Miracle-dz/UniFAR-FTUs huggingface dataset:
Explicit Knowledge and Tacit Knowledge Sharing

Several researchers suggested that tacit knowledge sharing is much different from explicit knowledge sharing. Accordingly, we extend Bock and his colleagues' works to investigate the differences between the motivators for explicit knowledge sharing and those for tacit knowledge sharing. Results gathered through vignette design with 217 valid responses show that explicit knowledge sharing is stimulated by both extrinsic and intrinsic motivators, while tacit knowledge sharing is stimulated by intrinsic motivators only. Implications and limitations of this study are also discussed in this study.
Taliban’s Resurgence in Afghanistan: The Frame Analysis of Editorials from Selected Pakistani Newspapers

The resurgence of the Afghan Taliban on 15th August 2021 created great tension in the whole world and made the topic debatable all over the world. The present research analyzes the discourse produced on this highly debatable topic. The study entails the frame analysis of the discourse produced in the selected Pakistani editorials. For this purpose, two Pakistani newspapers are selected i-e Dawn and The Express Tribune. The sample is purposive and comprises six editorials, three from each selected newspaper. The sample of the study is taken from 15th August 2021- 31st December 2021. The research is qualitative and the data is analyzed using the Frame Analysis method given by Goffman (1974), and Entman (1993). The in-depth analysis of the study reveals that the Pakistani newspapers’ editorials somehow talk in favor of the Taliban. They frame the event positively while giving recommendations to the Taliban for the bright future of their government. The research is therefore significant because it contributes to the field of linguistics and Frame Analysis.
Advances in Medical Education and Practice Dovepress Video-or Text-based E-learning When Teaching Clinical Procedures? a Randomized Controlled Trial

Background and aims: This study investigated the effectiveness of two different levels of e-learning when teaching clinical skills to medical students. Materials and methods: Sixty medical students were included and randomized into two comparable groups. The groups were given either a video-or text/picture-based e-learning module and subsequently underwent both theoretical and practical examination. A follow-up test was performed 1 month later. Results: The students in the video group performed better than the illustrated text-based group in the practical examination, both in the primary test (P,0.001) and in the follow-up test (P,0.01). Regarding theoretical knowledge, no differences were found between the groups on the primary test, though the video group performed better on the follow-up test (P=0.04). Conclusion: Video-based e-learning is superior to illustrated text-based e-learning when teaching certain practical clinical skills.
From novice to expert: the effect of tutorials on user expertise with spoken dialogue systems

One of the challenges for the current state of the art in spoken dialogue systems is how to make the limitations of the system apparent to users. These limitations have many sources: limited vocabulary, limited grammar, or limitations in the application domain. This study explored the use of a 4-minute tutorial session to acquaint novice users with the features of a spoken dialogue system for accessing email. On a set of three scenariobased tasks, novice users who had the tutorial had task completion times and user satisfaction ratings that were comparable to those of expert users of the system. Novices who did not experience the tutorial had significantly longer task completion times on the initial task, but similar completion times to the tutorial group on the final task. User satisfaction ratings of the no-tutorial group were consistently lower than the ratings of the tutorial and the expert groups. Evaluation using the PARADISE [7] framework indicated that perceived task completion, mean recognition score, and number of help requests were significant predictors of user satisfaction with the system.
Importance of Monocyte Chemoattractant Protein-1 Pathway in Neointimal Hyperplasia After Periarterial Injury in Mice and Monkeys

Neointimal hyperplasia is a major cause of restenosis after coronary intervention. Because vascular injury is now recognized to involve an inflammatory response, monocyte chemoattractant protein-1 (MCP-1) might be involved in underlying mechanisms of restenosis. In the present study, we demonstrate the important role of MCP-1 in neointimal hyperplasia after cuff-induced arterial injury. In the first set of experiments, placement of a nonconstricting cuff around the femoral artery of intact mice and monkeys resulted in inflammation in the early stages and subsequent neointimal hyperplasia at the late stages. We transfected with an N-terminal deletion mutant of the human MCP-1 gene into skeletal muscles to block MCP-1 activity in vivo. This mutant MCP-1 works as a dominant-negative inhibitor of MCP-1. This strategy inhibited early vascular inflammation (monocyte infiltration, increased expression of MCP-1, and inflammatory cytokines) and late neointimal hyperplasia. In the second set of experiments, the cuff-induced neointimal hyperplasia was found to be less in CCR2-deficient mice than in control CCR2+/+ mice. The MCP-1/CCR2 pathway plays a central role in the pathogenesis of neointimal hyperplasia in cuffed femoral artery of mice and monkeys. Therefore, the MCP-1/CCR2 pathway can be a therapeutic target for human restenosis after coronary intervention.
Locally Testable Codes Require Redundant Testers

Locally testable codes (LTCs) are error-correcting codes for which membership, in the code, of a given word can be tested by examining it in very few locations. Most known constructions of locally testable codes are linear codes, and give error-correcting codes whose duals have (superlinearly) {\em many} small weight codewords. Examining this feature appears to be one of the promising approaches to proving limitation results for (i.e., upper bounds on the rate of) LTCs. Unfortunately till now it was not even known if LTCs need to be non-trivially redundant, i.e., need to have {\em one} linear dependency among the low-weight codewords in its dual. In this paper we give the first lower bound of this form, by showing that every positive rate constant query strong LTC must have linearly many redundant low-weight codewords in its dual. We actually prove the stronger claim that the {\em actual test itself} must use a linear number of redundant dual codewords (beyond the minimum number of basis elements required to characterize the code); in other words, non-redundant (in fact, low redundancy) local testing is impossible.
Amorphous thin-film growth: Theory compared with experiment

Experimental results on amorphous ZrAlCu thin-film growth and the dynamics of the surface morphology as predicted from a minimal nonlinear stochastic deposition equation are analysed and compared. Key points of this study are: i) an estimation procedure for coefficients entering into the growth equation and ii) a detailed analysis and interpretation of the time evolution of the correlation length and the surface roughness. The results corroborate the usefulness of the deposition equation as a tool for studying amorphous growth processes.
Bayesian Analysis for Longitudinal Semicontinuous Data

In many biomedical applications, researchers encounter semicontinuous data whereby data are either continuous or zero. When the data are collected over time the observations are correlated. Analysis of these kind of longitudinal semi-continuous data is challenging due to the presence of strong skewness in the data. In this paper, we develop a ∞exible class of zero-in∞ated models in a longitudinal setting. Improving on a likelihood-based approach (using Monte-Carlo EM) that was proposed by Albert and Shen (2005), we use a Bayesian approach to analyze longitudinal data from a acupuncture clinical trial in which we compare the efiects of active acupuncture, sham acupuncture and standard medical care on chemotherapy-induced nausea in patients being treated for advanced stage breast cancer. A penalized spline model is introduced into the linear predictor of the model to explore the possibility of nonlinear treatment efiect. The subject-speciflc efiects involved in the model are assumed to follow a nonparametric Dirichlet process (DP) mixture. We also account
Understanding the Variation of Software Development Tasks: a Qualitative Study

In order to reduce cost, get to market faster and utilize global talents, large companies often organize their software development globally (distributed over Internet), a paradigm advocated by Internetware. Considering the complexity of distributed software development, it is important to understand the variation of various tasks, so the projects could work more efficiently on plan formulation, personnel organization, or task allocation. The main goal of this paper is to understand the variations of software development tasks. We conduct an interview with 47 interviewees and a survey with 148 people from 15 projects with different size and domain.Through the analysis of interviews and surveys, we find that a software task could be characterized through three aspects: value, difficulty and centrality. Among them, task value is influenced by the role of stakeholders and project context, and is related to the task difficulty and task centrality. Task difficulty is reflected by technology, domain difference, working relationships, customer related issues, and it is also related to the developers' personalities. Task centrality can be described by customer impact, system-wide impact, team impact and future impact. We believe our results can help project managers to optimize task allocation, or adjust project plan, and thus achieve efficient development.
Sysiphus: Enabling informal collaboration in global software development

In global software projects, informal communication across sites is severely hampered, making it difficult to disseminate implicit knowledge. Participants have a partial view of the overall organization, do not have access to the complete rationale behind decisions, and when changes arise, participants from other sites are surprised. Consequently, issues that could be clarified almost immediately require days until the relevant stakeholders are identified, the issues are understood, and a resolution is agreed upon. We focus on the specific problem of externalizing issues with their context, stakeholders, and organizational roles in distributed settings. The challenge is to capture sufficient knowledge as a side effect of development, while structuring it for long-term use. We describe Sysiphus, a distributed environment providing a uniform framework for system models, collaboration artifacts, and organizational models. Sysiphus encourages participants to make communication and issues explicit in the context of system models and become aware of relevant stakeholders
Dynamic Regulation of Mitotic Arrest in Fetal Male Germ Cells

During fetal mouse development, germ cells enter the developing gonad at embryonic day (E) 10–11. In response to signaling from the male or female gonad, the germ cells commit either to spermatogenesis at E12.5 and enter mitotic arrest or to oogenesis and enter meiotic arrest at E13.5. It is unclear whether male commitment of the germ line and mitotic arrest are directly associated or whether they are developmentally separate. In addition, the published data describing the timing of mitotic arrest are inconsistent, and the molecular processes underlying the control of the cell cycle during mitotic arrest also remain unknown. Using flow cytometric techniques, 5‐bromo‐2′‐deoxyuridine labeling, and immunofluorescent analysis of cell proliferation, we have determined that germ cells in the embryonic mouse testis arrest in G0 during E12.5 and E14.5. This process is gradual and occurs in an unsynchronized manner. We have also purified germ cells and analyzed molecular changes in male germ cells as they exit the cell cycle. This has allowed us to identify a series of molecular events, including activation of p27Kip1, p15INK4b, and p16INK4a; the dephosphorylation and degradation of retinoblastoma protein; and the suppression of CyclinE, which lead to mitotic arrest. For the first time, the data presented here accurately define the mitotic arrest of male germ cells by directly combining the analysis of cell cycle changes with the examination of functionally defined cell cycle regulators.
Spatial Interpolation Using Multiple Regression

Many real world data mining applications involve analyzing geo-referenced data. Frequently, this type of data sets are incomplete in the sense that not all geographical coordinates have measured values of the variable(s) of interest. This incompleteness may be caused by poor data collection, measurement errors, costs management and many other factors. These missing values may cause several difficulties in many applications. Spatial imputation/interpolation methods try to fill in these unknown values in geo-referenced data sets. In this paper we propose a new spatial imputation method based on machine learning algorithms and a series of data pre-processing steps. The key distinguishing factor of this method is allowing the use of data from faraway regions, contrary to the state of the art on spatial data mining. Images (e.g. from a satellite or video surveillance cameras) may also suffer from this incompleteness where some pixels are missing, which again may be caused by many factors. An image can be seen as a spatial data set in a Cartesian coordinates system, where each pixel (location) registers some value (e.g. degree of gray on a black and white image). Being able to recover the original image from a partial or incomplete version of the reality is a key application in many domains (e.g. surveillance, security, etc.). In this paper we evaluate our general methodology for spatial interpolation on this type of problems. Namely, we check the ability of our method to fill in unknown pixels on several images. We compare it to state of the art methods and provide strong experimental evidence of the advantages of our proposal.
Linear Precoding for the MIMO Multiple Access Channel With Finite Alphabet Inputs and Statistical CSI

In this paper, we investigate the design of linear precoders for the multiple-input-multiple-output (MIMO) multiple access channel (MAC). We assume that statistical channel state information (CSI) is available at the transmitters and consider the problem under the practical finite alphabet input assumption. First, we derive an asymptotic (in the large system limit) expression for the weighted sum rate (WSR) of the MIMO MAC with finite alphabet inputs and Weichselberger's MIMO channel model. Subsequently, we obtain the optimal structures of the linear precoders of the users maximizing the asymptotic WSR and an iterative algorithm for determining the precoders. We show that the complexity of the proposed precoder design is significantly lower than that of MIMO MAC precoders designed for finite alphabet inputs and instantaneous CSI. Simulation results for finite alphabet signaling indicate that the proposed precoder achieves significant performance gains over existing precoder designs.
Impact of the Ratio of Metastatic to Examined Lymph Nodes on the Survival of Early-Stage Cervical Cancer Patients

Background: The aim of the study was to determine the impact of the ratio of metastatic to examined lymph nodes (LN) on the survival of early-stage cervical cancer patients. Methods: A retrospective review was performed of all patients undergoing primary radical hysterectomy and pelvicparaaortic lymphadenectomy for stage I–II cervical cancer at the Ankara Oncology Hospital from 1995 to 2000. Survival was determined by Kaplan-Meier method and differences were assessed by log-rank test. Results: A total of 2,085 LN were examined. Nodal metastasis was found in 22.1% of the patients. Patients with zero involved LN had a 5-year survival of 89.19%, while patients with 1 positive LN and > 1 positive LNs had a 5-year survival of 100 and 76.92%, respectively. The difference in survival among these three groups was not statistically significant. The 5-year survival rates according to the metastatic/examined LN ratio (LNR) were 75, 90, and 89.19% in the groups of patients with LNR >10, 1–10, and 0%, respectively. The difference in survival among these three groups was not statistically significant. Conclusions: This factor might be helpful for a better prognostic discrimination of patients with metastatic LN. The stratification of node-positive cervical cancer for prognostic and treatment purposes warrants further investigation.
Blow-up in multidimensional aggregation equations with mildly singular interaction kernels

We consider the multidimensional aggregation equation ut − ∇· (u∇K * u) = 0 in which the radially symmetric attractive interaction kernel has a mild singularity at the origin (Lipschitz or better). In the case of bounded initial data, finite time singularity has been proved for kernels with a Lipschitz point at the origin (Bertozzi and Laurent 2007 Commun. Math. Sci. 274 717–35), whereas for C2 kernels there is no finite-time blow-up. We prove, under mild monotonicity assumptions on the kernel K, that the Osgood condition for well-posedness of the ODE characteristics determines global in time well-posedness of the PDE with compactly supported bounded nonnegative initial data. When the Osgood condition is violated, we present a new proof of finite time blow-up that extends previous results, requiring radially symmetric data, to general bounded, compactly supported nonnegative initial data without symmetry. We also present a new analysis of radially symmetric solutions under less strict monotonicity conditions. Finally, we conclude with a discussion of similarity solutions for the case K(x) = |x| and some open problems.
Facilitation and restoration of cognitive function in primate prefrontal cortex by a neuroprosthesis that utilizes minicolumn-specific neural firing

Objective. Maintenance of cognitive control is a major concern for many human disease conditions; therefore, a major goal of human neuroprosthetics is to facilitate and/or recover the cognitive function when such circumstances impair appropriate decision making. Approach. Minicolumnar activity from the prefrontal cortex (PFC) was recorded from nonhuman primates trained to perform a delayed match to sample (DMS), via custom-designed conformal multielectrode arrays that provided inter-laminar recordings from neurons in the PFC layer 2/3 and layer 5. Such recordings were analyzed via a previously demonstrated nonlinear multi-input–multi-output (MIMO) neuroprosthesis in rodents, which extracted and characterized multicolumnar firing patterns during DMS performance. Main results. The MIMO model verified that the conformal recorded individual PFC minicolumns responded to entrained target selections in patterns critical for successful DMS performance. This allowed the substitution of task-related layer 5 neuron firing patterns with electrical stimulation in the same recording regions during columnar transmission from layer 2/3 at the time of target selection. Such stimulation improved normal task performance, but more importantly, recovered performance when applied as a neuroprosthesis following the pharmacological disruption of decision making in the same task. Significance. These findings provide the first successful application of neuroprosthesis in the primate brain designed specifically to restore or repair the disrupted cognitive function.
Detecting the Presence of Cyberbullying Using Computer Software

Cyberbullying is willful and repeated harm inflicted through the medium of electronic text. Computer software was developed to detect the presence of cyberbullying in online chat conversations. Rules based on a dictionary of key words are used to classify a window of posts. A truth set of MySpace threads was created. The software was found to correctly identify windows containing cyberbullying 85.30% of the time, and it identifies innocent windows 51.91% of the time. The overall accuracy is 58.63%. This suggests that our coding rules must be refined to not falsely flag so much innocent conversation.
Human milk feedings and infection among very low birth weight infants.

BACKGROUND Preterm infants are immunologically immature at birth. Previous studies have demonstrated that human milk protects against infection in full-term infants, but there are few studies of its effect for preterm infants. OBJECTIVE To examine the effect of human milk feedings on infection incidence among very low birth weight (VLBW) infants during their initial hospitalization. STUDY DESIGN The sample consisted of 212 consecutive VLBW infants admitted to the Georgetown University Medical Center neonatal intensive care unit (NICU) during 1992-1993 and surviving to receive enteral feeding. Type of feeding (human milk vs formula), presence of infection and sepsis/meningitis (clinical signs and positive cultures for pathogenic organisms), and potential confounding variables were abstracted from medical records. Multiple logistic regression was used to control for confounders. RESULTS The incidence of infection (human milk [29.3%] vs formula [47.2%]) and sepsis/meningitis (human milk [19.5%] vs formula [32.6%]) differed significantly by type of feeding. Major risk factors for infection were similar in both groups. Human milk feeding was independently correlated with a reduced odds of infection (odds ratio [OR] = 0.43; 95% confidence interval [CI]: 0.23-0.81), controlling for gestational age, 5-minute Apgar score, mechanical ventilation days, and days without enteral feedings; and was independently correlated with a reduced odds of sepsis/meningitis (OR = 0.47, 95% CI:0.23-0. 95), controlling for gestational age, mechanical ventilation days, and days without enteral feedings. CONCLUSIONS The incidence of any infection and sepsis/meningitis are significantly reduced in human milk-fed VLBW infants compared with exclusively formula-fed VLBW infants.