Miracle-dz/UniFAR-FTUs huggingface dataset:
Transitivity Analysis of Mariam’s Character in A Thousand Splendid Suns

This study investigates the portrayal of the central character, Mariam, in A Thousand Splendid Suns through the framework of Transitivity based on Halliday’s Systemic Functional Linguistics (SFL). The study has analyzed some important events in Mariam’s life such as her childhood, her marital life, and the act of murdering her husband towards the end of the novel. A clause-by-clause analysis reveals that Mariam is assigned mental processes more than material, verbal, and relational processes in the beginning of the novel. Within mental processes, a majority of the processes are cognitive which illustrate that Mariam is a rational person. In contrast, a large number of verbal processes assigned to the Mullah, a religious figure, especially on the eve of Mariam’s wedding, suggest the influential and controlling role played by the religious/orthodox segments in the Afghan society as depicted in the novel. Towards the end of the novel, there is a shift in the use of material processes from Rasheed to Mariam which suggests the transfer of ‘power’ from one to the other, culminating in the murder of Rasheed at Mariam’s hand. The study shows the transformation of Mariam’s character from an ‘innocent’ and docile person into a powerful and empowered woman who takes her fate in her own hands.
Neural Recording Implants

(1) Sensors to assess several biophysical parameters such as O2, pH, impedances, pressures, temperature, various types of biopotentials [6–8], as well as biosensing and imaging at the level of molecules, cells, ions, etc. [9]. (2) Actuators which include drug delivery microsystems and several types of electrical stimulators [4, 10, 11]. The latter devices inject charge to excite tissue and then produce action potentials necessary to recover lost neuromuscular functions.
DETERMINATION OF RELIABLE REFERENCE GENES FOR REVERSE TRANSCRIPTION QUANTITATIVE REAL-TIME PCR FROM OIL PALM TRANSCRIPTOMES

A set of reliable reference genes is essential for accurate quantification and interpretation of gene expression data using reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR). In this study, Roche-454 RNA-seq reads from 27 libraries of various oil palm tissues were systematically analysed to identify a set of potential reference genes. Eleven candidate reference genes were identified from the transcriptome data. These genes, together with three oil palm reference genes previously identified for tissue culture samples ( PD000380 , PD00569 , pOP-EA01332 ) and five classical housekeeping genes [glyceraldehyde - 3-phosphate dehydrogenase (GAPDH), NAD5, TUBULIN, UBIQUITIN, ACTIN] were analysed across samples collected from various tissues from mature oil palm (leaf, root, endosperm, mesocarp, female flowers) and stages of tissue culture (non-embryogenic callus, embryogenic callus, polyembryoids, and shoots from polyembryoids). The expression levels of these genes were compared and evaluated using geNorm. Three genes (EgREF_5, EgREF_7 and EgREF_11) were found to be appropriate reference genes for normalising gene expression data from both mature plant and tissue culture samples.
Online analysis process on Automatic Identification System data warehouse for application in vessel traffic service

The widespread application of the Automatic Identification System has had a revolutionary impact on navigation technology. In terms of its impact on a vessel traffic service, it provides rich and real-time data on the vessels, which can be used for identification, tracking, and monitoring of vessels. The Automatic Identification System rapidly accumulates large volumes of data, and these data contain a very large number of implicit maritime traffic rules and characteristics, and thus, effective methods are needed to discover the knowledge contained therein. In this research, data warehouse and online analysis process technologies, which are utilized by ordinary business entities for large-quantity business information analysis, are applied to analyze Automatic Identification System information collected through a vessel traffic service. Automatic Identification System raw data collected in a harbor area are used for analysis and post-processing using the geographic information system and database technology, and the processed data with time and space characteristics are stored in an Automatic Identification System data warehouse. In addition, online analysis process technology, the Geographic Information System, and pivot analysis are utilized to perform rapid multidimensional, meaningful high-level information inquiries, analysis of marine traffic characteristics, and rule discovery in marine traffic. These can be used as references for port development planning, traffic forecasting, navigation safety assessment, and making other policy decisions.
The Course-keeping Quality of a Ship in steered Conditions

When a directionally stable ship deviates slightly from her course owing to some external disturbances she can return to a new state of equilibium without any steering.But in this case the ship's new track is quite different from her original one. In order to keep her course, the helmsman has to use the rudder continuously. In this respect, it is of much importance to study the course-keeping quality of a ship in steered conditions.The author has studied the motion of a ship when steered, on the assumption that the rudder angle is given directly proportional to the angle of yaw and the distance of deviation from the original track.The following results have been obtained:-(1) When the helmsman gives a rudder angle directly proportional to the angle of yaw, the ship's head may come back again onto her course, but in general it is impossible for her to reach her original track. (2) When the helmsman gives a rudder angle directly proportional to the distance of deviation from the original track, the ship tends to come back onto her original track, but in this case an initial deviation or yaw increases with a sinuous course. (3) When a rudder angle is given to follow the two modes of steering above mentioned, the ship may come back again onto her course and keep her original track.
Material Transport System by Cooperation of Conveyor-Loaded AGVs.

A new transport module for constructing an efficient and flexible material handling system are proposed in this paper : an AGV (Automated Guided Vehicle) module loaded a conveyor in which it is possible to hand over a transported object between two modules. The operation can solve a deadlock problem among AGVs in the process of material handling. Prototype modules are created and hand-over experiments are made to measure three kinds of hand-over costs of the modules. Control strategy is proposed and transport simulations are made for a model plant layout by using the cost values in the former experiments. The results show the effectiveness of the proposed module and control strategy in comparison with singleloop and unidirectional type transportation.
Active and Robust Twisting Morphing Wings With Geometric Constraints for Flying or Swimming Robots

Typically, a twisting morphing wing of flying or swimming robots has one spanwise shaft and many ribs, the ribs can swing in their individual planes perpendicular to the shaft or the spanwise direction of the wing, showing different swing angles and different speed ratios with respect to the rotation of the shaft, thus the wing can form various degrees of spanwise twisting as the shaft rotates. While feasible solutions and mechanical implementations via gear transmission with tight geometric constraints are largely unexplored. This article considers the tight geometric constraints for such robotic twisting wing, and provides and particularly expands the analytical feasible solutions for the constraints, as well as provides mechanical implementations for active twisting of the wing that is driven by only one motor installed at the wing base, which implementations are compact with low inertia, low control complexity, and also high robustness that tolerates the deformations (e.g., bending due to load) of the shaft. The results serve as a design guidance and can be used for morphing wings of flying or swimming robots, particularly for accurately active spanwise twisting and large load transmissions to the movable parts.
Buildings Interoperability Landscape

Through its Building Technologies Office (BTO), the United States Department of Energy’s Office of Energy Efficiency and Renewable Energy (DOE-EERE) is sponsoring an effort to advance interoperability for the integration of intelligent buildings equipment and automation systems, understanding the importance of integration frameworks and product ecosystems to this cause. This is important to BTO’s mission to enhance energy efficiency and save energy for economic and environmental purposes. For connected buildings ecosystems of products and services from various manufacturers to flourish, the ICT aspects of the equipment need to integrate and operate simply and reliably. Within the concepts of interoperability lie the specification, development, and certification of equipment with standards-based interfaces that connect and work. Beyond this, a healthy community of stakeholders that contribute to and use interoperability work products must be developed. On May 1, 2014, the DOE convened a technical meeting to take stock of the current state of interoperability of connected equipment and systems in buildings. Several insights from that meeting helped facilitate a draft description of the landscape of interoperability for connected buildings, which focuses mainly on small and medium commercial buildings. This document revises the February 2015 landscape document to address reviewer comments, incorporate important insightsmore » from the Buildings Interoperability Vision technical meeting, and capture thoughts from that meeting about the topics to be addressed in a buildings interoperability vision. In particular, greater attention is paid to the state of information modeling in buildings and the great potential for near-term benefits in this area from progress and community alignment. « less
Pedagogical Tools for Teaching Exploration

A common problem faced in post-secondary education is how do we move our students past being satisfied with the first answer they find and to a more thoughtful, more complete, and more nuanced solution? Once our students have ‘solved’ a case problem, they believe there is nothing more to do. Students, especially freshmen and sophomores, are not accustomed to exploring the case situation for additional insights beyond the first solution. This paper presents two pedagogical tools that have dramatically improved my students’ performance in using the methods presented in the classroom. These tools have helped my students understand how to go beyond the first solution and explore the situation from more than their own perspective and thereby gain valuable insights into the situation. The first tool is a two-step grading procedure, in which I grade both a rough draft and a final draft. Instead of the grading being a punitive exercise, it has become a way to guide and further educate my students. The second tool is specifically designed in-class demonstrations that highlight the improvements that result when exploring beyond the first solution. http://dx.doi. org/10.4995/HEAd15.2015. 345
A minimax p-robust optimization approach for planning under uncertainty

Production planning is basically concerned with determining the production and inventory level over a finite planning horizon to satisfy customer demand in the most efficient way. Such a decision has long been an important issue in manufacturing since it leads higher utilization of resources and customer satisfaction, and eventually, more profit for a company. So far, several mathematical optimization models have been proposed, including linear programming, mixed integer programming, and goal programming (Nam and Logendran, 1992; Pochet and Wolsey, 2006). When researchers and practitioners develop mathematical models, dealing with uncertainty is recognized as a critical concern, since models without consideration of uncertainty can be expected to perform worse than the models accounting for the uncertainty (Mula et al., 2006). Ho (1989) classified several types of uncertainty affecting production processes into two groups: environmental uncertainty beyond the production processes, and system uncertainty within the production processes. Similarly, Ravindran and Warsing (2012) divided the sources of uncertainty into internal and external sources. Examples of system uncertainty are production lead time, yield, and quality. Environmental uncertainty includes demand uncertainty and supply uncertainty. Typically, environmental uncertainty is less manageable than system uncertainty, since it arises outside of a manufacturing system. Therefore, determining a robust production planning and inventory management policy that is less sensitive to environmental uncertainty may be one of the most effective ways to mitigate loss for a company. There have been several approaches to optimization under uncertainty, such as stochastic optimization (Birge and Louveaux, 1997; Shimizu et al, 2011) and robust optimization (RO) (Ben-Tal et al., 2009; Seo and Chung, 2014). In traditional stochastic optimization, it is assumed that an uncertain parameter follows a certain probability distribution, and an optimal solution minimizes the average objective value. In contrast, discrete scenarios or a continuous range is assumed in RO to find an optimal solution that minimizes the worst-case objective value. The use of discrete scenarios Kwang-Kyu SEO*, Jun KIM** and Byung Do CHUNG** *Department of Management Engineering, Sangmyung University 31, Sangmyungdea-gil, Dongnam-gu, Cheonan, Chungnam 330-720, Republic of Korea **Department of Industrial Engineering, Sungkyunkwan University, 2066 Seobu-ro, Jangan-gu, Suwon 440-746, Republic of Korea E-mail: bd.chung@skku.edu
The Effects of Workload and Uncertainty on Team Development

Two studies were performed that attempted to test and extend the team development theory of “punctuated equilibrium” proposed by Gersick (1988). In the first study, twelve five-person teams performed a resource allocation task, either under low or high workload. In the second study, twelve three-person teams performed an adapted version of this resource allocation task under either certain or uncertain task conditions. Various aspects of performance were assessed. The results of these studies support Gersick's contention that teams do go through one marked period of transition. However, this transition does not necessarily occur in the midpoint of the team's life cycle.
Network traffic analysis through deep learning for detection of an army of bots in health IoT network

Purpose IoT has a wide range of applications in the health-care sector and has captured the interest of many academic and industrial communities. The health IoT devices suffer from botnet attacks as all the devices are connected to the internet. An army of compromised bots may form to launch a DDoS attack, steal confidential data of patients and disrupt the service, and hence detecting this army of bots is paramount. This study aims to detect botnet attacks in health IoT devices using the deep learning technique. Design/methodology/approach This paper focuses on designing a method to protect health IoT devices from botnet attacks by constantly observing communication network traffic and classifying them as benign and malicious flow. The proposed algorithm analyzes the health IoT network traffic through implementing Bidirectional long-short term memory, a deep learning technique. The IoT-23 data set is considered for this research as it includes diverse botnet attack scenarios. Findings The performance of the proposed method is evaluated using attack prediction accuracy. It results in the highest accuracy of 84.8%, classifying benign and malicious traffic. Originality/value The proposed method constantly monitors the health IoT network to detect botnet attacks and classifies the traffic as benign or attack. The system is implemented using the BiLSTM algorithm and trained using the IoT-23 data set. The diversity of attack scenarios of the IoT-23 data set demonstrates the proposed algorithm's competence in detecting botnet types in a heterogeneous environment.
This paper is published as part of a PCCP Themed Issue on: Physical Chemistry of Biomolecular Motors and Machines

Received 5th December 2008, Accepted 9th March 2009First published as an Advance Article on the web 16th April 2009DOI: 10.1039/b821861gDielectrophoresis was used to stretch and suspend actin ﬁlaments across a trench etchedbetween two electrodes patterned on a glass slide. Optical tweezers were used to bring a motorprotein-coated bead into close proximity to a pre-selected, suspended actin ﬁlament, facilitatingthe attachment of the myosin-coated bead to the ﬁlament. The clearance beneath the ﬁlamentallowed the bead to move freely along and around its ﬁlamentous track, unhindered by solidsurfaces. Using defocused images, the three-dimensional position of the bead was tracked as afunction of time to obtain its trajectory. Experiments were carried out with myosin V andmyosin X. Both motor proteins followed left-handed helical paths with the myosin X motorexhibiting a shorter pitch than the myosin V. The combined use of electrostatic and opticaltweezers facilitates the preparation of motility assays with suspended tracks. Variants of thistechnique will enable higher complexity experiments in vitro to better understand the behaviorof motors in cells.
The effects of quality management practices on employees' well-being

Recently, there has been an explosion of published work in quality management (QM) journals on issues associated with QM practices. However, many of these works have focused on different relationships between QM practices and business performance and have not addressed the effects of QM practices on employees. This research was aimed at exploring the relationship between the application of QM practices and employees' well-being. We proposed that QM practices alter workplace characteristics, affect employees, and improve work-related attitudes and work life outcomes. We tested our hypotheses with a questionnaire using a sample of 344 participants from 27 business organisations. Regarding validity, all questions in the questionnaire were constructed after a thorough literature review. Subsequently, before the questionnaire was mailed to participants, scholars and Taiwanese human resources experts discussed and evaluated the questions. We conducted a hierarchical regression analysis with indicators of employees' well-being as the dependent variables. Our findings supported the hypothesised model, which suggested that QM practices not only increase employees' belongingness and job satisfaction, but also decrease their work overload and work stress. The implications for managers and researchers, as well as research limitations, are also discussed.
Sovereign Risk and Government Change: Elections, Ideology and Experience

Global capital markets can react dramatically to elections in developing countries, affecting governments’ access to finance and sometimes setting off broader crises. We argue, contrary to some conventional wisdom, that investors do not systematically react to the election of left-leaning parties and candidates. Government ideology is often an imprecise heuristic, given the diversity in policies among parties, especially those on the left. We therefore expect that neither elections generally, nor elections that produce specific partisan outcomes, are associated with significant changes in sovereign financing costs. Yet we also predict that the election of left-leaning parties will generate volatility in sovereign bond markets, reflecting investors’ uncertainty over future policy outcomes. This volatility is especially pronounced when new governments take office; over time, however, government policy performance enables investors to make increasingly precise estimates of political risk. Volatility has implications for the real economy, as well as for governments’ ability to manage their debt. We test, and find support for, our core expectations using monthly data on sovereign bond spreads and credit default swap prices for 74 developing countries from 1994–2015.
Simulating the Impact of Land Use Change on Contaminant Transferal during Flood Events in Houston, Texas

Many studies have evaluated the impacts of urbanization on runoff and non-point source pollutants, few studies have combined hydrologic and water quality simulation models with spatial analyses to assess these impacts at the neighborhood scale, thereby exposing any environmental inequalities. This study applies the Long-Term Hydrologic Impact Assessment (L-THIA) model in Houston, TX, to estimate the current and future urban runoff and nonpoint pollutants for 88 Houston super-neighborhoods. We use hotspot analysis to explore the effects of land use changes on runoff and pollutant loads under different socioeconomic conditions. Comparing current land uses with the predicted 2045 Houston land uses shows that runoff and non-point source pollutants in all Houston super-neighborhoods would worsen by 55%, on average. Particularly, nitrogen, phosphorous, and nickel would have the greatest increase (76.88%, 60.29%, and 59.23%, respectively). Bacterial pollutants, including fecal coliform and fecal strep, are projected to increase by more than 60%. Results also show that disadvantaged communities tend to experience increased flood risk and are likely to face more public health problems from contaminant exposure, compared with advantaged communities. To reduce these risks, prevention and mitigation efforts should be diverted toward improving green infrastructure. Advocacy planning is needed to empower marginalized neighborhoods to combat inequitable effects related to land use change.
A new methodological framework for design for additive manufacturing

ABSTRACT Additive manufacturing (AM) offers numerous benefits for innovative design solutions. However, engineers are currently not supported in identifying and incorporating these potentials systematically in their design solutions. In this paper, previous Design for Additive Manufacturing (DfAM) approaches are first reviewed comprehensively and classified into distinct categories according to their main purpose and application. They are then analysed further by being related to conventional design methodologies like VDI 2221. Since previous DfAM approaches only provide selective assistance at single steps in the product development process, a new framework for DfAM is proposed. Existing methods and tools, both from DfAM and from general design methodologies, are integrated into the modular framework structure. A concept for using the framework is presented to provide design engineers with continuous support in all product development phases, thereby fostering the complete exploitation of AM potentials and the development of AM-conformal designs.