Search results for: mobility features

Authors: Y. T. Boon, M. N. Naim, R. Zakaria, N. F. Abu Bakar, N. Ahmad, I. W. Lenggoro

Abstract:

In this study, encapsulation of agarwood oil with non-ionic surfactant, Tween 80 was prepared at critical micelle concentration of 0.0167 % v/v to produce the most stable nano-emulsion in aqueous. The encapsulation has minimized the bioactive compounds degradation in various pH conditions thus prolong their shelf life and maintained its initial oil grade. The oil grading of the prepared samples were conducted using the gel electrophoresis instead of using common analytical industrial grading such as gas chromatography- mass spectrometry (GC- MS). The grading method was chosen due to their unique zeta potential value after the encapsulation process. This paper demonstrates the feasibility of applying the electrophoresis principles to separate the encapsulated agarwood oil or grading of the emulsified agarwood oil. The results indicated that the grading process are potential to be further investigate based on their droplet size and zeta potential value at various pH condition when the droplet were migrate through polyacrylamide gel.

Keywords: electrophoretic mobility, essential oil, nanoemulsion, polyacrylamide gel electrophoresis, tween 80, zeta potential

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Authors: Samantha Vargas-Alfonso

Abstract:

The phenomenon of migration has been long-recorded since ancient history but never has mobility in huge numbers been so rapid and constant than that of the present. A significant portion of these migrants move for the promise of better economic subsistence by finding employment in foreign lands; while there are local and international instruments to protect these migrant workers, they still face human rights violations amongst other hurdles in integrating themselves into their host country. This research aims to look at the occurrence of Passport Confiscation for Filipino migrant workers (blue-collar workers) who are situated in Saudi Arabia. In addition to this, the study will look at the Kafala System which GCC countries practice regulating their foreign employees. The research attempts to prove that international conventions lack power in constraining the occurrence of passport confiscation and that while the kafala system exists, there is very little opportunity to address this issue.

Keywords: kafala, labor, migration, passport

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Authors: Aijing Luo, Zirui Xin, Yifeng Yuan

Abstract:

Background: With the rapid development of the online health community, more and more patients or families are seeking health information on the Internet. Objective: This study aimed to discuss how to fully reveal the health information needs expressed by hypertensive patients in their questions in the online environment. Methods: This study randomly selected 1,000 text records from the question data of hypertensive patients from 2008 to 2018 collected from the website www.haodf.com and constructed a classification system through literature research and content analysis. This paper identified the background characteristics and questioning the intention of each hypertensive patient based on the patient’s question and used co-occurrence network analysis to explore the features of the health information needs of hypertensive patients. Results: The classification system for health information needs of patients with hypertension is composed of 9 parts: 355 kinds of drugs, 395 kinds of symptoms and signs, 545 kinds of tests and examinations , 526 kinds of demographic data, 80 kinds of diseases, 37 kinds of risk factors, 43 kinds of emotions, 6 kinds of lifestyles, 49 kinds of questions. The characteristics of the explored online health information needs of the hypertensive patients include: i)more than 49% of patients describe the features such as drugs, symptoms and signs, tests and examinations, demographic data, diseases, etc. ii) these groups are most concerned about treatment (77.8%), followed by diagnosis (32.3%); iii) 65.8% of hypertensive patients will ask doctors online several questions at the same time. 28.3% of the patients are very concerned about how to adjust the medication, and they will ask other treatment-related questions at the same time, including drug side effects, whether to take drugs, how to treat a disease, etc.; secondly, 17.6% of the patients will consult the doctors online about the causes of the clinical findings, including the relationship between the clinical findings and a disease, the treatment of a disease, medication, and examinations. Conclusion: In the online environment, the health information needs expressed by Chinese hypertensive patients to doctors are personalized; that is, patients with different background features express their questioning intentions to doctors. The classification system constructed in this study can guide health information service providers in the construction of online health resources, to help solve the problem of information asymmetry in communication between doctors and patients.

Keywords: online health community, health information needs, hypertensive patients, doctor-patient communication

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Authors: David Jurado, Carlos Ávila

Abstract:

Detection of early signs of breast cancer development is crucial to quickly diagnose the disease and to define adequate treatment to increase the survival probability of the patient. Computer Aided Detection systems (CADs), along with modern data techniques such as Machine Learning (ML) and Neural Networks (NN), have shown an overall improvement in digital mammography cancer diagnosis, reducing the false positive and false negative rates becoming important tools for the diagnostic evaluations performed by specialized radiologists. However, ML and NN-based algorithms rely on datasets that might bring issues to the segmentation tasks. In the present work, an automatic segmentation and detection algorithm is described. This algorithm uses image processing techniques along with the Hough transform to automatically identify microcalcifications that are highly correlated with breast cancer development in the early stages. Along with image processing, automatic segmentation of high-contrast objects is done using edge extraction and circle Hough transform. This provides the geometrical features needed for an automatic mask design which extracts statistical features of the regions of interest. The results shown in this study prove the potential of this tool for further diagnostics and classification of mammographic images due to the low sensitivity to noisy images and low contrast mammographies.

Keywords: breast cancer, segmentation, X-ray imaging, hough transform, image analysis

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Authors: W. Ling, Mohamed Saufi Bin Awang

Abstract:

Introduction: Mycobacterium tuberculosis post a major health problem worldwide. Central nervous system (CNS) infection by mycobacterium tuberculosis is one of the most devastating complications of tuberculosis. Although with advancement in medical fields, we are yet to understand the pathophysiology of how mycobacterium tuberculosis was able to cross the blood-brain barrier (BBB) and infect the CNS. CNS TB may present with nonspecific clinical symptoms which can mimic other diseases/conditions; this is what makes the diagnosis relatively difficult and challenging. Public health has to be informed and educated about the spread of TB, and early identification of TB is important as it is a curable disease. Case Report: A young 21-year-old Malay gentleman was initially presented to us with symptoms of ear discharge, tinnitus, and right-sided headache for the past one year. Further history reveals that the symptoms have been mismanaged and neglected over the period of 1 year. Initial investigation reveals features of inflammation of the ear. Further imaging showed the feature of chronic inflammation of the otitis media and atypical right cerebral abscess, which has the same characteristic features and consistency. He further underwent a biopsy, and results reveal positive Mycobacterium tuberculosis of the otitis media. With the results and the available imaging, we were certain that this is likely a case of disseminated tuberculosis causing CNS TB. Conclusion: We aim to highlight the challenge and difficult face in our health care system and public health in early identification and treatment.

Keywords: central nervous system tuberculosis, intracranial tuberculosis, tuberculous encephalopathy, tuberculous meningitis

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Authors: Salahud Din, Saima Masood, Hafsa Zaneb, Habib –ur- Rehman, Imad Khan, Muqader Shah

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The objective of this study was to examine the osteomorphological differences between the long bones of adult Chinkara and an adult Beetal goat, using visual observation, which has still not studied. The osseous remains of these small-sized ungulates often encountered, but cannot distinguish, because of the lack of literature. Specimens of the adult Chinkara of known age and sex for osteomorphological studies are collected from the Manglot Wildlife Park and Ungulate Breeding Centre, Nizampur, Pakistan, while the bones of adult Beetal goats are obtained after slaughtering in a slaughterhouse. The research is carried out at the University of Veterinary and Animal Sciences, Lahore, Pakistan. In this research, the main morphological features recorded in the long bones of thoracic limb and pelvic limb of the adult Chinkara, by comparing them to those of the Beetal goat. The most important differences between the two species are noted in the scapula, the humerus, the radius and ulna, the metacarpal, femur, tibia metatarsal and phalanges. In conclusion, the present study suggests that the morphology of the long bones of adult Chinkara has different from the Beetal goat in various points of view. Based on these recorded points, long bones of these two species can easily be differentiated. The study is helpful in zooarcheological, comparative osteometric studies, for forensic specialists and veterinary anatomists.

Keywords: Beetal goat, Chinkara, comparative morphological features, long bones, osteology

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Authors: Cheng-En Tsai, Chung-Chun Hsiao, Fu-Yuan Chang, Liang-Lun Lan, Jia-Ying Tu

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New design of three dimensional (3D) flywheel system based on gimbal and gyro mechanics is proposed. The 3D flywheel device utilizes the rotational motion of three spherical shells and the conservation of angular momentum to achieve planar locomotion. Actuators mounted to the ring-shape frames are installed within the system to drive the spherical shells to rotate, for the purpose of steering and stabilization. Similar to the design of 2D flywheel system, it is expected that the spherical shells may function like a “flyball” to store and supply mechanical energy; additionally, in comparison with typical single-wheel and spherical robots, the 3D flywheel can be used for developing omnidirectional robotic systems with better mobility. The Lagrangian method is applied to derive the equation of motion of the 3D flywheel system, and simulation studies are presented to verify the proposed design.

Keywords: Gimbal, spherical robot, gyroscope, Lagrangian formulation, flyball

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Authors: Haifeng Wang, Haili Zhang

Abstract:

Most movie recommendation systems have been developed for customers to find items of interest. This work introduces a predictive model usable by small and medium-sized enterprises (SMEs) who are in need of a data-based and analytical approach to stock proper movies for local audiences and retain more customers. We used classification models to extract features from thousands of customers’ demographic, behavioral and social information to predict their movie genre preference. In the implementation, a Gaussian kernel support vector machine (SVM) classification model and a logistic regression model were established to extract features from sample data and their test error-in-sample were compared. Comparison of error-out-sample was also made under different Vapnik–Chervonenkis (VC) dimensions in the machine learning algorithm to find and prevent overfitting. Gaussian kernel SVM prediction model can correctly predict movie genre preferences in 85% of positive cases. The accuracy of the algorithm increased to 93% with a smaller VC dimension and less overfitting. These findings advance our understanding of how to use machine learning approach to predict customers’ preferences with a small data set and design prediction tools for these enterprises.

Keywords: computational social science, movie preference, machine learning, SVM

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Authors: Hassane Ouazzani Chahdi, Omar Helli, Bourzgui Nour Eddine, Hassan Maher, Ali Soltani

Abstract:

The real-time knowledge of the NO, NO₂ concentration at high temperature, would allow manufacturers of automobiles to meet the upcoming stringent EURO7 anti-pollution measures for diesel engines. Knowledge of the concentration of each of these species will also enable engines to run leaner (i.e., more fuel efficient) while still meeting the anti-pollution requirements. Our proposed technology is promising in the field of automotive sensors. It consists of nanostructured semiconductors based on gallium nitride and zirconia dioxide. The development of new technologies for selective detection of NO and NO₂ gas species would be a critical enabler of superior depollution. The current response was well correlated to the NO concentration in the range of 0–2000 ppm, 0-2500 ppm NO₂, and 0-300 ppm NH₃ at a temperature of 600.

Keywords: NOₓ sensors, HEMT transistor, anti-pollution, gallium nitride, gas sensor

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Authors: Brahmia Nadjet

Abstract:

The growing needs of displacements led advanced countries in this field install new specific transport systems, able to palliate any deficiencies, especially when regular public transport does not adequately meet the requests of users. In this context, on-demand transport systems (ODT) are very efficient; they rely on techniques based on the location of trip generators which should be assured effectively with the use of operators responsible of the advance reservation, planning and organization, and studying the different ODT criteria (organizational, technical, geographical, etc.). As the advanced countries in the field of transport, some developing countries are involved in the adaptation of the new technologies to reduce the deficit in their communication system. This communication presents the study of an ODT implementation in the west of Algeria, by developing the Geomatics side of the study. This part requires the use of specific systems (such as GIS, RDBMS), so we developed the process through an application in an environment of mobility by using the computer tools dedicated to the management of the entities related to the transport field.

Keywords: ODT, geomatics, GIS, transport systems

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Authors: Mattias Bergstrom

Abstract:

Significance of the Study: This research will provide new insights into the risks with digital embedded infrastructure. Through this research, we will analyze each risk and its potential negation strategies, especially for AI and autonomous automation. Moreover, the analysis that is presented in this paper will convey valuable information for future research that can create more stable, secure, and efficient autonomous systems. To learn and understand the risks, a large IoT system was envisioned, and risks with hardware, tampering, and cyberattacks were collected, researched, and evaluated to create a comprehensive understanding of the potential risks. Potential solutions have then been evaluated on an open source IoT hardware setup. This list shows the identified passive and active risks evaluated in the research. Passive Risks: (1) Hardware failures- Critical Systems relying on high rate data and data quality are growing; SCADA systems for infrastructure are good examples of such systems. (2) Hardware delivers erroneous data- Sensors break, and when they do so, they don’t always go silent; they can keep going, just that the data they deliver is garbage, and if that data is not filtered out, it becomes disruptive noise in the system. (3) Bad Hardware injection- Erroneous generated sensor data can be pumped into a system by malicious actors with the intent to create disruptive noise in critical systems. (4) Data gravity- The weight of the data collected will affect Data-Mobility. (5) Cost inhibitors- Running services that need huge centralized computing is cost inhibiting. Large complex AI can be extremely expensive to run. Active Risks: Denial of Service- It is one of the most simple attacks, where an attacker just overloads the system with bogus requests so that valid requests disappear in the noise. Malware- Malware can be anything from simple viruses to complex botnets created with specific goals, where the creator is stealing computer power and bandwidth from you to attack someone else. Ransomware- It is a kind of malware, but it is so different in its implementation that it is worth its own mention. The goal with these pieces of software is to encrypt your system so that it can only be unlocked with a key that is held for ransom. DNS spoofing- By spoofing DNS calls, valid requests and data dumps can be sent to bad destinations, where the data can be extracted for extortion or to corrupt and re-inject into a running system creating a data echo noise loop. After testing multiple potential solutions. We found that the most prominent solution to these risks was to use a Peer 2 Peer consensus algorithm over a blockchain to validate the data and behavior of the devices (sensors, storage, and computing) in the system. By the devices autonomously policing themselves for deviant behavior, all risks listed above can be negated. In conclusion, an Internet middleware that provides these features would be an easy and secure solution to any future autonomous IoT deployments. As it provides separation from the open Internet, at the same time, it is accessible over the blockchain keys.

Keywords: IoT, security, infrastructure, SCADA, blockchain, AI

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Authors: Puran Chandra Joshi

Abstract:

The Himalaya is the newest mountain system on this earth. This highest as well as fragile mountain system is still rising up. The tectonic activities have been experienced by this entire area, so the geomorphology of the region is affected by it. As we know, geomorphology is the study of landforms and their processes on the earth surface. These landforms are very important for human beings and other creatures on this planet. Present paper traces out the geomorphological features and their significance along Dhauli Ganga river valley in the Himalaya. Study area falls in higher Himalaya, which has experienced glacial and fluvial processes. Dhauli Ganga river is a considerable tributary of river kali, which is the part of huge Gangetic system. Dhauli originates in the form of two tributaries from valley glaciers of the southern slopes of Kumaun-Tibbet water divide. The upper catchment of this river has been carved by the glacial activity. The area of investigation is a remote regionin, Kumaun Himalaya. The native people do seasonal migration due to harsh winters. In summers, they return back with their cattle. In this season, they also grow potatoes and pulses, especiallybeanson river terraces. This study is important for making policies in the entire area. Area has witnessed big landslide in the recent past. So, the present study becomes more important.

Keywords: himalaya, geomorphology, glacial, tectonics

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Authors: Aabiah Nayeem, Fariha Shafiq, Mustabshra Aftab, Rabia Saman Pirzada, Samia Ghazala

Abstract:

In this modern era of technology, the concept of Internet of Things is very popular in every domain. It is a widely distributed system of things in which the data collected from sensory devices is transmitted, analyzed locally/collectively then broadcasted to network where action can be taken remotely via mobile/web apps. Today’s mobile computing is also gaining importance as the services are provided during mobility. Through mobile computing, data are transmitted via computer without physically connected to a fixed point. The challenge is to provide services with high speed and security. Also, the data gathered from the mobiles must be processed in a secured way. Mobile computing is strongly influenced by internet of things. In this paper, we have discussed security issues and challenges of internet of things and mobile computing and we have compared both of them on the basis of similarities and dissimilarities.

Keywords: embedded computing, internet of things, mobile computing, wireless technologies

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Authors: Nadjet Brahmia

Abstract:

The growing needs of displacements led advanced countries in this field install new specific transport systems, able to palliate any deficiencies, especially when regular public transport does not adequately meet the requests of users. In this context, on-demand transportation (ODT) are very efficient; they rely on techniques based on the location of trip generators which should be assured effectively with the use of operators responsible of the advance reservation, planning and organization, and studying the different ODT criteria (organizational, technical, geographical, etc.). As the advanced countries in the field of transport, some developing countries are involved in the adaptation of the new technologies to reduce the deficit in their communication system. This communication presents the study of an ODT implementation in the west of Algeria, by developing the Geomatics side of the study. This part requires the use of specific systems (such as GIS, RDBMS…), so we developed the process through an application in an environment of mobility by using the computer tools dedicated to the management of the entities related to the transport field.

Keywords: ODT, geomatics, GIS, transport systems

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Authors: Christopher Thornton, Niina Kolehmainen, Kianoush Nazarpour

Abstract:

Background: Accelerometers are widely used to measure physical activity behavior, including in children. The traditional method for processing acceleration data uses cut points, relying on calibration studies that relate the quantity of acceleration to energy expenditure. As these relationships do not generalise across diverse populations, they must be parametrised for each subpopulation, including different age groups, which is costly and makes studies across diverse populations difficult. A data-driven approach that allows physical activity intensity states to emerge from the data under study without relying on parameters derived from external populations offers a new perspective on this problem and potentially improved results. We evaluated the data-driven approach in a diverse population with a range of rapidly evolving physical and mental capabilities, namely very young children (9-38 months old), where this new approach may be particularly appropriate. Methods: We applied an unsupervised machine learning approach (a hidden semi-Markov model - HSMM) to segment and cluster the accelerometer data recorded from 275 children with a diverse range of physical and cognitive abilities. The HSMM was configured to identify a maximum of six physical activity intensity states and the output of the model was the time spent by each child in each of the states. For comparison, we also processed the accelerometer data using published cut points with available thresholds for the population. This provided us with time estimates for each child’s sedentary (SED), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA). Data on the children’s physical and cognitive abilities were collected using the Paediatric Evaluation of Disability Inventory (PEDI-CAT). Results: The HSMM identified two inactive states (INS, comparable to SED), two lightly active long duration states (LAS, comparable to LPA), and two short-duration high-intensity states (HIS, comparable to MVPA). Overall, the children spent on average 237/392 minutes per day in INS/SED, 211/129 minutes per day in LAS/LPA, and 178/168 minutes in HIS/MVPA. We found that INS overlapped with 53% of SED, LAS overlapped with 37% of LPA and HIS overlapped with 60% of MVPA. We also looked at the correlation between the time spent by a child in either HIS or MVPA and their physical and cognitive abilities. We found that HIS was more strongly correlated with physical mobility (R²HIS =0.5, R²MVPA= 0.28), cognitive ability (R²HIS =0.31, R²MVPA= 0.15), and age (R²HIS =0.15, R²MVPA= 0.09), indicating increased sensitivity to key attributes associated with a child’s mobility. Conclusion: An unsupervised machine learning technique can segment and cluster accelerometer data according to the intensity of movement at a given time. It provides a potentially more sensitive, appropriate, and cost-effective approach to analysing physical activity behavior in diverse populations, compared to the current cut points approach. This, in turn, supports research that is more inclusive across diverse populations.

Keywords: physical activity, machine learning, under 5s, disability, accelerometer

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Authors: Vidya Yadav

Abstract:

In every society, males and females are expected to behave in certain ways, and in every culture, those expectation, values and norms are different and vary accordingly. Many of the inequalities between men and women are rooted in institutional structure such as in educational field, labour market, wages, decision-making power, access to services as well as in accessing the health and well-being care also. The marriage and kinship pattern shape both men’s and women’s lives. Earlier many studies have highlighted the gender disparities which vary tremendously between regions, social classes, and communities. This study will try to explore the prominent indicators to show the status of women and well-being condition in Indian society. Primarily this paper concern with firstly identification of indicators related to gender in each area like education, work status, mobility, women participation in public and private decision making, autonomy and domestic violence etc. And once the indicators are identified next task is to define them. The indicators which are selected here are for a comparison of women’s status across Indian states. Recent Indian Human Development Survey, 2011-12 has been procured to show the current situation of women. Result shows that in spite of rising levels of education and images of growing westernization in India, love marriages remain in rarity even among urban elite. In India marriage is universal, and most of the men and women marry at relatively young age. Even though the legal age of marriage is 18, but more than 60 percent are married before the legal age. Not surprisingly, but Bihar and Rajasthan are the states with earliest age at marriage. Most of them reported that they have very limited contact with their husband before marriages. Around 69 percent of women met their husbands on the day of the wedding or shortly before. In spite of decline in fertility, still childbearing remains essential to women’s lives. Mostly women aged 25 and older had at least one child. Women’s control over household resources, physical space and mobility is also limited. Indian women’s, mostly rely on men to purchase day to day necessities, as well as medicines, as well as other necessary items. This ultimately reduces the likelihood that women have cash in hand for such purchases. The story is quite different when it comes to have control over decision over purchasing household assets such as TVs or refrigerator, names on the bank account, and home ownership papers. However, the likelihood of ownership rises among urbanite educated women’s. Women’s still have to the cultural norms and the practice of purdah or ghunghat, familial control over women’s physical movement. Wife beating and domestic violence still remain pervasive, and beaten for minor transgression like going out without permission. Development of India cannot be realized without the very significant component of gender. Therefore detailed examinations of different indicators are required to understand, strategize, plan and formulate programmes.

Keywords: autonomy, empowerment, gender, violence

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Authors: Xunan Huang, Caicai Zhang

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This paper investigated the code-mixing features in Mandarin-English bilingual children in Singapore. First, it examined whether the code-mixing rate was different in Mandarin Chinese and English contexts. Second, it explored the syntactic categories of code-mixing in Singapore bilingual children. Moreover, this study investigated whether morphological information was preserved when inserting syntactic components into the matrix language. Data are derived from the Singapore Bilingual Corpus, in which the recordings and transcriptions of sixty English-Mandarin 5-to-6-year-old children were preserved for analysis. Results indicated that the rate of code-mixing was asymmetrical in the two language contexts, with the rate being significantly higher in the Mandarin context than that in the English context. The asymmetry is related to language dominance in that children are more likely to code-mix when using their nondominant language. Concerning the syntactic categories of code-mixing words in the Singaporean bilingual children, we found that noun-mixing, verb-mixing, and adjective-mixing are the three most frequently used categories in code-mixing in the Mandarin context. This pattern mirrors the syntactic categories of code-mixing in the Cantonese context in Cantonese-English bilingual children, and the general trend observed in lexical borrowing. Third, our results also indicated that English vocabularies that carry morphological information are embedded in bare forms in the Mandarin context. These findings shed light upon how bilingual children take advantage of the two languages in mixed utterances in a bilingual environment.

Keywords: bilingual children, code-mixing, English, Mandarin Chinese

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Authors: Kent Salomonsson, Xuefang Zhao, Sara Kallin

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Human soft tissue is loaded and deformed by any activity, an effect known as a stress-strain relationship, and is often described by a load and tissue elongation curve. Several advances have been made in the fields of biology and mechanics of soft human tissue. However, there is limited information available on in vivo tissue mechanical characteristics and behavior. Confident mechanical properties of human soft tissue cannot be extrapolated from e.g. animal testing. Thus, there is need for non invasive methods to analyze mechanical characteristics of soft human tissue. In the present study, the internal mechanical conditions of the lower limb, which is subject to an external load, is studied by use of the finite element method. A detailed finite element model of the lower limb is made possible by use of MRI scans. Skin, fat, bones, fascia and muscles are represented separately and the material properties for them are obtained from literature. Previous studies have been shown to address macroscopic deformation features, e.g. indentation depth, to a large extent. However, the detail in which the internal anatomical features have been modeled does not reveal the critical internal strains that may induce hypoxia and/or eventual tissue damage. The results of the present study reveals that lumped material models, i.e. averaging of the material properties for the different constituents, does not capture regions of critical strains in contrast to more detailed models.

Keywords: FEM, tissue, indentation, properties

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Authors: Meysam Saidi

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While the specific externalities and required regulatory measures in relation to Islamic banking are fairly uncertain, the business is growing across the world. Unofficial data indicate that the Islamic Finance market is growing with annual rate of 15% and it has reached 1.3 $ trillion size. This trend is associated with inherent systematic connection of Islamic financial institutions to other entities and different sectors of economies. Islamic banking has been subject of market development policies in major economies, most notably the UK. This trend highlights the need for identification of distinct risk features of Islamic banking and crafting customized regulatory measures. So far there has not been a significant systemic crisis in this market which can be attributed to its distinct nature. However, the significant growth and spread of its products worldwide necessitate an in depth study of its nature for customized congruent regulatory measures. In the post financial crisis era some market analysis and reports suggested that the Islamic banks fairly weathered the crisis. As far as heavily blamed conventional financial products such as subprime mortgage backed securities and speculative credit default swaps were concerned the immunity claim can be considered true, as Islamic financial institutions were not directly exposed to such products. Nevertheless, similar to the experience of the conventional banking industry, it can be only a matter of time for Islamic banks to face failures that can be specific to the nature of their business. Using the experience of conventional banking regulations and identifying those peculiarities of Islamic banking that need customized regulatory approach can aid to prevent major failures. Frank Knight has stated that “We perceive the world before we react to it, and we react not to what we perceive, but always to what we infer”. The debate over congruent Islamic banking regulations might not be an exception to Frank Knight’s statement but I will try to base my discussion on concrete evidences. This paper first analyzes both theoretical and actual features of Islamic banking in order to ascertain to its peculiarities in terms of market stability and other externalities. Next, the paper discusses distinct features of Islamic financial transactions and banking which might require customized regulatory measures. Finally, the paper explores how a more transparent path for the Islamic banking regulations can be drawn.

Keywords: Islamic banking, regulation, risks, capital requirements, customer protection, financial stability

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Authors: Halina Veloso e Zarate, Manuela Triggianese

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The urban challenges posed by rapid population growth, climate adaptation, and sustainable living have compelled Dutch cities to reimagine their built environment and transportation systems. As a pivotal contributor to CO₂ emissions, the transportation sector in the Netherlands demands innovative solutions for transitioning to low-carbon mobility. This study investigates the potential of transit oriented development (TOD) as a strategy for achieving carbon reduction and sustainable urban transformation. Focusing on the Lombardijen station area in Rotterdam, which is targeted for significant densification, this paper presents a design-oriented exploration of a low-carbon transport node. By employing a research-by-design methodology, this study delves into multifaceted factors and scales, aiming to propose future scenarios for Lombardijen. Drawing from a synthesis of existing literature, applied research, and practical insights, a robust design framework emerges. To inform this framework, governmental data concerning the built environment and material embodied carbon are harnessed. However, the restricted access to crucial datasets, such as property ownership information from the cadastre and embodied carbon data from De Nationale Milieudatabase, underscores the need for improved data accessibility, especially during the concept design phase. The findings of this research contribute fundamental insights not only to the Lombardijen case but also to TOD studies across Rotterdam's 13 nodes and similar global contexts. Spatial data related to property ownership facilitated the identification of potential densification sites, underscoring its importance for informed urban design decisions. Additionally, the paper highlights the disparity between the essential role of embodied carbon data in environmental assessments for building permits and its limited accessibility due to proprietary barriers. Although this study lays the groundwork for sustainable urbanization through TOD-based design, it acknowledges an area of future research worthy of exploration: the socio-economic dimension. Given the complex socio-economic challenges inherent in the Lombardijen area, extending beyond spatial constraints, a comprehensive approach demands integration of mobility infrastructure expansion, land-use diversification, programmatic enhancements, and climate adaptation. While the paper adopts a TOD lens, it refrains from an in-depth examination of issues concerning equity and inclusivity, opening doors for subsequent research to address these aspects crucial for holistic urban development.

Keywords: Rotterdam zuid, transport oriented development, carbon emissions, low-carbon design, cross-scale design, data-supported design

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Authors: Diana Ruth Caga-Anan

Abstract:

Classroom management is a critical skill but the styles are constantly evolving. It is constantly under pressure particularly in the college education level due to diversity in student profiles, modes of delivery, and marketization of higher education. This study sought to analyze the extent of implementation of classroom management practices (CMPs) of the college instructors of the Hotel, Restaurant, and Institution Management of a premier university in the Philippines. It was also determined if their length of teaching affects their classroom management style. A questionnaire with sixteen 'evidenced-based' CMPs grouped into five critical features of classroom management, adopted from the literature search of Simonsen et al. (2008), was administered to 4 instructor-respondents and to their 88 students. Weighted mean scores of each of the CMPs revealed that there were differences between the instructors’ self-scores and their students’ ratings on their implementation of CMPs. The critical feature of classroom management 'actively engage students in observable ways' got the highest mean score, corresponding to 'always' from the instructors’ self-rating and 'frequently' from their students’ ratings. However, 'use a continuum of strategies to respond to inappropriate behaviors' got the lowest scores from both the instructors and their students corresponding only to 'occasionally'. Analysis of variance showed that the only CMP affected by the length of teaching is the practice of 'prompting students to respond'. Based on the findings, some recommendations for the instructors to improve on the critical feature where they scored low are discussed and suggestions are included for future research.

Keywords: classroom management, CMPs, critical features, evidence-based classroom management practices

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Authors: Walid Moudani

Abstract:

The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the coronary heart disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts’ knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.

Keywords: multi-classifier decisions tree, features reduction, dynamic programming, rough sets

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Authors: A. O. Boyo, A. T. Akinwunmi

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The effect of extracting solvent and adjustment of pHs on the stability of Terminalia catappa L. dye-sensitized solar cell was investigated. We introduced ZnO as an alternative to TiO2 in the dye sensitized solar cells (DSSCs) due to its band gap similar to TiO2, higher electron mobility, and flexible procedures of preparations. Dye-sensitized solar cells (DSSCs) based on Terminalia catappa L. was extracted in water (A), ethanol (B) and the mixture of ethanol and water in the ratio 1:1by volume (C). The best performance Solar cells sensitized was from extracts A and achieved up to Jsc 1.51 mAcm−2, Voc 0.75V, FF 0.88 and η 0.63%. We notice that as pHs decreases there is the increase in DSSC efficiency. There is Long period stability in efficiency of the cells prepared using A than in C and a fair stability in efficiency of B cell. The results obtained with extracts B and C confirmed that Ethanol with water could not be considered as a suitable solvent for the extraction of natural dye.

Keywords: zinc oxide, dye-sensitized solar cell, terminalia catappa L., TiO2

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Authors: Sonia Kudlacik-Kramarczyk, Anna Drabczyk, Dagmara Malina, Bozena Tyliszczak, Agnieszka Sobczak-Kupiec

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Introduction: In the preparation of polymer materials, compounds of natural origin are currently gaining more and more interest. This is particularly noticeable in the case of synthesis of materials considered for biomedical use. Then, selected material has to meet many requirements. It should be characterized by non-toxicity, biodegradability and biocompatibility. Therefore special attention is directed to substances such as polysaccharides, proteins or substances that are the basic building components of proteins, i.e. amino acids. These compounds may be crosslinked with other reagents that leads to the preparation of polymer matrices. Such amino acids as e.g. cysteine or histidine. On the other hand, previously mentioned requirements may be met by polymers obtained as a result of biosynthesis, e.g. polyhydroxybutyrate. This polymer belongs to the group of aliphatic polyesters that is synthesized by microorganisms (selected strain of bacteria) under specific conditions. It is possible to modify matrices based on given polymer with substances of various origin. Such a modification may result in the change of their properties or/and in providing the material with new features desirable in viewpoint of specific application. Described materials are synthesized using UV radiation. Process of photopolymerization is fast, waste-free and enables to obtain final products with favorable properties. Methodology: Polymer matrices have been prepared by means of photopolymerization. First step involved the preparation of solutions of particular reagents and mixing them in the appropriate ratio. Next, crosslinking agent and photoinitiator have been added to the reaction mixture and the whole was poured into the Petri dish and treated with UV radiation. After the synthesis, polymer samples were dried at room temperature and subjected to the numerous analyses aimed at the determining their physicochemical properties. Firstly, sorption properties of obtained polymer matrices have been determined. Next, mechanical properties have been characterized, i.e. tensile strength. The ability to deformation under applied stress of all prepared polymer matrices has been checked. Such a property is important in viewpoint of the application of analyzed materials e.g. as wound dressings. Wound dressings have to be elastic because depending on the location of the wound and its mobility, such a dressing has to adhere properly to the wound. Furthermore, considering the use of the materials for biomedical purposes it is essential to determine its behavior in environments simulating these ones occurring in human body. Therefore incubation studies using selected liquids have also been conducted. Conclusions: As a result of photopolymerization process, polymer matrices based on natural compounds have been prepared. These exhibited favorable mechanical properties and swelling ability. Moreover, biocompatibility in relation to simulated body fluids has been stated. Therefore it can be concluded that analyzed polymer matrices constitute an interesting materials that may be considered for biomedical use and may be subjected to the further more advanced analyses using specific cell lines.

Keywords: photopolymerization, polymer matrices, simulated body fluids, swelling properties

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Authors: Philipp Sommer, Amgad Agoub

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The construction sector significantly impacts global CO₂ emissions, particularly through the energy usage of residential buildings. To address this, various governments, including Germany's, are focusing on reducing emissions via sustainable refurbishment initiatives. This study examines the application of machine learning (ML) to estimate energy demands dynamically in residential buildings and enhance the potential for large-scale sustainable refurbishment. A major challenge in Germany is the lack of extensive publicly labeled datasets for energy performance, as energy performance certificates, which provide critical data on building-specific energy requirements and consumption, are not available for all buildings or require on-site inspections. Conversely, England and other countries in the European Union (EU) have rich public datasets, providing a viable alternative for analysis. This research adapts insights from these English datasets to the German context by developing a comprehensive data schema and calibration dataset capable of predicting building energy demand effectively. The study proposes a minimal feature set, determined through feature importance analysis, to optimize the ML model. Findings indicate that ML significantly improves the scalability and accuracy of energy demand forecasts, supporting more effective emissions reduction strategies in the construction industry. Integrating energy performance certificates into municipal heat planning in Germany highlights the transformative impact of data-driven approaches on environmental sustainability. The goal is to identify and utilize key features from open data sources that significantly influence energy demand, creating an efficient forecasting model. Using Extreme Gradient Boosting (XGB) and data from energy performance certificates, effective features such as building type, year of construction, living space, insulation level, and building materials were incorporated. These were supplemented by data derived from descriptions of roofs, walls, windows, and floors, integrated into three datasets. The emphasis was on features accessible via remote sensing, which, along with other correlated characteristics, greatly improved the model's accuracy. The model was further validated using SHapley Additive exPlanations (SHAP) values and aggregated feature importance, which quantified the effects of individual features on the predictions. The refined model using remote sensing data showed a coefficient of determination (R²) of 0.64 and a mean absolute error (MAE) of 4.12, indicating predictions based on efficiency class 1-100 (G-A) may deviate by 4.12 points. This R² increased to 0.84 with the inclusion of more samples, with wall type emerging as the most predictive feature. After optimizing and incorporating related features like estimated primary energy consumption, the R² score for the training and test set reached 0.94, demonstrating good generalization. The study concludes that ML models significantly improve prediction accuracy over traditional methods, illustrating the potential of ML in enhancing energy efficiency analysis and planning. This supports better decision-making for energy optimization and highlights the benefits of developing and refining data schemas using open data to bolster sustainability in the building sector. The study underscores the importance of supporting open data initiatives to collect similar features and support the creation of comparable models in Germany, enhancing the outlook for environmental sustainability.

Keywords: machine learning, remote sensing, residential building, energy performance certificates, data-driven, heat planning

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Authors: Pawel Magryta, Mateusz Paszko

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In today's world, a big problem of individual mobility, especially in large urban areas, occurs. Commonly used grand way of transport such as buses, trains or cars do not fulfill their tasks, i.e. they are not able to meet the increasing mobility needs of the growing urban population. Additional to that, the limitations of civil infrastructure construction in the cities exist. Nowadays the most common idea is to transfer the part of urban transport on the level of air transport. However to do this, there is a need to develop an individual flying transport vehicle. The biggest problem occurring in this concept is the type of the propulsion system from which the vehicle will obtain a lifting force. Standard propeller drives appear to be too noisy. One of the ideas is to provide the required take-off and flight power by the machine using the innovative ejector system. This kind of the system will be designed through a suitable choice of the three-dimensional geometric structure with special shape of nozzle in order to generate overpressure. The authors idea is to make a device that would allow to cumulate the overpressure using the a five-sided geometrical structure that will be limited on the one side by the blowing flow of air jet. In order to test this hypothesis a computer simulation study of aerodynamic drag of such 3D structures have been made. Based on the results of these studies, the tests on real model were also performed. The final stage of work was a comparative analysis of the results of simulation and real tests. The CFD simulation studies of air flow was conducted using the Star CD - Star Pro 3.2 software. The design of virtual model was made using the Catia v5 software. Apart from the objective to obtain advanced aviation propulsion system, all of the tests and modifications of 3D structures were also aimed at achieving high efficiency of this device while maintaining the ability to generate high value of overpressures. This was possible only in case of a large mass flow rate of air. All these aspects have been possible to verify using CFD methods for observing the flow of the working medium in the tested model. During the simulation tests, the distribution and size of pressure and velocity vectors were analyzed. Simulations were made with different boundary conditions (supply air pressure), but with a fixed external conditions (ambient temp., ambient pressure, etc.). The maximum value of obtained overpressure is 2 kPa. This value is too low to exploit the power of this device for the individual transport vehicle. Both the simulation model and real object shows a linear dependence of the overpressure values obtained from the different geometrical parameters of three-dimensional structures. Application of computational software greatly simplifies and streamlines the design and simulation capabilities. This work has been financed by the Polish Ministry of Science and Higher Education.

Keywords: aviation propulsion, CFD, 3d structure, aerodynamic drag

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Authors: Omar A. Abuobidalla, Mingyuan Chen, Satyaveer S. Chauhan

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Railroad transportation of hazardous materials freights is important to the North America economics that supports the national’s supply chain. This paper introduces various extensions of the dynamic hazardous materials trip plan problems. The problem captures most of the operational features of a real-world railroad transportations systems that dynamically initiates a set of blocks and assigns each shipment to a single block path or multiple block paths. The dynamic hazardous materials trip plan policies have distinguishing features that are integrating the blocking plan, and the block activation decisions. We also present a non-linear mixed integer programming formulation for each variant and present managerial insights based on a hypothetical railroad network. The computation results reveal that the dynamic car scheduling policies are not only able to take advantage of the capacity of the network but also capable of diminishing the population, and environment risks by rerouting the active blocks along the least risky train services without sacrificing the cost advantage of the railroad. The empirical results of this research illustrate that the issue of integrating the blocking plan, and the train makeup of the hazardous materials freights must receive closer attentions.

Keywords: dynamic car scheduling, planning and scheduling hazardous materials freights, airborne hazardous materials, gaussian plume model, integrated blocking and routing plans, box model

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Authors: Sultan Mahmud, Qamar Zaman, Travis Esau, Young Chang

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Strawberry powdery mildew (PM) is a serious disease that has a significant impact on strawberry production. Field scouting is still a major way to find PM disease, which is not only labor intensive but also almost impossible to monitor disease severity. To reduce the loss caused by PM disease and achieve faster automatic detection of the disease, this paper proposes an approach for detection of the disease, based on image texture and classified with support vector machines (SVMs) and k-nearest neighbors (kNNs). The methodology of the proposed study is based on image processing which is composed of five main steps including image acquisition, pre-processing, segmentation, features extraction and classification. Two strawberry fields were used in this study. Images of healthy leaves and leaves infected with PM (Sphaerotheca macularis) disease under artificial cloud lighting condition. Colour thresholding was utilized to segment all images before textural analysis. Colour co-occurrence matrix (CCM) was introduced for extraction of textural features. Forty textural features, related to a physiological parameter of leaves were extracted from CCM of National television system committee (NTSC) luminance, hue, saturation and intensity (HSI) images. The normalized feature data were utilized for training and validation, respectively, using developed classifiers. The classifiers have experimented with internal, external and cross-validations. The best classifier was selected based on their performance and accuracy. Experimental results suggested that SVMs classifier showed 98.33%, 85.33%, 87.33%, 93.33% and 95.0% of accuracy on internal, external-I, external-II, 4-fold cross and 5-fold cross-validation, respectively. Whereas, kNNs results represented 90.0%, 72.00%, 74.66%, 89.33% and 90.3% of classification accuracy, respectively. The outcome of this study demonstrated that SVMs classified PM disease with a highest overall accuracy of 91.86% and 1.1211 seconds of processing time. Therefore, overall results concluded that the proposed study can significantly support an accurate and automatic identification and recognition of strawberry PM disease with SVMs classifier.

Keywords: powdery mildew, image processing, textural analysis, color co-occurrence matrix, support vector machines, k-nearest neighbors

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Authors: Jochen Nelles, Susanne Kohns, Julia Spies, Friederike Schmitz-Buhl, Roland Thietje, Christopher Brandl, Alexander Mertens, Christopher M. Schlick

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Industrial robots as part of highly automated manufacturing are recently developed to cooperative (light-weight) robots. This offers the opportunity of using them as assistance robots and to improve the participation in professional life of disabled or handicapped people such as tetraplegics. Robots under development are located within a cooperation area together with the working person at the same workplace. This cooperation area is an area where the robot and the working person can perform tasks at the same time. Thus, working people and robots are operating in the immediate proximity. Considering the physical restrictions and the limited mobility of tetraplegics, a hands-free robot control could be an appropriate approach for a cooperative assistance robot. To meet these requirements, the research project MeRoSy (human-robot synergy) develops methods for cooperative assistance robots based on the measurement of head movements of the working person. One research objective is to improve the participation in professional life of people with disabilities and, in particular, mobility impaired persons (e.g. wheelchair users or tetraplegics), whose participation in a self-determined working life is denied. This raises the research question, how a human-robot cooperation workplace can be designed for hands-free robot control. Here, the example of a library scenario is demonstrated. In this paper, an empirical study that focuses on the impact of head movement related stress is presented. 12 test subjects with tetraplegia participated in the study. Tetraplegia also known as quadriplegia is the worst type of spinal cord injury. In the experiment, three various basic head movements were examined. Data of the head posture were collected by a motion capture system; muscle activity was measured via surface electromyography and the subjective mental stress was assessed via a mental effort questionnaire. The muscle activity was measured for the sternocleidomastoid (SCM), the upper trapezius (UT) or trapezius pars descendens, and the splenius capitis (SPL) muscle. For this purpose, six non-invasive surface electromyography sensors were mounted on the head and neck area. An analysis of variance shows differentiated muscular strains depending on the type of head movement. Systematically investigating the influence of different basic head movements on the resulting strain is an important issue to relate the research results to other scenarios. At the end of this paper, a conclusion will be drawn and an outlook of future work will be presented.

Keywords: assistance robot, human-robot interaction, motion capture, stress-strain-concept, surface electromyography, tetraplegia

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Authors: A. Hameed, N. Upreti, P. Srivastava

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Main objective the present study is to investigate microscopic, sub-microscopic, clay mineralogical and geochemical characteristics of three calcic soil profiles from the western Thar Desert for the last 30 ka paleoclimatic information. Thin-sections of the soils show weakly to moderately developed pedofeatures dominated by powdery to well-indurated pedogenic calcium carbonate. Sub-microscopy of the representative calcretes show extensive growth of fibrous palygorskite in pore spaces of micritic and sparitic nodules. XRD of the total clay ( < 2 µm) and fine clay ( < 0.2 µm) fractions of the soils show dominance of smectite, palygorskite, chlorite, mica, kaolinite and small amounts of quartz and feldspar. Formation of the palygorskite is attributed to pedogenic processes associated with Bw, Bss and Bwk horizons during drier conditions over the last 30 ka. Formation of palygorskite was mainly favoured by strongly evaporating percolating water and precipitation of secondary calcite, high pH (9-10), high Mg, Si and low Al activities during pedogenesis. Age estimate and distribution of calcretes, palygorskite, and illuvial features indicate fluctuating monsoonal strength during MIS3-MIS1 stages. The pedogenic features in calcic soils of western Thar suggest relatively arid conditions during MIS3-MIS2 transition and LGM time that changed to relatively wetter conditions during post LGM time and again returned to dry conditions at ~4 ka in MIS1.

Keywords: palygorskite, clay minerals, Thar, aridisol, late quaternary

Procedia PDF Downloads 150