Miracle-dz/UniFAR-FTUs huggingface dataset:
A behavioral perspective on IT project risk management: a three-essay thesis

This thesis studies information technology (IT) project risk management from a behavioral perspective. Prior studies suggest that IT project managers’ perceived risk exposure (i.e., subjective assessment of threats to projects’ objectives) and risk response decisions (i.e., subjective plans to perform project management activities in order to reduce risks) are sometimes different from the prescriptions in the literature. Based on the premise that a better understanding of IT project managers’ actual risk management behavior can help develop risk management practices that are better suited to their needs, this thesis aims to take a step in this direction. To do so, the thesis comprises three standalone but interrelated essays. Essay 1—a problematization-based literature review—studies what the previous IT project risk management literature, as a whole, assumes for normative purposes. It first invokes the premise that alternative conceptual assumptions about the same concepts could coexist in the literature to enable alternative research objectives. It then develops an alternative assumption set for the purpose of behavioral theory building and offers a number of directions for future research. Essay 2—a qualitative piece—examines two types of risk assessment processes: experiential and analytical processes. It sheds some light on the use of experiential risk assessment processes, including the use of heuristics and relying upon expertise-based intuition. It offers several propositions on the determinants of preferring experiential or analytical risk assessment processes in IT projects. Essay 3—a survey—develops a model of the antecedents of IT project managers’ intention to enact certain specific risk responses. It then instantiates the model for three specific risk responses, enriches each instance with the salient beliefs of a sample of IT project managers, and tests each instance using a separate survey. This thesis contributes by 1) proposing a set of decision-making assumptions that can be used in behavioral theories of risk management and offering several avenues for future research in the form of research questions, 2) developing propositions on the determinants of preferring experiential or analytical risk assessment processes, and 3) developing and validating a model that revisits the effect of perceived risk exposure on the risk-response intention of IT project managers.
Quantifying the cumulative effect of low-penetrance genetic variants on breast cancer risk

Many common diseases have a complex genetic basis in which large numbers of genetic variations combine with environmental factors to determine risk. However, quantifying such polygenic effects has been challenging. In order to address these difficulties we developed a global measure of the information content of an individual's genome relative to a reference population, which may be used to assess differences in global genome structure between cases and appropriate controls. Informally this measure, which we call relative genome information (RGI), quantifies the relative “disorder” of an individual's genome. In order to test its ability to predict disease risk we used RGI to compare single‐nucleotide polymorphism genotypes from two independent samples of women with early‐onset breast cancer with three independent sets of controls. We found that RGI was significantly elevated in both sets of breast cancer cases in comparison with all three sets of controls, with disease risk rising sharply with RGI. Furthermore, these differences are not due to associations with common variants at a small number of disease‐associated loci, but rather are due to the combined associations of thousands of markers distributed throughout the genome. Our results indicate that the information content of an individual's genome may be used to measure the risk of a complex disease, and suggest that early‐onset breast cancer has a strongly polygenic component.
Alkaloids of fascaplysin are effective conventional chemotherapeutic drugs, inhibiting the proliferation of C6 glioma cells and causing their death in vitro

Glioblastoma multiforme is an invasive malignant glial brain tumor with a poor prognosis for patients. The primary reasons that lead to the development of treatment resistance are associated with tumor cells infiltrating the brain parenchyma and the specific properties of tumor stem cells. A crucial research area in medical science is the search for effective agents that are able to act on these targets. Fascaplysin alkaloids possess potent antitumor activity. Modern methods for the targeted delivery of drugs reveal extensive possibilities in terms of the clinical use of these compounds. The aim of the present study was to establish effective concentrations of fascaplysin that inhibit the growth and kill the cells of glial tumors, as well as to perform a comparative analysis of fascaplysin's effectiveness in relation to other chemotherapy drugs. C6 glioma cells were utilized as an optimal model of glioblastoma. It was established that fascaplysin at 0.5 µM has a strong cytotoxic effect, which is subsequently replaced by tumor cell death via apoptosis as the length of drug exposure time is increased. Fascaplysin kills glioma cells at a dose higher than 0.5 µM. The efficiency of fascaplysin was observed to significantly exceed that of temozolomide. Therefore, a significant feature of fascaplysin is its ability to inhibit the growth of and kill multipotent tumor cells.
Prognostic precipitation with three liquid water classes in the ECHAM5–HAM GCM

Abstract. A new parameterization with three prognostic liquid water classes was implemented into the general circulation model (GCM) ECHAM5 with the aerosol module HAM in order to improve the global representation of rain formation in marine stratiform clouds. The additionally introduced drizzle class improves the physical representation of the droplet spectrum and, more importantly, improves the microphysical processes relevant for precipitation formation compared to the standard parameterization. In order to avoid a mismatch of the liquid and ice phase, a prognostic treatment of snow has been introduced too. This has a significant effect on the amount and altitude of ice clouds, which in turn affects not only the in- and outgoing radiation but also the parameterized collection rates. With the introduction of a prognostic precipitation scheme, a more realistic representation of both liquid and ice phase large-scale precipitation is achieved compared to a diagnostic treatment. An encouraging finding is that with the prognostic treatment the increase of the liquid water path in response to anthropogenic aerosols is reduced by about 25 %. Although the total net radiative forcing is decreased from −1.3±0.3 to −1.6±0.3 W m −2 from the control to the prognostic model version, the difference is within the interannual variability. Altogether the results suggest that the treatment of precipitation in global circulation models has not only a significant influence on the phase of clouds and their conversion rates, but also hints towards uncertainties related to a prognostic precipitation scheme.
DOPAMINE D1/5 RECEPTOR-MEDIATED LTP OF INTRINSIC EXCITABILITY IN RAT PREFRONTAL CORTICAL NEURONS: Ca-DEPENDENT INTRACELLULAR SIGNALING

Prefrontal Cortex (PFC) dopamine D1/5 receptors modulate long-and short-term neuronal plasticity which may contribute to cognitive functions. Synergistic to synaptic strength modulation, direct post-synaptic D1/5 receptor activation also modulates voltage-dependent ionic currents that regulate spike firing, thus altering the neuronal input-output relationships in a process called long-term potentiation of intrinsic excitability (LTP-IE). Here, the intracellular signals that mediate this D1/5 receptor-dependent LTP-IE were determined using whole-cell current-clamp recordings in layer V-VI rat pyramidal neurons from PFC slices. Following blockade of all major amino acid receptors (V HOLD =-65mV) brief tetanic stimulation (20 Hz) of local afferents or application of the D1 agonist SKF81297 (0.2–50µM) induced LTP-IE, as shown by a prolonged (>40mins) increase in depolarizing pulse-evoked spike firing.
Hypoxia, Overnight Wear, and Tear Stagnation Effects on the Corneal Epithelium: Data and Proposed Model

Purpose. To explore the possible mechanisms that may lead to overnight contact lens–associated corneal morbidity by examining data from several corneal epithelial permeability experiments obtained under different environmental and lens fitting paradigms. Methods. Epithelial permeability was assessed by using fluorometry to determine the fluorescein penetration rate from the tear film into the corneal stroma. Changes in this rate provide an index of the corneal epithelial status; increased permeability leads to decreased barrier function. Results. Hypoxia and tear stagnation during overnight lens wear play a significant role in altering the corneal epithelial barrier function (P<0.05). However, eliminating lens-induced hypoxia alone does not ameliorate changes in epithelial status (P<0.05). Conclusions. Based on data from these experiments, it is suggested that hypoxia and tear stagnation should be eliminated to minimize alteration of the corneal epithelium associated with overnight contact lens wear.
Development Of A Pattern Recognition-Based Myoelectric Transhumeral Prosthesis With Multifunctional Simultaneous Control Using A Model-Driven Approach For Mechatronic Systems

Modern components and materials in combination with recent pattern recognition methods for electromyographic (EMG) signals enable creating multi-functional arm prostheses with intelligent and user-friendly control [1]. While the usage of pattern recognition of features extracted from EMG signals has proven highly efficient in transradial prostheses [2,3], most current transhumeral prostheses utilize the amplitude of EMG signals from residual arm muscles to control open and close the hand. Co-contracting the muscles usually performs a switch to a different mode like flexion and extension of the elbow, which is cumbersome and does not allow simultaneous movements.
Reviving Bruce: negotiating Asian masculinity through Bruce Lee paratexts in Giant Robot and Angry Asian Man

ABSTRACT These two case studies of the work of independent Asian American media producers show how Asian American audiences might construct paratexts for Bruce Lee’s work that address and undermine dominant stereotypes while also enabling a distinct “zone of transaction” between Asian American audiences and Lee’s films. By tracing the circulation and ideological investments of a Bruce Lee t-shirt manufactured by the Asian American ‘zine Giant Robot and the kung fu action figure that appears as the homepage image for the influential blog Angry Asian Man, we can understand the construction of Asian American masculinity at the nexus of hegemonic white masculinity, denigrated African American masculinity, and highly gendered “outsider” and nerd cultures.
Political Uncertainty and Public Financing Costs: Evidence from U.S. Gubernatorial Elections and Municipal Bond Markets

This research investigates how political uncertainty around U.S. gubernatorial elections influences the borrowing costs of public debt, measured by yields of municipal bonds. We find that yields of municipal bonds increase sharply by 6 to 8 basis points before elections and then reverse afterward. Elections have more pronounced impact during economic downturns, when outcomes are less predictable, and when states have more outstanding debt. Several state institutions, such as GAAP-budgeting, spending limits and tax-increase limits, help to mitigate the adverse impact of political uncertainty. Evidence from detailed municipal bonds transactions suggests that declining demand due to investor aversion to political uncertainty is the driving force behind the increases in yields prior to elections. The findings suggest that investors are averse to political uncertainty and demand compensation for bearing this risk.
Coffee drinking and risk of endometrial cancer—A population‐based cohort study

Coffee drinking has been reported to have beneficial effects on insulin resistance, which has been directly associated with endometrial cancer. Although a relationship between coffee consumption and endometrial cancer risk is biologically plausible, this hypothesis has been previously explored in only 2 prospective studies, with a small number of cases. We used data from the Swedish Mammography Cohort, a population‐based prospective cohort study of 60,634 women. During 17.6 years of follow‐up, 677 participants were diagnosed with incident endometrial cancer (adenocarcinoma). We examined the association between self‐reported coffee consumption (at baseline 1987–90 and in 1997) and endometrial cancer risk using Cox proportional hazards models. Each additional cup (200 g) of coffee per day was associated with a rate ratio (RR) of 0.90 [95% confidence interval (CI), 0.83–0.97]. In women drinking 4 or more cups of coffee a day, the RR for the risk reduction of endometrial cancer was 0.75 (95% CI, 0.58–0.97) when compared with those who drank 1 cup or less. The association seemed largely confined to overweight and obese women, who showed a respective risk reduction of 12% (95% CI, 0–23%) and 20% (95% CI, 7–31%) for every cup of coffee, but was not observed among normal‐weight women. There was a statistically significant interaction between coffee consumption and body mass index (pinteraction < 0.001). These data indicate that coffee consumption may be associated with decreased risk of endometrial cancer, especially among women with excessive body weight. If confirmed by other prospective studies, these results are of major public health significance. © 2009 UICC
Effects of Sleeve Gastrectomy in Neonatally Streptozotocin-Induced Diabetic Rats

Background Sleeve gastrectomy (SG) has emerged recently as a stand-alone bariatric procedure to treat morbid obesity and enhance glucose homeostasis. The aim of the study was to evaluate its effects in neonatally streptozotocin (STZ)-induced diabetic rats (n-STZ diabetic rats). Methodology and Principal Findings To induce diabetes, STZ (90 mg/kg) was administered intraperitoneally to 2-day-old male pups. When 12 weeks old, diabetic rats were randomized into sleeve operation group (SLG, n = 6) and sham operation group (SOG, n = 6). Body weights were monitored weekly, and daily consumption of water and food were followed for eight consecutive weeks postoperatively. Serum glucose levels were measured periodically at the 4th and 8th week after surgery. Insulin, ghrelin, glucose-dependent insulinotropic polypeptide (GIP) and Glucagon-like peptide-1 (GLP-1) levels were assayed at the end of the study. Our data showed that SLG rats exhibited significantly lower body weight gain in addition to reduced food and water intakes postoperatively compared to their sham-operation counterparts. However, resolution of diabetes was not observed in our study. Correspondingly, there were no significant differences between SOG rats and SLG rats in glucose metabolism-associated hormones, including insulin, GIP and GLP-1. In contrast, ghrelin level significantly decreased (P<0.01) in SLG group (58.01±3.75 pg/ml) after SG surgery compared to SOG group (76.36±3.51 pg/ml). Conclusions These observations strongly suggest that SG is effective in controlling body weight. However, SG did not achieve resolution or improvement of diabetes in n-STZ diabetic rats.
Everyday learning at work: communities of practice in TAFE.

Ongoing restructuring, new types of students, changes in systems and the movement of staff within sections and institutes are only some of the daily challenges facing practitioners in many areas of TAFE as they grapple with the notion of organisational flexibility and customer responsiveness. This paper looks at how members of four workgroups based in two metropolitan institutes are dealing with challenges through informal learning. This paper draws from preliminary findings of an Australian Research Council collaborative research project concerned with determining the significance of informal learning and its contribution to organisational performance. The project is currently midway through and has completed interviews and held feedback sessions with members of four workgroups undertaking quite different types of work. While the project is based in an educational organisation, the major focus of the research project is on TAFE as a workplace. Wenger has written extensively on communities of practice and his work provides a new perspective for viewing learning occurring in workplaces (Wenger, 1998). This paper draws from Wenger’s theoretical work and views the four workgroups from the point of view of communities of practice. In doing so, it enables many of the everyday work practices of the workgroups to be articulated as ‘learning’. This offers potential for learning and development because it begins to foreground practices within TAFE that may foster informal learning environments and strengthen what is already occurring in these communities.
An Efficient and Self-Adapting Localization in Static Wireless Sensor Networks

Localization is one of the most important subjects in Wireless Sensor Networks (WSNs). To reduce the number of beacons and adopt probabilistic methods, some particle filter-based mobile beacon-assisted localization approaches have been proposed, such as Mobile Beacon-assisted Localization (MBL), Adapting MBL (A-MBL), and the method proposed by Hang et al. Some new significant problems arise in these approaches, however. The first question is which probability distribution should be selected as the dynamic model in the prediction stage. The second is whether the unknown node adopts neighbors’ observation in the update stage. The third is how to find a self-adapting mechanism to achieve more flexibility in the adapting stage. In this paper, we give the theoretical analysis and experimental evaluations to suggest which probability distribution in the dynamic model should be adopted to improve the efficiency in the prediction stage. We also give the condition for whether the unknown node should use the observations from its neighbors to improve the accuracy. Finally, we propose a Self-Adapting Mobile Beacon-assisted Localization (SA-MBL) approach to achieve more flexibility and achieve almost the same performance with A-MBL.
Arterial blood pressure parameter estimation and tracking using particle filters

In this paper, we present a computationally efficient method for adaptive tracking of physiological parameters such as heart rate and respiratory rate from the arterial blood pressure (ABP) measurement using particle filters. A previously reported estimation and tracking method was based on approximating the nonlinear models to linear ones based on the extended Kalman filters. However, the dynamic state-space model of the time-varying parameters and the ABP measurement is highly nonlinear in nature. In addition, the periodic nature of many of the time-varying parameters tend to make the estimation and tracking problem ill posed. In this light, the Rao-Blackwellized particle filtering method is proposed to adaptively estimate and track those parameters. The Rao-Blackwellized particle filter is capable of estimating the time-varying parameters of a nonlinear state-space model without performing any linear approximations while being computationally efficient. We demonstrate the performance improvements of our proposed method through computer simulations.
True and False DRM Memories: Differences Detected with an Implicit Task

Memory is prone to illusions. When people are presented with lists of words associated with a non-presented critical lure, they produce a high level of false recognitions (false memories) for non-presented related stimuli indistinguishable, at the explicit level, from presented words (DRM paradigm). We assessed whether true and false DRM memories can be distinguished at the implicit level by using the autobiographical IAT (aIAT), a novel method based on indirect measures that permits to detect true autobiographical events encoded in the respondent’s mind/brain. In our experiment, after a DRM task participants performed two aIATs: the first aimed at testing implicit memory for presented words (true-memories aIAT) and the second aimed at evaluating implicit memory for critical lures (false-memories aIAT). Specifically, the two aIATs assessed the association of presented words and critical lures with the logical dimension “true. ” Results showed that the aIAT detected a greater association of presented words than critical lures with the logical dimension “true. ” This result indicates that although true and false DRM memories are indistinguishable at the explicit level a different association of the true and false DRM memories with the logical dimension “true” can be detected at the implicit level, and suggests that the aIAT may be a sensitive instrument to detect differences between true and false DRM memories.
Signaling Pathways Controlling Microglia Chemotaxis

Microglia are the primary resident immune cells of the central nervous system (CNS). They are the first line of defense of the brain’s innate immune response against infection, injury, and diseases. Microglia respond to extracellular signals and engulf unwanted neuronal debris by phagocytosis, thereby maintaining normal cellular homeostasis in the CNS. Pathological stimuli such as neuronal injury induce transformation and activation of resting microglia with ramified morphology into a motile amoeboid form and activated microglia chemotax toward lesion site. This review outlines the current research on microglial activation and chemotaxis.
Survey of STT-MRAM Cell Design Strategies

Spin-Transfer Torque Random Access Memory (STT-MRAM) has been explored as a post-CMOS technology for embedded and data storage applications seeking non-volatility, near-zero standby energy, and high density. Towards attaining these objectives for practical implementations, various techniques to mitigate the specific reliability challenges associated with STT-MRAM elements are surveyed, classified, and assessed in this article. Cost and suitability metrics assessed include the area of nanomagmetic and CMOS components per bit, access time and complexity, sense margin, and energy or power consumption costs versus resiliency benefits. Solutions to the reliability issues identified are addressed within a taxonomy created to categorize the current and future approaches to reliable STT-MRAM designs. A variety of destructive and non-destructive sensing schemes are assessed for process variation tolerance, read disturbance reduction, sense margin, and write polarization asymmetry compensation. The highest resiliency strategies deliver a sensing margin above 300mV while incurring low power and energy consumption on the order of picojoules and microwatts, respectively, and attaining read sense latency of a few nanoseconds down to hundreds of picoseconds for non-destructive and destructive sensing schemes, respectively.