Miracle-dz/UniFAR-FTUs huggingface dataset:
Working together: Exploring the factors that influence interorganizational cooperation

Administrative and policy failures increasingly occur because of the inability of organizations to facilitate collective action in the absence of a central, hierarchical authority. I explore how organizations achieve (or fail to achieve) voluntary, self-organizing collective action that is not a direct result of external control, presenting a polycentric system of governance within a set of public, nonprofit, and for-profit agencies operating in the policy domain of emergency management. Using a complex adaptive systems framework (Axelrod and Cohen 1999), I identify the patterns of variation, interaction, and the choices made among agencies that determine whether organizations work together. I develop a model of an integrated, interdependent system of emergency management facilitated by a knowledge commons, as opposed to the established sequential cycle of disaster response. The research problem addressed, collective action without hierarchy, is fundamentally an issue of decision making. The ability of decision makers to recognize key situations in their environments and develop strategies for action, i.e. cognition, is critical. Analysis of network data and semi-structured interviews finds that urgent need, proximity, and professional capital, a concept developed in this dissertation, promote and sustain cooperation. I show how these factors increase the capacity of heterogeneous networks to accomplish shared goals. Even if the conditions of urgent need and proximity are satisfied, situations exist where agencies fail to cooperate. Key standards of professional performance—appearance, levels of staffing, past performance, response time, and the quality of equipment—influence the decisions of emergency managers to work together. I present the concept of professional capital to describe how these recognized standards of professional performance demonstrate competence and justify the decisions of managers to interact. Professional capital transcends jurisdictional and disciplinary boundaries, influencing the confidence of decision makers and shaping judgments based on expectations of performance. This concept adds a missing component to social capital theory, which currently focuses on the roles of pre-established trust and norms of reciprocity in promoting collective action.
Tactile sensor and algorithm to detect slip in robot grasping processes

In this paper we introduce a tactile slip sensor for an anthropomorphic robot hand, the measurement circuit and the corresponding algorithm to determine slip states. The main slip sensor components consist of a silicone rubber surface which covers a PVDF sensor. After the amplification of the signal it is processed by a discrete short-time Fourier transform. The resulting spectrogram is processed by a principal component analysis to determine the main signal components. For a classification of three states (‘slip’, ‘signal but no slip’ and ‘noise’) a k-nearest neighbour classifier has been trained with the main signal components and serves for discrimination of slip states on the sensor's surface. The build-up of the sensor and the experimental setup will be briefly explained, the signal processing and the results will be discussed in detail.
The demographic and morphological features of rotator cuff disease. A comparison of asymptomatic and symptomatic shoulders.

BACKGROUND Very little comparative information is available regarding the demographic and morphological characteristics of asymptomatic and symptomatic rotator cuff tears. This information is important to provide insight into the natural history of rotator cuff disease and to identify which factors may be important in the development of pain. The purpose of the present study was to compare the morphological characteristics and prevalences of asymptomatic and symptomatic rotator cuff disease in patients who presented with unilateral shoulder pain. METHODS Five hundred and eighty-eight consecutive patients in whom a standardized ultrasonographic study had been performed by an experienced radiologist for the assessment of unilateral shoulder pain were evaluated with regard to the presence and size of rotator cuff tears in each shoulder. The demographic factors that were analyzed included age, gender, side, and cuff thickness. All of these factors were evaluated with regard to their correlation with the presence of pain. RESULTS Of the 588 consecutive patients who met the inclusion criteria, 212 had an intact rotator cuff bilaterally, 199 had a unilateral rotator cuff tear (either partial or full thickness), and 177 had a bilateral tear (either partial or full thickness). The presence of rotator cuff disease was highly correlated with age. The average age was 48.7 years for patients with no rotator cuff tear, 58.7 years for those with a unilateral tear, and 67.8 years for those with a bilateral tear. Logistic regression analysis indicated a 50% likelihood of a bilateral tear after the age of sixty-six years (p < 0.01). In patients with a bilateral rotator cuff tear in whom one tear was symptomatic and the other tear was asymptomatic, the symptomatic tear was significantly larger (p < 0.01). The average size of a symptomatic tear was 30% greater than that of an asymptomatic tear. Overall, patients who presented with a full-thickness symptomatic tear had a 35.5% prevalence of a full-thickness tear on the contralateral side. CONCLUSIONS There is a high correlation between the onset of rotator cuff tears (either partial or full thickness) and increasing age. Bilateral rotator cuff disease, either symptomatic or asymptomatic, is common in patients who present with unilateral symptomatic disease. As the size of a tear appears to be an important factor in the development of symptoms, we recommend surveillance at yearly intervals for patients with known rotator cuff tears that are treated nonoperatively.
Using Genetic Algorithm with Combinational Crossover to solve Travelling Salesman Problem

This paper proposes a new solution for Traveling Salesman Problem (TSP) using genetic algorithm. A combinational crossover technique is employed in the search for optimal or near-optimal TSP solutions. It is based upon chromosomes that utilise the concept of heritable building blocks. Moreover, generation of a single offspring, rather than two, per pair of parents, allows the system to generate high performance chromosomes. This solution is compared with the well performing Ordered Crossover (OX). Experimental results demonstrate that, due to the well structured crossover technique, has enhanced performance.
Mid-Task Break Improves Global Integration of Functional Connectivity in Lower Alpha Band

Numerous efforts have been devoted to revealing neurophysiological mechanisms of mental fatigue, aiming to find an effective way to reduce the undesirable fatigue-related outcomes. Until recently, mental fatigue is thought to be related to functional dysconnectivity among brain regions. However, the topological representation of brain functional connectivity altered by mental fatigue is only beginning to be revealed. In the current study, we applied a graph theoretical approach to analyse such topological alterations in the lower alpha band (8~10 Hz) of EEG data from 20 subjects undergoing a two-session experiment, in which one session includes four successive blocks with visual oddball tasks (session 1) whereas a mid-task break was introduced in the middle of four task blocks in the other session (session 2). Phase lag index (PLI) was then employed to measure functional connectivity strengths for all pairs of EEG channels. Behavior and connectivity maps were compared between the first and last task blocks in both sessions. Inverse efficiency scores (IES = reaction time/response accuracy) were significantly increased in the last task block, showing a clear effect of time-on-task in participants. Furthermore, a significant block-by-session interaction was revealed in the IES, suggesting the effectiveness of the mid-task break on maintaining task performance. More importantly, a significant session-independent deficit of global integration and an increase of local segregation were found in the last task block across both sessions, providing further support for the presence of a reshaped topology in functional brain connectivity networks under fatigue state. Moreover, a significant block-by-session interaction was revealed in the characteristic path length, small-worldness, and global efficiency, attributing to the significantly disrupted network topology in session 1 in comparison of the maintained network structure in session 2. Specifically, we found increased nodal betweenness centrality in several channels resided in frontal regions in session 1, resembling the observations of more segregated global architecture under fatigue state. Taken together, our findings provide insights into the substrates of brain functional dysconnectivity patterns for mental fatigue and reiterate the effectiveness of the mid-task break on maintaining brain network efficiency.
Increased beta-nerve growth factor messenger RNA and protein levels in neonatal rat hippocampus following specific cholinergic lesions

High levels of NGF have recently been detected in cerebral cortex and hippocampus, and it was suggested that NGF supports cholinergic, basal forebrain neurons. The present study directly examined whether NGF levels are altered in the neonatal hippocampus following cholinergic denervation by transection of the fimbria. Ten days after transection, hippocampal cholinergic innervation, as assessed by AChE histochemistry and CAT immunohistochemistry, was decreased, and both hippocampal NGF mRNA and protein were elevated about 50%. This indicates possible lesion-induced transcriptional control of neonatal hippocampal NGF levels. This increase was specific to lesions of cholinergic systems, as entorhinal cortex ablation, which removes other afferent fibers to the hippocampus, did not cause a similar increase. At 30 d after fimbria transection, hippocampal NGF mRNA and protein did not differ from control levels, but the decrease in AChE and CAT staining persisted. Peripheral sympathectomy carried out in the adult rat resulted in 2- to 5-fold increases in NGF protein levels in heart atrium and ventricle, as well as submandibular gland, with no concomitant increase in NGF mRNA. Therefore, the control of NGF levels in the adult PNS is probably posttranscriptional. Our results strongly suggest that NGF is involved in the regulation of central cholinergic neurons and is transiently elevated in the neonatal hippocampus following cholinergic lesion.
CD133+ Tumor Initiating Cells in a Syngenic Murine Model of Pancreatic Cancer Respond to Minnelide

Purpose: Pancreatic adenocarcinoma is the fourth leading cause for cancer-related mortality with a survival rate of less than 5%. Late diagnosis and lack of effective chemotherapeutic regimen contribute to these grim survival statistics. Relapse of any tumor is largely attributed to the presence of tumor-initiating cells (TIC) or cancer stem cells (CSC). These cells are considered as hurdles to cancer therapy as no known chemotherapeutic compound is reported to target them. Thus, there is an urgent need to develop a TIC-targeted therapy for pancreatic cancer. Experimental Design: We isolated CD133+ cells from a spontaneous pancreatic ductal adenocarcinoma mouse model and studied both surface expression, molecular markers of pancreatic TICs. We also studied tumor initiation properties by implanting low numbers of CD133+ cells in immune competent mice. Effect of Minnelide, a drug currently under phase I clinical trial, was studied on the tumors derived from the CD133+ cells. Results: Our study showed for the first time that CD133+ population demonstrated all the molecular markers for pancreatic TIC. These cells initiated tumors in immunocompetent mouse models and showed increased expression of prosurvival and proinvasive proteins compared to the CD133− non-TIC population. Our study further showed that Minnelide was very efficient in downregulating both CD133− and CD133+ population in the tumors, resulting in a 60% decrease in tumor volume compared with the untreated ones. Conclusion: As Minnelide is currently under phase I clinical trial, its evaluation in reducing tumor burden by decreasing TIC as well as non-TIC population suggests its potential as an effective therapy. Clin Cancer Res; 20(9); 2388–99. ©2014 AACR.
The Potent Chinese Herbs for Inhibiting Cytotoxicity of Eosinophil Cationic Protein

The eosinophil cationic protein (ECP) is cytotoxic to bacteria, viruses, parasites and mammalian cells. The cells were damaged via the processes of pore-forming, permeability change and membrane leaking. Some clinical studies reported that ECP gathered in the bronchial tract of asthma patients, the bronchial and the airway epithelial cells were damaged and thus resulted in breathing tract inflammation. Therefore, inhibition of the cytotoxicity of ECP may serve as an approach for treatment of airway inflammation. To reach the purpose, reduction of the ECP/cell interaction is rational. In Chinese populations, herbs and prescriptions have been used to mitigate the airway inflammation with the chronic or acute symptoms. In this work, the relative binding ability between ECP and Beas-2B bronchial epithelial cells was measured by cell-based ELISA with or without adding Chinese herbs. Eighty three Chinese herbs or prescriptions were tested and 5 and 6 effective herb and prescription candidates were selected, respectively. According to the combinatory network generated from single-herbal drugs and prescriptions, a combinative network was established, and we found that a single herb, Gan-cao (甘草), served as a node connecting 5 prescriptions. In addition, Sheng-di-huang (生地黃), Dang-guei (當歸) and Mu-tong (木通) appeared in 5, 4 and 3 kinds of prescriptions, respectively. After further characterization, the extracts of these 3 herbs indeed effectively inhibit the interaction between ECP and Beas-2B cells. Since these Chinese herbs can reduce the binding affinity between ECP and cells, they are potential for * Correspondence: htchang@mail.cmu. edu.tw The Third International Symposium on Optimization and Systems Biology (OSB’09) Zhangjiajie, China, September 20–22, 2009 Copyright © 2009 ORSC & APORC, pp. 311–318 mitigating the airway inflammation symptoms.
Acetylcholinesterase mRNA Level and Synaptic Activity in Rat Muscles Depend on Nerve-Induced Pattern of Muscle Activation

Acetylcholinesterase (AChE) mRNA levels are severalfold higher in fast rat muscles compared with slow. We hypothesized that AChE mRNA levels and AChE activity in the neuromuscular junction depend on a specific nerve-induced pattern of motor unit activation. Chronic low-frequency stimulation, mimicking the activation pattern in slow muscles, was applied to fast muscles in rats. Molecular forms of AChE were analyzed by velocity sedimentation, and AChE mRNA levels were analyzed by Northern blots. AChE mRNA levels in stimulated fast muscles dropped to 10–20% of control after 1 week and became comparable to those in slow soleus muscles. The activity of the junctional A12 AChE form in 35 d stimulated fast muscles decreased to 56% of control value, reaching that in the soleus muscle. Therefore, synaptic AChE itself depends on the muscle activation pattern. Complete inactivity after denervation also decreased the AChE mRNA level in fast muscles to <10% in 48 hr. In contrast, profuse fibrillations observed in noninnervated immature regenerating muscles maintain AChE mRNA levels at 80% of that in the innervated fast muscles. If protein synthesis was inhibited by cycloheximide, AChE mRNA levels in 3-d-old regenerating muscle, still containing myoblasts, increased approximately twofold. No significant increase after cycloheximide application was observed either in denervated mature fast muscles or in normal slow muscles. Low AChE mRNA levels observed in those muscles are probably not caused by decreased stability of AChE mRNA as demonstrated in myoblasts.
Active Steganalysis of Transform Domain Steganography Based on Sparse Component Analysis

This paper presents a new active steganalysis method to break the transform domain steganography. Most of steganalysis techniques focus on detecting the presence or absence of a secret message in a cover (passive steganalysis), but in some cases we need to extract or estimate a hidden message (active steganalysis). Despite the importance of estimating the message, little research has been conducted in this area. In this study, a new active steganalysis method based on Spars Component Analysis (SCA) technique is presented. Here, the sparsity property of the cover image and hidden message has been used to extract the hidden message from a stego image. In our method, the transform domain steganography is formulated mathematically as a linear combination of sparse sources. Thus, the active steganalysis can be presented as a SCA problem. The feasibility of the SCA problem solving is confirmed by Linear Programming methods. Then, a fast algorithm is proposed to decrease the computational cost of steganalysis and still maintains the accuracy. The accuracy of the proposed method has been confirmed in different experiments on a variety of transform domain steganography methods. According to these experiments, our method not only reduces the error rate, but also decreases the computational cost compared to the previous active steganalysis methods in the literature.
Bilingual Cognitive Control in Language Switching: An fMRI Study of English-Chinese Late Bilinguals

The present study explored the bilingual cognitive control mechanism by comparing Chinese-English bilinguals’ language switching in a blocked picture naming paradigm against three baseline conditions, namely the control condition (a fixation cross, low-level baseline), single L1 production (Chinese naming, high-level baseline), and single L2 production (English naming, high-level baseline). Different activation patterns were observed for language switching against different baseline conditions. These results indicate that different script bilingual language control involves a fronto-parietal-subcortical network that extends to the precentral gyrus, the Supplementary Motor Area, the Supra Marginal Gyrus, and the fusiform. The different neural correlates identified across different comparisons supported that bilingual language switching involves high-level cognitive processes that are not specific to language processing. Future studies adopting a network approach are crucial in identifying the functional connectivity among regions subserving language control.
Functionalized Optical Fibre Sensors for Real-Time Environmental Monitoring Applications

The role of optical fibres as a medium for information transfer has found many applications. One of these is in environmental sensing, where slight perturbations in the surrounding environment can be remotely detected through modulation of light at selected points along the optical fibre. These perturbations exist in the form of variations in refractive index (RI), temperature or strain. This paper reviews our recent work on optical fibre-based RI sensors, in particular long period fibre gratings (LPFGs), integrated with carbon nano-materials. These carbon nano-materials with their unique properties modified the sensing scheme of the conventional fibre sensors, allowing them to gain immunity from certain free spectral range limitations, extend their operation range and also present the potential for efficient real-time environmental monitoring applications.
An approach to extracting the target text line from a document image captured by a pen scanner

In this paper, we present a new approach to extracting the target text line from a document image captured by a pen scanner. Given the binary image, a set of possible text lines are first formed by nearest-neighbor grouping of connected components (CC). They are then refined by text line merging and adding the missed CCs. The possible target text line is identified by using a geometric feature based score function and fed to an OCR engine for character recognition. If the recognition result is confident enough, the target text line is accepted. Otherwise, all the remaining text lines are fed to the OCR engine to verify whether an alternative target text line exists or the whole image should be rejected. The effectiveness of the above approach is confirmed by experiments on a testing database consisting of 117 document images captured by C-Pen and ScanEye pen scanners.
Electronic Communications of the EASST Volume 47 ( 2012 ) Proceedings of the 11 th International Workshop on Graph Transformation and Visual Modeling Techniques ( GTVMT 2012 ) Incremental Pattern Matching for Regular Expressions

Graph pattern matching lies at the heart of any graph transformationbased system. Incremental pattern matching is one approach proposed for reducing the overall cost of pattern matching over successive transformations by preserving the matches that stay relevant after a rule application. An important issue in any matching scheme, is the ability to properly and consistently deal with various facilities that add to the expressiveness of a GT-tool’s rule language. One such feature is the support for regular path expressions, which would let two nodes to be considered as a “match”, if a certain path of edges exists between them. In this paper, the incorporation of regular expression support into incremental pattern matching is discussed within the context of the GROOVE tool set. This includes laying down a formal foundation for incremental pattern matching for regular expressions which is then used to justify the extension proposed to add regular expression support to a well-known pattern matching algorithm.
On Measuring Semantic Similarity of Business Process Models

Identifying and integrating similar business processes within different organizations is an important task in construction of virtual enterprise. However, the same business process may be represented in different ways by different modelers even when they using the same modeling language. This is because that different organization using different terminologies and the problem of semantic heterogeneity makes it a tedious job to compare business processes. Therefore, the technologies of semantic similarity computing are employed to resolve ambiguity issues caused by the use of synonyms or homonyms. In particular, the idea of similarity propagation is introduced to pick out a mapping between corresponding activities and data, and Hungarian algorithm is expanded to reduce its time complexity. Then the similarity of whole models is measured based on Jaccard coefficient. Finally, an experiment is given to evaluate the method.