitable for the fabrication of optical fibers. The nonlinear optical parameters (nonlinear absorption coefficient and nonlinear refractive index) are calculated out by using the Z-scan technique with a Ti: sapphire laser at 800 nm. It has been concluded that the size of the nanoparticles highly influences the structural thermal and optical properties system.

Keywords: bismuth borate glass, different size, gold nanoparticles, nonlinearity

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Authors: Sanjai Sureshkumar, Sathish G. Kumar, P. V. V. Sathyanarayana

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For e-gear drivetrain, the transmission error and the resulting variation in mesh stiffness is one of the main source of excitation in High performance Electric Vehicle. These vibrations are transferred through the shaft to the bearings and then to the e-Gear drive housing eventually radiating noise. A parametrical model developed in 1-D system simulation by optimizing the micro and macro geometry along with bearing properties and oil filtration to achieve least transmission error and high contact ratio. Histogram analysis is performed to condense the actual road load data into condensed duty cycle to find the bearing forces. The structural vibration generated by these forces will be simulated in a nonlinear solver obtaining the normal surface velocity of the housing and the results will be carried forward to Acoustic software wherein a virtual environment of the surrounding (actual testing scenario) with accurate microphone position will be maintained to predict the sound pressure level of radiated noise and directivity plot of the e-Gear Drive. Order analysis will be carried out to find the root cause of the vibration and whine noise. Broadband spectrum will be checked to find the rattle noise source. Further, with the available results, the design will be optimized, and the next loop of simulation will be performed to build a best e-Gear Drive on NVH aspect. Structural analysis will be also carried out to check the robustness of the e-Gear Drive.

Keywords: 1-D system simulation, contact ratio, e-Gear, mesh stiffness, micro and macro geometry, transmission error, radiated noise, NVH

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Authors: Alvaro Ramírez, Martín Muñoz-Morales, Ester López- Fernández, Javier Llanos, C. Ania

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Carbon blacks are value-added materials typically produced through the incomplete combustion or thermal decomposition of hydrocarbons. Traditionally, they have been used as catalysts in many different applications, but in the last decade, their potential in green chemistry has gained significant attention. Among them, the electrochemical production of H₂O₂ has attracted interest because of their properties as high oxidant capacity or their industrial interest as a bleaching agent. Carbon blacks are commonly used in this application in a catalytic ink that is drop-casted on supporting electrodes and acts as catalysts for the electrochemical production of H₂O₂ through oxygen reduction reaction (ORR). However, the different structural and electrochemical behaviors of each type of carbon black influence their applications. In this line, the term ‘carbon black’, has to be considered as a generic name that does not guarantee any physicochemical properties if any further description is mentioned. In fact, different specific surface area (SSA), surface functional groups, porous structure, and electro catalysts effect seem very important for electrochemical applications, and considerable differences were found during the analysis of four types of carbon blacks. Thus, the aim of this work is to evaluate the influence of SSA, porous structure, oxygen functional groups, and structural defects to differentiate among these carbon blacks (e.g. Vulcan XC72, Superior Graphite Co, Printex XE2, and Prolabo) for H₂O₂ production via ORR, using carbon paper as electrode support with improved selectivity and efficiency. Results indicate that the number and size of pores, along with surface functional groups, are key parameters that significantly affect the overall process efficiency.

Keywords: carbon blacks, oxygen reduction reaction, hydrogen peroxide, porosity, surface functional groups

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Authors: Wiqar Hussain Shah

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The Structural, magnetic and transport behavior of La1-xCaxMnO3+ (x=0.48, 0.50, 0.52 and 0.55 and =0.015) compositions close to charge ordering, was studied through XRD, resistivity, DC magnetization and AC susceptibility measurements. With time and thermal cycling (T<300 K) there is an irreversible transformation of the low-temperature phase from a partially ferromagnetic and metallic to one that is less ferromagnetic and highly resistive. For instance, an increase of resistivity can be observed by thermal cycling, where no effect is obtained for lower Ca concentration. The time changes in the magnetization are logarithmic in general and activation energies are consistent with those expected for electron transfer between Mn ions. The data suggest that oxygen non-stoichiometry results in mechanical strains in this two-phase system, leading to the development of irreversible metastable states, which relax towards the more stable charge-ordered and antiferromagnetic microdomains at the nano-meter size. This behavior is interpreted in terms of strains induced charge localization at the interface between FM/AFM domains in the antiferromagnetic matrix. Charge, orbital ordering and phase separation play a prominent role in the appearance of such properties, since they can be modified in a spectacular manner by external factor, making the different physical properties metastable. Here we describe two factors that deeply modify those properties, viz. the doping concentration and the thermal cycling. The metastable state is recovered by the high temperature annealing. We also measure the magnetic relaxation in the metastable state and also the revival of the metastable state (in a relaxed sample) due to high temperature (800 ) thermal treatment.

Keywords: Rare-earth maganites, nano-structural materials, doping effects on electrical, magnetic properties, competing interactions

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Authors: Cheng Yang Kwa, Yoke Rung Wong

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Laminated composite materials are widely employed in automotive, aerospace, and other industries. These materials provide distinct benefits due to their high specific strength, high specific modulus, and ability to be customized for a specific function. However, delamination of laminated composite materials is one of the main defects which can occur during manufacturing, regular operations, or maintenance. Delamination can bring about considerable internal damage, unobservable by visual check, that causes significant loss in strength and stability, leading to composite structure catastrophic failure. Structural health monitoring (SHM) is known to be the automated method for monitoring and evaluating the condition of a monitored object. There are several ways to conduct SHM in aerospace. One of the effective methods is to monitor the natural frequency shift of structure due to the presence of defect. This study investigated the mechanical resonance frequency shift of a multi-layer composite cantilever beam due to interlaminar delamination. ANSYS Workbench® was used to create a 4-plies laminated composite cantilever finite element model with [90/0]s fiber setting. Epoxy Carbon UD (230GPA) Prepreg was chosen, and the thickness was 2.5mm for each ply. The natural frequencies of the finite element model with various degree of delamination were simulated based on modal analysis and then validated by using literature. It was shown that the model without delamination had natural frequency of 40.412 Hz, which was 1.55% different from the calculated result (41.050 Hz). Thereafter, the various degree of delamination was mimicked by changing the frictional conditions at the middle ply-to-ply interface. The results suggested that delamination in the laminated composite cantilever induced a change in its stiffness which alters its mechanical resonance frequency.

Keywords: structural health monitoring, NDT, cantilever, laminate

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Authors: Mrinal Mukherjee, Gargi Seal, Bitopan Mazumdar, Prakhar Agarwal

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The central sector of Palghat-Cauvery Shear zone Tamil Nadu, India, had been studied with reference to development, mode of occurrence, interrelationship and variation of structural elements. The litho assemblages of the study area include gneisses migmatites granites and bear signature of multistage deformation patterns. The early deformation D1 is characterized in migmatites and gneisses by the development of tight to isoclinal, recumbent to reclined folds within the compositional bands that are refolded subsequently to produce D2 deformation structures ranging from type-II to type-III superposed geometry. The granite, in general, is undeformed, save a few places where strong mylonitic foliation developed with stretching lineation on it. The D1-D2 structures of gneisses and migmatites were affected by a D3 stage- E-W trending shear zone (Palghat-Cauvery Shear zone) that dips steeply towards north. The shear zone is characterized by the development of mylonite zone with stretching lineation on foliation, shear band structures, modification of geometry and orientation of earlier folds and foliations within the shear zone and development of shear induced folds and foliations. Several anastomosing lenses of shear zones define the larger Palghat-Cauvery Shear zone. The orientation of the shear induced folds and foliations and deflections of earlier foliation and folds within the Palghat-Cauvery shear zone indicate an oblique-slip thrust-shear with north-towards-east sense of displacement. The E-W trending shear zone is further openly folded along N-S in the D4 stage of deformation.

Keywords: deformation, migmatites, mylonites, shear zones

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Authors: Boonyalitpun P., Pruckpattranon P., Thonghom A., Rotpenpian N.

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Osteoarthritis is a musculoskeletal and neuromuscular abnormality, masticatory muscle, and other tissue that causes pain and breaks down the articular surface of the temporomandibular joint (TMJ). The aim of this study is to investigate the change in the mandibular condyle, in terms of thickness and porosity, and osteoclast marker in the mandibular condyle of TMJ induced osteoarthritis mice (TMJ-OA mice). We investigated the bony changes in the TMJ structure of a complete Freund adjuvant (CFA)-injected TMJ in a mice model over 28 days. On day 28, we observed any change in the TMJ by a micro computed tomography scan (micro-CT scan) in the parameters of trabecular microarchitecture. Then we studied the thickness of the condyles by hematoxylin and eosin staining. Moreover, we calculated the area around the TMJ’s condylar head containing the osteoclast expression by TRAP (Tartrate-resistant acid phosphatase) immunohistochemistry staining. The result found that the parameter of a micro-CT scan was no different from microarchitecture in the TMJ compared with the control group; however, mandibular condyles of the TMJ-OA group was significantly thinner than the control groups, and the osteoclast expression significantly increased in the TMJ-OA group. Therefore, our findings suggest that CFA-induced TMJ-OA represents an expression of osteoclast mandibular condyle of the TMJ, which is the proposed mechanism for a TMJ-OA model.

Keywords: condyle, osteoarthritis, osteoclast, temporomandibular joint

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