Miracle-dz/UniFAR-FTUs huggingface dataset:
Hospital Leadership in Support of Digital Transformation

Evolving customer expectations and the rapid introduction of new information technologies are influencing business operations, and businesses need to transform themselves with new operating models to remain competitive. The traditional top-down administrative leadership approach is not sufficiently flexible to support the innovation needed to sustain customer engagement and retention. There is a need for both an enabling leadership that supports the exploration of innovative ideas quickly for viability and an adaptive leadership to transition the ideas that show promise into the current business model or a variation of this model to sustain growth. We define digital leadership as a strategic process that collectively uses these three leadership styles to create an ecosystem that advances a culture of innovation within organizations. This leadership process uses four foundational platforms to support business transformations: (1) An innovation platform to empower teams to explore ideas that create value using digital transformations; (2) An agile system and business platform to quickly design and deliver IT implementations; (3) A learning platform to support reflective discourse that leads to organizational capacity building; and (4) An adoption platform to decide when and what implementations get transitioned to the regular business for sustaining competitiveness. We will illustrate how digital leadership is used to transform the culture of a community hospital through several IS implementations recognized by external peers for their innovativeness
Domain-Specific Sentiment Word Extraction by Seed Expansion and Pattern Generation

This paper focuses on the automatic extraction of domain-specific sentiment word (DSSW), which is a fundamental subtask of sentiment analysis. Most previous work utilizes manual patterns for this task. However, the performance of those methods highly relies on the labelled patterns or selected seeds. In order to overcome the above problem, this paper presents an automatic framework to detect large-scale domain-specific patterns for DSSW extraction. To this end, sentiment seeds are extracted from massive dataset of user comments. Subsequently, these sentiment seeds are expanded by synonyms using a bootstrapping mechanism. Simultaneously, a synonymy graph is built and the graph propagation algorithm is applied on the built synonymy graph. Afterwards, syntactic and sequential relations between target words and high-ranked sentiment words are extracted automatically to construct large-scale patterns, which are further used to extracte DSSWs. The experimental results in three domains reveal the effectiveness of our method.
Quantifying the density of Friedman's pathogenic emotions (AIAI).

Because of both psychoneuroendocrine and psychobehavioral mechanisms, the chronicity of negative emotional arousal is probably the final common pathway mediating the relationship of psychosocial factors (cognitions, environments and behaviors) on one side of the mind-brain chasm, and ischemic heart disease (IHD) on the other. But the problem of "denial" remains a potential source of measurement error in studies of the association of such factors and IHD endpoints. The present study examined the association of patient-reported and spouse/friend-reported AIAI (aggravation, irritation, anger and impatience) with four measures of Type A Behavior or hostility (the Framingham Type A Scale, Cook-Medley Hostility Scale, Type A Structured Interview and a Hostility rating from the Structured Interview) in two samples: 175 men undergoing coronary angiography; and 56 age and SES-matched males with no manifest history of occlusive atherosclerotic disease. Chronic AIAI was underreported by the sample as a whole relative to spouse/friend perception, while the opposite was true of Depression and Anxiety/Worry (p < .001). All four measures were significantly associated with both patient and spouse/friend reported chronicity of AIAI, but the FTAS was the most reliable correlate according to both sources. The FTAS was also negatively associated with denial of AIAI, while the other three measures were not.
Complete Development of Mosquito Phases of the Malaria Parasite in Vitro

Methods for reproducible in vitro development of the mosquito stages of malaria parasites to produce infective sporozoites have been elusive for over 40 years. We have cultured gametocytes ofPlasmodium berghei through to infectious sporozoites with efficiencies similar to those recorded in vivo and without the need for salivary gland invasion. Oocysts developed extracellularly in a system whose essential elements include co-cultured Drosophila S2 cells, basement membrane matrix, and insect tissue culture medium. Sporozoite production required the presence of para-aminobenzoic acid. The entire life cycle of P. berghei, a useful model malaria parasite, can now be achieved in vitro.
Molecular Substrates of Social Avoidance Seen following Prenatal Ethanol Exposure and Its Reversal by Social Enrichment

Prenatal ethanol exposure is associated with, and is a risk factor for, developmental disorders with abnormal social behaviors, including autism spectrum disorders. We hypothesize that the specific effects of ethanol on social behavior are defined by the timing of the exposure as well as subsequent changes in brain regions such as the amygdala and ventral striatum. We recently reported that in utero ethanol exposure on gestational day 12 alters social behaviors of weanling [postnatal day (P) 28], adolescent (P42), and young adult (P75) rats. Male, but not female, offspring of the ethanol-exposed dams showed significant decreases in social investigation (sniffing of a social partner), contact behavior (grooming or crawling over/under the partner), and play fighting (following, chasing, nape attacks, or pinning) at all ages tested with maximal effects at P28 and P42. Furthermore, ethanol-exposed males and females showed evidence of social avoidance at P42 and P75. The present study sought to test whether a form of social enrichment could normalize any of the social deficits and what the molecular mechanisms of such effects might be. We found that housing rats with nonmanipulated control rats normalized the social avoidance phenotype normally seen when they are housed with sex-matched prenatal ethanol-exposed littermates. There was no mitigation of the other ethanol-induced behavioral deficits. Conversely, male control-treated rats housed with nonlittermates showed deficits in play fighting, social investigation and contact behavior. Molecular analyses of the amygdala and ventral striatum of adolescent rats following fetal ethanol exposure indicated several specific neurotransmitter systems and pathways that might underlie the social avoidance phenotype as well as its reversal.
Mesotheliomas: A light- and electron‐microscopical study concerning histogenetic relationships between the epithelial and the mesenchymal variants

Mesotheliomas have variable histological patterns which may suggest a predominance of epithelial cells, a predominance of mesenchymal cells, or a mixture of epithelial and mesenchymal cells. An adenomatoid tumor of the testis, a fibrous mesothelioma, and an epithelial mesothelioma were studied by light and electron microscopy to search for evidence of a histogenetic link between the various cell types. Each neoplasm was composed of poorly differentiated spindle-shaped cells and variably differentiated cells having epithelial, mesenchymal, and combined epithelial and mesenchymal features. The differentiated neoplastic cells exhibited a spectrum of cytodifferentiation with typical mesothelial cells at one end, typical fibroblasts at the other end, and trasitional forms in between. These observations are presented in detail as morphological evidence for a direct histogenetic relationship between the epithelial-appearing cells and the mesenchymal-appearing cells of human mesothelial neoplasms.
The Earth Mourns: Prophetic Metaphor and Oral Aesthetic

"The Earth Mourns": Prophetic Metaphor and Oral Aesthetic, by Katherine M. Hayes. Academia Biblica 8. Atlanta: Society of Biblical Literature, 2002. Pp. 286. $39.95 (paper). ISBN 1589830342. In this review it is not possible to look at her treatment of all the texts, so I will direct my comments to three passages from the book of Jeremiah: 4:23-28; 12:1-4, 7-13. Hayes argues that Jer 4:23-28 is a distinct unit (although not necessarily all composed by Jeremiah) and divides it into a prophetic vision (w. 23-26) and a divine speech (vv. 27-28) that "affirms or explains the vision" (p. 69). In w. 23-26 the earth is barely responsive, and there is no indication of human activity. In this way the passage differs significantly from, for example, Hos 4:1-3, where the earth mourns because of the behavior of its inhabitants. Verses 23-26 emphasize the state of the earth, and make only passing reference to actions such as the quaking of mountains and the shaking of hills. In vv. 27-28, however, the earth is a more active figure. Now the earth mourns, the heavens become dark, and the earth becomes a desolation. Hayes points to the presence of similar language about the earth's distress in Nah 1:5-6, where the desolation is the result of the activity of the divine warrior, and concludes that divine warrior imagery is also operative in w. 23-28. Her insight here is important because it helps us better understand the relationship of 4:23-28 to its larger context (chs. 4-6), which is dominated by the imagery of warfare and invasion. In Jer 4:23-28 the earth mourns not specifically because of the behavior of its inhabitants, but because human life may become extinct and the cosmos reduced to desolation. In Jer 12:1-4 the picture is different, and the role of human behavior is central. The destruction of birds and animals is linked to the behavior of the earth's inhabitants. Here the punitive action of YHWH is a secondary theme, whereas in 4:23-28 the immediate cause of the earth's mourning is not the evil behavior of the people but rather the devastating action of YHWH. In 12:1-4 the imagery of the earth mourning is not related to the past and a catastrophe that has already happened, but points to both the present and the future. With regard to the present, the imagery is symptomatic of what is already happening: the withering of the earth and the flourishing of the wicked. With regard to the future, it is a warning of what lies ahead, when the evildoers will be culled and slaughtered like sheep. In Jer 12:7-13 the mourning of the earth is a response to YHWH'S punishment. In this way the imagery functions differently than in 12:1-4, but similarly to that in 4:23-28. In 12:7-13 the destruction is not complete. The earth is an active figure that mourns. …
In-home assessment of dementia by nurses: experience using the CERAD evaluations. Consortium to Establish a Registry for Alzheimer's Disease.

PURPOSE OF STUDY To maximize respondent participation in a study of the prevalence, incidence, and natural history of dementia. DESIGN AND METHODS Clinical research nurses were trained to carry out evaluations for dementia in the home. We describe the assessment and training procedures used and note the advantages and drawbacks of this approach. RESULTS Nurse identification of the presence of dementia agreed well with that of medical specialists (kappa = 0.84), but was slightly poorer regarding type of dementia (kappa = 0.71). IMPLICATIONS Use of nurses for such activity need not be limited to epidemiological studies, but is relevant also in clinical practice.
A Fully Parallel 3D Thinning Algorithm and Its Applications

A thinning algorithm is a connectivity preserving process which is applied to erode an object layer by layer until only a “skeleton” is left. Generally, it is difficult to prove that a 3D parallel thinning algorithm preserves connectivity. Sufficient conditions which can simplify such proofs were proposed recently inCVGIP: Image Understanding(59, No. 3 (1994), 328? 339). One of the purposes of this paper is to propose a connectivity preserving fully parallel 3D thinning algorithm. The other purpose is to show how to use the sufficient conditions to prove a 3D parallel thinning algorithm to be connectivity preserving. By this demonstration, a new generation of 3D parallel thinning algorithms can be designed and proved to preserve connectivity relatively easily.
Injury-induced kinematic compensations within the lower back: impact of non-lower back injuries

With the number of musculoskeletal disorders increasing in the workplace, the potential exists for multiple injuries due to compensations. The objective of this study was to quantify the impact of non-lower back injuries on the trunk motions adopted by the individual during typical lifting tasks. A total of 32 injured subjects (eight for each injury group—shoulder, hand/wrist, knee and foot/ankle) and 32 matched (gender, height and weight) healthy subjects performed laboratory lifting tasks. The independent variables were task asymmetry (clockwise, sagittally symmetric and counter-clockwise), lift origin (waist, knee and floor) and box weight (2.27 and 6.82 kg). The dependent variables were peak trunk kinematics (as measured by the lumbar motion monitor) and moment arm between the box and lower back. The two injuries that had the greatest impact on the lower back kinematics were foot/ankle and hand/wrist. Individuals who suffered a foot/ankle injury produced greater three-dimensional trunk velocities (up to 10°/s) while individuals with hand/wrist injuries slowed down in the sagittal plane but increased the twisting velocity—specifically when lifting from the asymmetric shelves. Knee and shoulder injuries had limited impact on the trunk motions. Overall, the results indicate workplace design must take into account non-lower back injuries.
Trust and Technology Acceptance on Mobile Banking

The advancement in the mobile technology and wireless Internet has transformed banking operations to the mobile devices which enables a customer to do the banking operation at anytime and anywhere. The introduction of smart phones and high-speed Internet made customer to access various services and information at anywhere and banks also started taking advantages of these technologies by offering a wide variety of services through mobile devices. Mobile banking is new to the customer even today in emerging markets. Therefore, it is important to attract customers to use these services. Mobile banking has a wide potential in developing countries as many customers can avail banking services through their mobile phones. In this technology era expecting customers to use banking services through mobile is a demanding task where they have plenty of alternative service channels available. To understand the customer acceptance of mobile banking, this study aims to focus on the role of trust and the impact of technology to use the mobile banking service. There are very limited studies, which focus on the relationship between trust and technology acceptance in the context of mobile banking, which has been studied mostly in an isolated manner (Luarn & Lin, 2005; Chung & Kwon, 2009a, 2009b; Kim et al., 2009; Sripalawat et al., 2011). This paper addresses this gap in the existing literature of mobile banking adoption by studying the role of trust and technology acceptance variables.
Towards a Comprehensive Set of Big Data Benchmarks

This paper reviews the Ogre classification of Big Data application with 50 facets divided into four groups or views. These four correspond to Problem Architecture, Execution mode, Data source and style, and the Processing model used. We then look at multiple existing or proposed benchmark suites and analyze their coverage of the different facets suggesting a process to obtain a complete set. We illustrate this by looking at parallel data analytics benchmarked on multicore clusters.
F-C3D: FPGA-based 3-dimensional convolutional neural network

In recent years, 3-dimension convolutional neural networks (3D CNNs) have been widely used for video analysis, 3-dimension geometric data and medical image diagnosis. While conventional CNNs are computationally intensive, 3D CNNs push the computational requirements into another level, since each computation depends on multiple image frames. This paper describes a novel hardware architecture for a 3D convolutional neural network, and design strategies to resolve memory usage and bandwidth limitations. The proposed architecture F-C3D is implemented on zc706 at 172MHz, showing 231 times speed up compared with software implementation on 1 GHz ARM CPU, 7.4 times speed up on 3.07 GHz Intel CPU and nearly 10 times lower power consumption than GPU.
A Study on Improving Security and Efficiency using Dynamic Ownership Management in Client-Side Deduplication Environments

A R T I C L E I N F O A B S T R A C T Article history: Received: 21 August, 2018 Accepted: 24 September, 2018 Online: 12 October, 2018 Data deduplication technology is used to improve the spatial efficiency of cloud storage. This technology is used for storing data on a cloud and omitting data uploading if the data are already present. However, various security threats may occur during the deduplication process. These security threats include poison attacks and user identity exposure through ownership. In addition, in an environment in which ownership changes in real time, there is a problem in renewing ownership information that has already been issued. Therefore, various studies have been conducted to solve these problems. In this study, a poison attack, real-time ownership management, and ownership anonymization are provided through MLE and dynamic ownership management.
A study of collaboration between university industrial design departments and corporate firms

Research shows design education is concerned with providing an educational experience that helps develop skills and prepare responsible professionals. It has been suggested that collaboration between industrial design departments and industry provides an enriched educational experience for industrial design students. Studying the collaborative project is a step toward gaining a general understanding (a) to look at how the collaborative project contributes toward an enriched educational experience; (b) to examine how design issues are addressed in the collaborative project; and (c) to identify the problems and conflicts that emerge. While every situation has unique qualities and requirements, it is feasible to take findings from one study and apply them to another similar situation, thus this study provides a perspective for the University Technology of MARA (UiTM) in Malaysia. It may help guide curriculum development that balances student needs, educational goals and objectives, and industrial development of Malaysia. The case study method is used to present the collaborative project experience conducted between university design departments and industry. Data is gathered through review of literature, documents, observations and interviews of participating students, instructors and client. The outcomes of the study that are applicable to the industrial design department at UiTM, Malaysia are that the collaborative project experience builds the students' design skills in terms of problem solving, material usage, and working within particular limitations. However, educational objectives need to become a part of the shared vision between industrial design departments and industry that need to be negotiated through the collaboration process. Careful selection of collaborative projects can significantly contribute to design education experience for industrial design students, including the type of product to be designed, the complexity project and the commitment of industry partners. Collaboration can provide a holistic approach opportunity to educate designers and industry.
Attack vulnerability of interdependent local-world networks: The effect of degree heterogeneity

Attack vulnerability is one of the fundamental properties of complex interdependent networks, which has attracted a lot of research efforts in recent years. In this paper, we study the effect of degree heterogeneity on structural vulnerability of interdependent networks when they suffer targeted attacks. Firstly, we construct an interdependent system model composed of two network components. By adjusting a parameter, the extent of degree heterogeneity of each network can be controlled. Then, numerical simulations are implemented to demonstrate the impact of degree heterogeneity. The research results verify that the vulnerability of both single and interdependent networks can be affected by degree heterogeneity, that is, degree heterogeneity can significantly increase the vulnerability of these networks. Additionally, the existence of interdependent links between two networks makes both networks much more vulnerable against targeted attacks. In particular, when coupling preference is taken into account, it is found that compared with disassortative coupling and random coupling, assortative coupling can lead to a more fragile interdependent system. Our research results can give some help on the deep understanding of structural vulnerability of complex interdependent networks, and shed some light on the design of robust systems.
Outlier detection based on neighborhood proximity.

Outliers, also called anomalies are data patterns that do not conform to the behavior that is expected or differ too much from the rest. In some cases, outliers could be caused by errors in data generating/collecting methods or by inherent data variability. However, in many situations, outliers are indications of interesting events that have never been known before and hence, an adaptation of the theory to capture the new events is required to explore the underlying mechanisms. The two-side effect of outliers necessitates the development of efficient methods to detect them for either (a) eliminating/minimizing their impacts on general performance of information systems or (b) capturing the underlying interesting knowledge (e.g. intrusive connections in a network). In general, outlier detection has many practical applications, especially in domains that have scope for abnormal behavior, such as fraud detection, network intrusion detection, medical diagnosis, marketing, customer segmentation, etc. There are many ways in practice to solve our problem of interest. This thesis deals specifically with outlier notions based on measures of neighborhood dissimilarity. Related works can be divided into two main categories: distance-based and density-based. In our study, we place our focus more on distance-based approaches. With considerations to the limitations of existing works, we propose two techniques, tackling separate aspects of outlier detection. Different neighborhood-proximity-based techniques introduce/use different notions of outliers. That makes their performance vary greatly through disparate datasets. Therefore, using only one technique may not yield desired outcome. Motivated by the issue, we present a novel scheme for classifying and combining various outlier detectors in order to exploit their own advantages. The ensemble framework applies each detector on a randomly chosen subspace. Hence, error suffered by one detector is unlikely repeated by others. In high-dimensional spaces, subspace irrelevance is a local rather than a global property. Choosing different subspaces for different detectors helps our technique to overcome the curse of dimensionality. Extensive experiments point out that our method yields better detection accuracy than existing ones on high-dimensional datasets. iii ATTENTION: The Singapore Copyright Act applies to the use of this document. Nanyang Technological University Library