Search results for: coding complexity metric mccabe

Authors: Natina Yaduma, Allan Williams, Sangwon Park, Andrew Lockwood

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This paper analyses flexible working, and the employment of migrants, as determinants of productivity in hotels. Controlling for the institutional environment, by focussing on a single firm, it analyses data on actual hours worked and outputs, on a weekly basis, over an 8 year period. The unusually disaggregated data allows the paper to examine not only inter-establishment, but also intra-establishment (departmental) variations in productivity, and to compare financial versus physical measures. The findings emphasise the complexity of productivity findings, sometimes contrasting evidence for establishments versus departments, and the positive but scale and measure-specific contributions of both the employment of migrants and flexible working, especially the utilisation of zero hours contracts.

Keywords: labour productivity, physical productivity, financial productivity, numerical flexibility, functional flexibility, migrant employment, cero-contract employment

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Authors: Y. Kumru, K. Enhos, H. Köymen

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In this paper, we report the experimental results on using complementary Golay coded signals at 7.5 MHz to detect breast microcalcifications of 50 µm size. Simulations using complementary Golay coded signals show perfect consistence with the experimental results, confirming the improved signal to noise ratio for complementary Golay coded signals. For improving the success on detecting the microcalcifications, orthogonal complementary Golay sequences having cross-correlation for minimum interference are used as coded signals and compared to tone burst pulse of equal energy in terms of resolution under weak signal conditions. The measurements are conducted using an experimental ultrasound research scanner, Digital Phased Array System (DiPhAS) having 256 channels, a phased array transducer with 7.5 MHz center frequency and the results obtained through experiments are validated by Field-II simulation software. In addition, to investigate the superiority of coded signals in terms of resolution, multipurpose tissue equivalent phantom containing series of monofilament nylon targets, 240 µm in diameter, and cyst-like objects with attenuation of 0.5 dB/[MHz x cm] is used in the experiments. We obtained ultrasound images of monofilament nylon targets for the evaluation of resolution. Simulation and experimental results show that it is possible to differentiate closely positioned small targets with increased success by using coded excitation in very weak signal conditions.

Keywords: coded excitation, complementary golay codes, DiPhAS, medical ultrasound

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Authors: Shyam Parhi

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Airports GIS program collects Airports data, validate and verify it, and stores it in specific database. Airports GIS allows authorized users to submit changes to airport data. The verified data is used to develop several engineering applications. One of these applications is electronic Airport Layout Plan (eALP) whose primary aim is to move from paper to digital form of ALP. The first phase of development of eALP was completed recently and it was tested for a few pilot program airports across different regions. We conducted gap analysis and noticed that a lot of development work is needed to fine tune at least six mandatory sheets of eALP. It is important to note that significant amount of programming is needed to move from out-of-box ArcGIS to a much customized ArcGIS which will be discussed. The ArcGIS viewer capability to display essential features like runway or taxiway or the perpendicular distance between them will be discussed. An enterprise level workflow which incorporates coordination process among different lines of business will be highlighted.

Keywords: geospatial data, geology, geographic information systems, aviation

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Authors: Muhammad Yousaf Sadiq

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The complexity arises in defining the construction quality due to its perception, based on inherent market conditions and their requirements, the diversified stakeholders itself and their desired output. An quantitative survey based approach was adopted in this constructive study. A questionnaire-based survey was conducted for the assessment of construction Quality perception and expectations in the context of quality improvement technique. The survey feedback of professionals of the leading construction organizations/companies of Pakistan construction industry were analyzed. The financial capacity, organizational structure, and construction experience of the construction firms formed basis for their selection. The quality perception was found to be project-scope-oriented and considered as an excess cost for a construction project. Any quality improvement technique was expected to maximize the profit for the employer, by improving the productivity in a construction project. The study is beneficial for the construction professionals to assess the prevailing construction quality perception and the expectations from implementation of any quality improvement technique in construction projects.

Keywords: construction quality, expectation, improvement, perception

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Authors: Bruno Diniz Fecchio

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Operations have been demanding increasingly challenging operational targets for the dewatering process, requiring lower humidity for concentrates. Chemical dewatering agents are able to improve solid/liquid separation processes, allowing operations to deal with increased complexity caused by either mineralogical changes or seasonal events that present operations with challenging moisture requirements for transportation and downstream steps. These chemicals reduce water retention by reducing the capillary pressure of the mineral and contributing to improved water drainage. This current study addresses the reagent effects on pile dewatering for Bauxite. Such chemicals were able to decrease the moisture of granulated Bauxite (particle size of 5 – 50 mm). The results of the laboratory scale tests and industrial trials presented the obtention of up to 11% relative moisture reduction, which reinforced the strong interaction between dewatering agents and the particle surface of granulated Bauxite. The evaluated dewatering agents, however, did not present any negative impact on these operations.

Keywords: bauxite, dewatering agents, pile dewatering, moisture reduction

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Authors: Adebola Adedugbe

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The challenge of post-harvest losses poses serious threats for food security in Nigeria and the north-eastern part with the country losing about $9billion annually due to postharvest losses in the sector. Post-harvest loss (PHL) is the quantitative and qualitative loss of food in various post-harvest operations. In Nigeria, post-harvest losses (PHL) have been a major challenge to food security and improved farmer’s income. In 2022, the Nigerian government had said over 30 percent of food produced by Nigerian farmers perish during post-harvest. For many in northeast Nigeria, agriculture is the predominant source of livelihood and income. The persistent communal conflicts, flood, decade-old attacks by boko haram and insurgency in this region have disrupted farming activities drastically, with farmlands becoming insecure and inaccessible as communities are forced to abandon ancestral homes, The impact of climate change is also affecting agricultural and fishing activities, leading to shortage of food supplies, acute hunger and loss of livelihood. This has continued to impact negatively on the region and country’s food production and availability making it loose billions of US dollars annually in income in this sector. The root cause of postharvest losses among others in crops, livestock and fisheries are lack of modern post-harvest equipment, chemical and lack of technologies used for combating losses. The 2019 Global Hunger Index showed Nigeria’s case was progressing from a ‘serious to alarming level’. As part of measures to address the problem of post-harvest losses experienced by farmers, the federal government of Nigeria concessioned 17 silos with 6000 metric tonne storage space to private sector to enable farmers to have access to storage facilities. This paper discusses the causes, effects and solutions in handling post-harvest losses and optimize returns on food security in northeast Nigeria.

Keywords: farmers, food security, northeast Nigeria, postharvest loss

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Authors: J. Yang, Y. Ma, X. Zhang, S. Li, Y. Zhang

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The traditional k-means algorithm has been widely used as a simple and efficient clustering method. However, the algorithm often converges to local minima for the reason that it is sensitive to the initial cluster centers. In this paper, an algorithm for selecting initial cluster centers on the basis of minimum spanning tree (MST) is presented. The set of vertices in MST with same degree are regarded as a whole which is used to find the skeleton data points. Furthermore, a distance measure between the skeleton data points with consideration of degree and Euclidean distance is presented. Finally, MST-based initialization method for the k-means algorithm is presented, and the corresponding time complexity is analyzed as well. The presented algorithm is tested on five data sets from the UCI Machine Learning Repository. The experimental results illustrate the effectiveness of the presented algorithm compared to three existing initialization methods.

Keywords: degree, initial cluster center, k-means, minimum spanning tree

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Authors: Gayathri Nagarajan, L. D. Dhinesh Babu

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Health care is one of the prominent industries that generate voluminous data thereby finding the need of machine learning techniques with big data solutions for efficient processing and prediction. Missing data, incomplete data, real time streaming data, sensitive data, privacy, heterogeneity are few of the common challenges to be addressed for efficient processing and mining of health care data. In comparison with other applications, accuracy and fast processing are of higher importance for health care applications as they are related to the human life directly. Though there are many machine learning techniques and big data solutions used for efficient processing and prediction in health care data, different techniques and different frameworks are proved to be effective for different applications largely depending on the characteristics of the datasets. In this paper, we present a framework that uses ensemble machine learning technique gradient boosted trees for data classification in health care big data. The framework is built on Spark platform which is fast in comparison with other traditional frameworks. Unlike other works that focus on a single technique, our work presents a comparison of six different machine learning techniques along with gradient boosted trees on datasets of different characteristics. Five benchmark health care datasets are considered for experimentation, and the results of different machine learning techniques are discussed in comparison with gradient boosted trees. The metric chosen for comparison is misclassification error rate and the run time of the algorithms. The goal of this paper is to i) Compare the performance of gradient boosted trees with other machine learning techniques in Spark platform specifically for health care big data and ii) Discuss the results from the experiments conducted on datasets of different characteristics thereby drawing inference and conclusion. The experimental results show that the accuracy is largely dependent on the characteristics of the datasets for other machine learning techniques whereas gradient boosting trees yields reasonably stable results in terms of accuracy without largely depending on the dataset characteristics.

Keywords: big data analytics, ensemble machine learning, gradient boosted trees, Spark platform

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Authors: Vikrant Gupta, Amrit Goswami

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The fixed income market forms the basis of the modern financial market. All other assets in financial markets derive their value from the bond market. Owing to its over-the-counter nature, corporate bonds have relatively less data publicly available and thus is researched upon far less compared to Equities. Bond price prediction is a complex financial time series forecasting problem and is considered very crucial in the domain of finance. The bond prices are highly volatile and full of noise which makes it very difficult for traditional statistical time-series models to capture the complexity in series patterns which leads to inefficient forecasts. To overcome the inefficiencies of statistical models, various machine learning techniques were initially used in the literature for more accurate forecasting of time-series. However, simple machine learning methods such as linear regression, support vectors, random forests fail to provide efficient results when tested on highly complex sequences such as stock prices and bond prices. hence to capture these intricate sequence patterns, various deep learning-based methodologies have been discussed in the literature. In this study, a recurrent neural network-based deep learning model using long short term networks for prediction of corporate bond prices has been discussed. Long Short Term networks (LSTM) have been widely used in the literature for various sequence learning tasks in various domains such as machine translation, speech recognition, etc. In recent years, various studies have discussed the effectiveness of LSTMs in forecasting complex time-series sequences and have shown promising results when compared to other methodologies. LSTMs are a special kind of recurrent neural networks which are capable of learning long term dependencies due to its memory function which traditional neural networks fail to capture. In this study, a simple LSTM, Stacked LSTM and a Masked LSTM based model has been discussed with respect to varying input sequences (three days, seven days and 14 days). In order to facilitate faster learning and to gradually decompose the complexity of bond price sequence, an Empirical Mode Decomposition (EMD) has been used, which has resulted in accuracy improvement of the standalone LSTM model. With a variety of Technical Indicators and EMD decomposed time series, Masked LSTM outperformed the other two counterparts in terms of prediction accuracy. To benchmark the proposed model, the results have been compared with traditional time series models (ARIMA), shallow neural networks and above discussed three different LSTM models. In summary, our results show that the use of LSTM models provide more accurate results and should be explored more within the asset management industry.

Keywords: bond prices, long short-term memory, time series forecasting, empirical mode decomposition

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Authors: L. Bikulciene, E. Venskaityte, G. Jarusevicius

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Non-stationary and nonlinear signals generated by living complex systems defy traditional mechanistic approaches, which are based on homeostasis. Previous our studies have shown that the evaluation of the interactions of physiological signals by using special analysis methods is suitable for observation of physiological processes. It is demonstrated the possibility of using deep physiological model, based interpretation of the changes of the human body’s functional states combined with an application of the analytical method based on matrix theory for the physiological signals analysis, which was applied on high risk cardiac patients. It is shown that evaluation of cardiac signals interactions show peculiar for each individual functional changes at the onset of hemodynamic restoration procedure. Therefore we suggest that the alterations of functional state of the body, after patients overcome surgery can be complemented by the data received from the suggested approach of the evaluation of functional variables interactions.

Keywords: cardiac diseases, complex systems theory, ECG analysis, matrix analysis

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Authors: Georgiana Ciobotaru

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The vocabulary that foreign students assimilate once they start studying the Romanian language must allow them to develop the linguistic competence of oral and written expression, but also the intercultural one, necessary for their integration into the new socio-cultural environment. Therefore, the familiarization courses with Romanian as a foreign language aim at fundamental language acquisitions in order to obtain the expected level of Romanian language. They also relate differently to the new culture and the new language they come in contact with, having a distinct way of expressing themselves. Foreign students want to continue their university and postgraduate studies at specialized faculties in the country; therefore, they need both a general language for their integration into society and for interaction with others, Romanians or students from countries other than their own, but also from a specialized language that facilitates didactic communication and professional development. The complexity of the vocabulary must thus cover the daily communication needs, but also the subsequent evolution of each one. This paper aims to illustrate the most important semantic fields that students must assimilate in order to crystallize a linguistic identity in the new context of their personal and professional development and to help them cope with the culture shock.

Keywords: integration, intercultural, language, linguistic, vocabulary

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Authors: Heba M. Jahin, Ali F. Bakr, Zeyad T. Elsayad

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As smart spaces can be defined as any working environment which integrates embedded computers, information appliances and multi-modal sensors to remain focused on the interaction between the users, their activity, and their behavior in the space; hence, smart space must be aware of their contexts and automatically adapt to their changing context-awareness, by interacting with their physical environment through natural and multimodal interfaces. Also, by serving the information used proactively. This paper suggests a dynamic framework through the architectural design process of the space based on the principles of computational methods and context-awareness principles to help in creating a field of changes and modifications. It generates possibilities, concerns about the physical, structural and user contexts. This framework is concerned with five main processes: gathering and analyzing data to generate smart design scenarios, parameters, and attributes; which will be transformed by coding into four types of models. Furthmore, connecting those models together in the interaction model which will represent the context-awareness system. Then, transforming that model into a virtual and ambient environment which represents the physical and real environments, to act as a linkage phase between the users and their activities taking place in that smart space . Finally, the feedback phase from users of that environment to be sure that the design of that smart space fulfill their needs. Therefore, the generated design process will help in designing smarts spaces that can be adapted and controlled to answer the users’ defined goals, needs, and activity.

Keywords: computational methods, context-awareness, design process, smart spaces

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Authors: Leah Gwatimba, Nanga Raymond Raselekoane

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The incidences of youth who engage in unlawful or criminal activities are of great concern for the criminal justice system and government in South Africa. In terms of the juvenile justice system in South Africa, under-age youth who have been found guilty and sentenced to serve a jail term cannot be sent to the same detention facility as adults. The juvenile justice system is meant to protect young offenders from physical, emotional and mental exploitation by adult prisoners. Under-age young offenders should be assisted and exposed to educational, entrepreneurial and behavioral programmes that can equip them with the much needed skills that will turn them into law-abiding and economically productive citizens. The aim of this study was to evaluate the effectiveness of the justice system in South Africa in the rehabilitation young offenders. A qualitative method was used. The study used the non-probability purposive sampling to select the respondents. In-depth interviews, focus groups, observation and thematic coding were used to collect and analyse the data respectively. The study population consisted of social workers and offending youth. The sample comprised of 16 respondents (i.e. 4 social workers and twelve offending youth (6 males and 6 females). The study indicated that there is worrying recurrence of the anti-social behavior by some of the young offenders. According to this study, the effectiveness of the juvenile justice system in the rehabilitation of the offending youth can be achieved by paying serious attention to follow-up services, participation of families of the offending youth in the diversion programmes and by improving the socio-economic conditions in the homes and communities of the offending youth.

Keywords: juvenile delinquent, juvenile justice system, diversion programmes, rehabilitation, restorative justice

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Authors: Linyu Wang, Liguo Qiao, Jianhong Xiang, Hao Xu

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In semantic communication, the existing joint Source Channel coding (JSCC) wireless communication system without pilot has unstable transmission performance and can not effectively capture the global information and location information of images. In this paper, a pilot-free image transmission system of joint source channel based on multi-level semantic information (Multi-level JSCC) is proposed. The transmitter of the system is composed of two networks. The feature extraction network is used to extract the high-level semantic features of the image, compress the information transmitted by the image, and improve the bandwidth utilization. Feature retention network is used to preserve low-level semantic features and image details to improve communication quality. The receiver also is composed of two networks. The received high-level semantic features are fused with the low-level semantic features after feature enhancement network in the same dimension, and then the image dimension is restored through feature recovery network, and the image location information is effectively used for image reconstruction. This paper verifies that the proposed multi-level JSCC algorithm can effectively transmit and recover image information in both AWGN channel and Rayleigh fading channel, and the peak signal-to-noise ratio (PSNR) is improved by 1~2dB compared with other algorithms under the same simulation conditions.

Keywords: deep learning, JSCC, pilot-free picture transmission, multilevel semantic information, robustness

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Authors: T. Sanches, K. Bousson

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As part of the development of a 4D autopilot system for unmanned aerial vehicles (UAVs), i.e. a time-dependent robust trajectory generation and control algorithm, this work addresses the problem of optimal path control based on the flight sensors data output that may be unreliable due to noise on data acquisition and/or transmission under certain circumstances. Although several filtering methods, such as the Kalman-Bucy filter or the Linear Quadratic Gaussian/Loop Transfer Recover Control (LQG/LTR), are available, the utter complexity of the control system, together with the robustness and reliability required of such a system on a UAV for airworthiness certifiable autonomous flight, required the development of a proper robust filter for a nonlinear system, as a way of further mitigate errors propagation to the control system and improve its ,performance. As such, a nonlinear algorithm based upon the LQG/LTR, is validated through computational simulation testing, is proposed on this paper.

Keywords: autonomous flight, LQG/LTR, nonlinear state estimator, robust flight control

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Authors: Egemen Sert, Leila Hedayatifar, Rachel A. Rigg, Amir Akhavan, Olha Buchel, Dominic Elias Saadi, Aabir Abubaker Kar, Alfredo J. Morales, Yaneer Bar-Yam

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The complexity of providing timely and cost-effective distribution of finished goods from industrial facilities to customers makes effective operational coordination difficult, yet effectiveness is crucial for maintaining customer service levels and sustaining a business. Logistics planning becomes increasingly complex with growing numbers of customers, varied geographical locations, the uncertainty of future orders, and sometimes extreme competitive pressure to reduce inventory costs. Linear optimization methods become cumbersome or intractable due to a large number of variables and nonlinear dependencies involved. Here we develop a complex systems approach to optimizing logistics networks based upon dimensional reduction methods and apply our approach to a case study of a manufacturing company. In order to characterize the complexity in customer behavior, we define a “customer space” in which individual customer behavior is described by only the two most relevant dimensions: the distance to production facilities over current transportation routes and the customer's demand frequency. These dimensions provide essential insight into the domain of effective strategies for customers; direct and indirect strategies. In the direct strategy, goods are sent to the customer directly from a production facility using box or bulk trucks. In the indirect strategy, in advance of an order by the customer, goods are shipped to an external warehouse near a customer using trains and then "last-mile" shipped by trucks when orders are placed. Each strategy applies to an area of the customer space with an indeterminate boundary between them. Specific company policies determine the location of the boundary generally. We then identify the optimal delivery strategy for each customer by constructing a detailed model of costs of transportation and temporary storage in a set of specified external warehouses. Customer spaces help give an aggregate view of customer behaviors and characteristics. They allow policymakers to compare customers and develop strategies based on the aggregate behavior of the system as a whole. In addition to optimization over existing facilities, using customer logistics and the k-means algorithm, we propose additional warehouse locations. We apply these methods to a medium-sized American manufacturing company with a particular logistics network, consisting of multiple production facilities, external warehouses, and customers along with three types of shipment methods (box truck, bulk truck and train). For the case study, our method forecasts 10.5% savings on yearly transportation costs and an additional 4.6% savings with three new warehouses.

Keywords: logistics network optimization, direct and indirect strategies, K-means algorithm, dimensional reduction

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Authors: Bagus Indrawan Hardi

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Cellular Automata are widely used in land use modeling, it has been proven powerful to simulate land use change for small scale in many large cities in the world. In this paper, we try to implement CA for land use modeling in unique city in Indonesia, Karawang. Instead the complex numerical implementation, CA are simple, and it is accurate and also highly dependable on the on the rules (rule based). The most important to do in CA is how we form and calculate the neighborhood effect. The neighborhood effect represents the environment and relationship situation between the occupied cell and others. We adopted 196 cells of circular neighborhood with 8 cells of radius. For the results, CA works well in this study, we exhibit several analyzed and proceed of zoomed part in Karawang region. The rule set can handle the complexity in land use modeling. However, we cannot strictly believe of the result, many non-technical parameters, such as politics, natural disaster activities, etc. may change the results dramatically.

Keywords: cellular automata (CA), land use change, spatial dynamics, urban sprawl

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Authors: Regina R. Gunawan, Indwiani Astuti, H. Raden Danarto

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Cancer is the leading cause of death worldwide. Cancer is caused by mutations that alter the function of normal human genes and give rise to cancer genes. MicroRNA (miRNA) is a small non-coding RNA that regulates the gen through complementary bond towards mRNA target and cause mRNA degradation. miRNA works by either promoting or suppressing cell proliferation. miRNA level expression in cancer may offer another value of miRNA as a biomarker in cancer diagnostic. miRNA-21 is believed to have a role in carcinogenesis by enhancing proliferation, anti-apoptosis, cell cycle progression and invasion of tumor cells. Hsa-miR-21-5p marker has been identified in Prostate Cancer (PCa) and Benign Prostatic Hyperplasia (BPH) patient’s urine. This research planned to explore the diagnostic performance of miR-21 to differentiate PCa and BPH patients. In this study, urine samples were collected from 20 PCa patients and 20 BPH patients. miR-21 relative expression against the reference gene was analyzed and compared between the two. miRNA expression was analyzed using the comparative quantification method to find the fold change. miR-21 validity in identifying PCa patients was performed by quantifying the sensitivity and specificity with the contingency table. miR-21 relative expression against miR-16 in PCa patient and in BPH patient has 12,98 differences in fold change. From a contingency table of Cq expression of miR-21 in identifying PCa patients from BPH patient, Cq miR-21 has 100% sensitivity and 75% specificity. miR-21 relative expression can be used in discriminating PCa from BPH by using a urine sample. Furthermore, the expression of miR-21 has higher sensitivity compared to PSA (Prostate specific antigen), therefore miR-21 has a high potential to be analyzed and developed more.

Keywords: benign prostate hyperplasia, biomarker, miRNA-21, prostate cancer

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Authors: Chelly Souhir, Harizi Chahida, Hachaichi Aicha, Aissaoui Sihem, Chahed Mohamed Kouni

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Introduction: In Tunisia, few studies have attempted to describe the demand for primary care in a standardized and systematic way. The purpose of this study is to describe the main reasons for demand for care in primary health care, through a survey of the Ariana Governorate PHC and to identify their evolutionary trend compared to last 30 years, reported by studies of the same type. Materials and methods: This is a cross-sectional descriptive study which concerns the study of consultants in the first line of the governorate of Ariana and their use of care recorded during 2 days in the same week during the month of May 2016, in each of these PHC. The same data collection sheet was used in all CSBs. The coding of the information was done according to the International Classification of Primary Care (ICPC). The data was entered and analyzed by the EPI Info 7 software. Results: Our study found that the most common ICPC chapters are respiratory (42%) and digestive (13.2%). In 1996 were the respiratory (43.5%) and circulatory (7.8%). In 2000, we found also the respiratory (39,6%) and circulatory (10,9%). In 2002, respiratory (43%) and digestive (10.1%) motives were the most frequent. According to the ICPC, the pathologies in our study were acute angina (19%), acute bronchitis and bronchiolitis (8%). In 1996, it was tonsillitis ( 21.6%) and acute bronchitis (7.2%). For Ben Abdelaziz in 2000, tonsillitis (14.5%) follow by acute bronchitis (8.3%). In 2002, acute angina (15.7%), acute bronchitis and bronchiolitis (11.2%) were the most common. Conclusion: Acute angina and tonsillitis are the most common in all studies conducted in Tunisia.

Keywords: acute angina, classification of primary care, primary health care, tonsillitis, Tunisia

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Authors: Sadaf Sahar, Usman Qamar, Sadaf Ayaz

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In the software development lifecycle, the quality prediction techniques hold a prime importance in order to minimize future design errors and expensive maintenance. There are many techniques proposed by various researchers, but with the increasing complexity of the software lifecycle model, it is crucial to develop a flexible system which can cater for the factors which in result have an impact on the quality of the end product. These factors include properties of the software development process and the product along with its operation conditions. In this paper, a neural network (perceptron) based software quality prediction technique is proposed. Using this technique, the stakeholders can predict the quality of the resulting software during the early phases of the lifecycle saving time and resources on future elimination of design errors and costly maintenance. This technique can be brought into practical use using successful training.

Keywords: software quality, fuzzy logic, perception, prediction

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Authors: Bahadir Batar, Elif Serdal, Berna Erdal, Hasan Ogul

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Micro-ribonucleic acids (miRNAs) are small short non-coding ribonucleic acid molecules about 22 nucleotides long. miRNAs play a key role in response to chemotherapeutic agents. WW domain-containing oxidoreductase (WWOX) gene encodes a tumor suppressor protein. Loss or reduction of Wwox protein is observed in many breast cancer cases. WWOX protein deficiency is increased in triple-negative breast cancer (TNBC). TNBC is a heterogeneous, highly aggressive, and difficult to treat tumor type. WWOX loss contributes to resistance to cisplatin therapy in patients with TNBC. Here, the aim of the study was to investigate the potential role of miRNAs in cisplatin therapy resistance of WWOX-deficient TNBC cells. This was a cell culture study. miRNA expression profiling was analyzed by LightCycler 480 system. miRNA Set Enrichment Analysis tool was used to integrate experimental data with literature-based biological knowledge to infer a new hypothesis. Increased miR-182 and decreased miR-214 were significantly correlated with cisplatin resistance in WWOX-deficient TNBC cells. miR-182 and miR-214 may involve in cisplatin resistance of WWOX-deficient TNBC cells by deregulating the DNA repair, apoptosis, or protein kinase B signaling pathways. These data highlight the mechanism by which WWOX regulates cisplatin resistance of TNBC and the potential use of WWOX as a predictor biomarker for cisplatin resistance.

Keywords: cisplatin, microRNA, triple-negative breast cancer, WWOX

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Authors: Athanasios Raftopoulos

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In this paper, an attempt is made to explain the evolution or development of human’s representational arsenal from its humble beginnings to its modern abstract symbols. Representations are physical entities that represent something else. To represent a thing (in a general sense of “thing”) means to use in the mind or in an external medium a sign that stands for it. The sign can be used as a proxy of the represented thing when the thing is absent. Representations come in many varieties, from signs that perceptually resemble their representative to abstract symbols that are related to their representata through conventions. Relying the distinction among indices, icons, and symbols, it is explained how symbolic representations gradually emerged from indices and icons. To understand the development or evolution of our representational arsenal, the development of the cognitive capacities that enabled the gradual emergence of representations of increasing complexity and expressive capability should be examined. The examination of these factors should rely on a careful assessment of the available empirical neuroscientific and paleo-anthropological evidence. These pieces of evidence should be synthesized to produce arguments whose conclusions provide clues concerning the developmental process of our representational capabilities. The analysis of the empirical findings in this paper shows that Homo Erectus was able to use both icons and symbols. Icons were used as external representations, while symbols were used in language. The first step in the emergence of representations is that a sensory-motor purely causal schema involved in indices is decoupled from its normal causal sensory-motor functions and serves as a representation of the object that initially called it into play. Sensory-motor schemes are tied to specific contexts of the organism-environment interactions and are activated only within these contexts. For a representation of an object to be possible, this scheme must be de-contextualized so that the same object can be represented in different contexts; a decoupled schema loses its direct ties to reality and becomes mental content. The analysis suggests that symbols emerged due to selection pressures of the social environment. The need to establish and maintain social relationships in ever-enlarging groups that would benefit the group was a sufficient environmental pressure to lead to the appearance of the symbolic capacity. Symbols could serve this need because they can express abstract relationships, such as marriage or monogamy. Icons, by being firmly attached to what can be observed, could not go beyond surface properties to express abstract relations. The cognitive capacities that are required for having iconic and then symbolic representations were present in Homo Erectus, which had a language that started without syntactic rules but was structured so as to mirror the structure of the world. This language became increasingly complex, and grammatical rules started to appear to allow for the construction of more complex expressions required to keep up with the increasing complexity of social niches. This created evolutionary pressures that eventually led to increasing cranial size and restructuring of the brain that allowed more complex representational systems to emerge.

Keywords: mental representations, iconic representations, symbols, human evolution

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Authors: M. Shoukath Ali, Rajendra Prasad Singh

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Game Theory approaches and their application in improving the performance of Wireless Sensor Networks (WSNs) are discussed in this paper. The mathematical modeling and analysis of WSNs may have low success rate due to the complexity of topology, modeling, link quality, etc. However, Game Theory is a field, which can efficiently use to analyze the WSNs. Game Theory is related to applied mathematics that describes and analyzes interactive decision situations. Game theory has the ability to model independent, individual decision makers whose actions affect the surrounding decision makers. The outcome of complex interactions among rational entities can be predicted by a set of analytical tools. However, the rationality demands a stringent observance to a strategy based on measured of perceived results. Researchers are adopting game theory approaches to model and analyze leading wireless communication networking issues, which includes QoS, power control, resource sharing, etc.

Keywords: wireless sensor network, game theory, cooperative game theory, non-cooperative game theory

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Authors: Luana Conte, Giorgio De Nunzio, Giuseppe Raso, Donato Cascio

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The intestinal epithelium serves as a pivotal model for studying stem cell biology and diseases such as colorectal cancer. Intestinal epithelial organoids, which replicate many in vivo features of the intestinal epithelium, are increasingly used as research models. However, manual classification of organoids is labor-intensive and prone to subjectivity, limiting scalability. In this study, we developed an automated object-detection algorithm to classify intestinal organoids in transmitted-light microscopy images. Our approach utilizes the YOLOv10 medium model (YOLO10m), a state-of-the-art object-detection algorithm, to predict and classify objects within labeled bounding boxes. The model was fine-tuned on a publicly available dataset containing 840 manually annotated images with 23,066 total annotations, averaging 28.2 annotations per image (median: 21; range: 1–137). It was trained to identify four categories: cysts, early organoids, late organoids, and spheroids, using a 90:10 train-validation split over 150 epochs. Model performance was assessed using mean average precision (mAP), precision, and recall metrics. The mAP, a standard metric ranging from 0 to 1 (with 1 indicating perfect agreement with manual labeling), was calculated at a 50% overlap threshold (mAP=0.5). Optimal performance was achieved at epoch 80, with an mAP of 0.85, precision of 0.78, and recall of 0.80 on the validation dataset. Classspecific mAP values were highest for cysts (0.87), followed by late organoids (0.83), early organoids (0.76), and spheroids (0.68). Additionally, the model demonstrated the ability to measure organoid sizes and classify them with accuracy comparable to expert scientists, while operating significantly faster. This automated pipeline represents a robust tool for large-scale, high-throughput analysis of intestinal organoids, paving the way for more efficient research in organoid biology and related fields.

Keywords: intestinal organoids, object detection, YOLOv10, transmitted-light microscopy

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Authors: Andreas Aagaard Nohr

Abstract:

International Relations is an academic discipline which is rarely in direct contact with its field. However, there has in recent years been a growing interest in the different agents within and beyond the state and their associated practices; yet some of the research tools with which to study them are not widely used. This paper introduces video-observation as a method for the study of IR and argues that it offers a unique way of studying the complexity of the everyday context of actors. The paper is divided into two main parts: First, the philosophical and methodological underpinnings of the kind of data that video-observation produces are discussed; primarily through a discussion of the phenomenology of Husserl, Heidegger, and Merleau-Ponty. Second, taking simulation of a WTO negotiation round as an example, the paper discusses how the data created can be analysed: in particular with regard to the structure of events, the temporal and spatial organization of activities, rhythm and periodicity, and the concrete role of artefacts and documents. The paper concludes with a discussion of the ontological, epistemological, and practical challenges and limitations that ought to be considered if video-observation is chosen as a method within the field of IR.

Keywords: video-observation, phenomenology, international relations

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Authors: Rajendra Chetty

Abstract:

This paper analyses the experiences of teachers of literacy in underprivileged schools in the Western Cape, South Africa. The purpose is to provide teachers in poorly resourced schools within economically deprived areas an opportunity to voice their experiences of teaching literacy. The paper is based on an empirical study using interviews and classroom observation. A descriptive account of the observation data was followed by an interpretive analysis. The content analysis of the interview data led to the development of themes and patterns for the discussion. The study reveals key factors for literacy underachievement that include lack of critical and emancipatory pedagogies, resources, parental support, lack of teacher knowledge, absence of cognitive activities, and the social complexity of poverty. The paper recommends that a new model of literacy that is underpinned by critical pedagogy challenge inequality and provides strategic and sustained teacher support in disadvantaged schools is crucial in a society emerging from oppression and racism.

Keywords: critical pedagogy, disadvantaged schools, literacy, poverty

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Authors: Soroush Rasti Boroujeni, S. Hassan Mousavi, Javad Ebrahimizadeh, Ardeshir Palizban, Mohammad-Reza Nezhad-Ahmadi, Safieddin Safavi-Naeini

Abstract:

This paper presents a wideband True Time Delay (TTD) phase shifter with low insertion loss variation. The circuit benefits from a controllable resistive load shunt with transmission line segments to optimize return loss variations, addressing the unbalanced capacitive nature of the varactor. The phase shifter reduces the complexity of the calibration process because the dependency of insertion loss on voltage controls is improved up to 3 dB. The TTD phase shifter provides a continuous changing delay time of 6.4 ps with low insertion loss (IL) in the 10-35 GHz frequency range. The proposed circuit benefits from lowloss phase shifters with a small footprint. Fabricated using a 65 nm CMOC process, the TTD phase shifter occupies only 388 × 615 μm² of chip area, achieving a 20% improvements compared to conventional TTD phase shifters.

Keywords: millimeter-wave phased-array, true time delay phase shifter, insertion loss variation, compact size

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Authors: Catherine Equey Balzli

Abstract:

Old age retirement pensions are an important concern among the Swiss but estimating one’s income after retirement is difficult due to the Swiss insurance system’s complexity. This project’s aim is to prepare for developing a digital platform that will allow individuals to plan for retirement in a simplified manner. The main objective of the platform will be to give individuals the tools to check that their savings and retirement benefits will allow them to continue the lifestyle to which they are accustomed once they are retired. The research results from qualitative (focus group) and quantitative (survey) methodologies, recommend the scope and functionalities for a digital platform to be developed. A main outcome is the need to limit the platform’s scope to old-age pension only (excluding survivors’ or disability pensions, for instance). Furthermore, an outcome regarding the functionalities is the proposition of scenarios such as early retirement, changes to income, or modifications to personal status. The development of the digital platform will be a subsequent project.

Keywords: benefit statement, digital platform, retirement financial planning, social insurance

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Authors: Kurmet Kivipõld, Maaja Vadi

Abstract:

Current paper develops the conceptual framework for organizational leadership capability. Organizational leadership here is understood as collective multi-level phenomenon which has been embedded into organizational processes as a capability at the level of the entire organization. The paper analyses and systematises the theo¬retical approaches to multi-level leadership in existing literature. This analysis marks the foundation of collective leadership at the organizational level, which forms the basis for the development of the conceptual framework of organi¬zational leadership capability. The developed conceptual framework of organiza¬tional leadership capability is formed from the synthesis of the three groups of base theories – traditional leadership theories, the resource-based view from strategic management and complexity theory from system theories. These conceptual sources present the main characteristics that determine the nature of organizational leadership capability and are the basis for its mea¬surement.

Keywords: leadership, organizational capability, organizational leadership, resource-based view, system theory

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Authors: Xing Yan Fan, Xing Lin Xu, Man Yuan Chen, Pei Tzu Lee, Yu Ting Wang, Yi Xiao Cao, Rui Yao

Abstract:

Pyramid sales have been a widespread issue in China. Victims who are defrauded not only lose money but damage interpersonal relationship. A deeper understanding of pyramid-sale models can be beneficial to prevent potential victims from fraud and improve the property security. The goals of this study were to detect psychological characteristics of pyramid-sale sellers, and analyse persuasive skills in pyramid organizations. A qualitative study was conducted in this study. Participants (n=6) recruited by 'snowball' sampling from present pyramid-sale sellers (n=3) and imprisoned pyramid-sale sellers (n=3). All participants accepted semi-structured interview for collecting data. Content analysis was adopted for data coding and analysis. The results indicate that pyramid organizations are used to utilize their appearance packaging and celebrity effect to strengthen the positions in participants’ mind. The status gap between pyramid-sale sellers in same organization, as well as rewards to increase reputation, are used to motivate participants in pyramid. The most significant common characteristics among all participants are that they tend to possess a high sense of belongingness within the firm. Moreover, the expression of pyramid-sale sellers on gambling mentality is expected to growth as constantly losing money. Findings suggest that the psychological characteristics of pyramid-sale sellers in accordance with Maslow’s hierarchy of needs, persuasive skills of pyramid organization confront to 'attitude-behaviour change model'. These findings have implication on 'immune education' that providing guidance for victims out of stuck and protecting ordinary people from the jeopardizing of pyramid sales.

Keywords: pyramid sales, characteristics, persuasive skills, qualitative study

Procedia PDF Downloads 257