1,447 research outputs found
Word Combination Kernel for Text Classification with Support Vector Machines
In this paper we propose a novel kernel for text categorization. This kernel is an inner product defined in the feature space generated by all word combinations of specified length. A word combination is a collection of unique words co-occurring in the same sentence. The word combination of length k is weighted by the k rm th root of the product of the inverse document frequencies (IDF) of its words. By discarding word order, the word combination features are more compatible with the flexibility of natural language and the feature dimensions of documents can be reduced significantly to improve the sparseness of feature representations. By restricting the words to the same sentence and considering multi-word combinations, the word combination features can capture similarity at a more specific level than single words. A computationally simple and efficient algorithm was proposed to calculate this kernel. We conducted a series of experiments on the Reuters-21578 and 20 Newsgroups datasets. This kernel achieves better performance than the word kernel and word-sequence kernel. We also evaluated the computing efficiency of this kernel and observed the impact of the word combination length on performance
Stratified Transfer Learning for Cross-domain Activity Recognition
In activity recognition, it is often expensive and time-consuming to acquire
sufficient activity labels. To solve this problem, transfer learning leverages
the labeled samples from the source domain to annotate the target domain which
has few or none labels. Existing approaches typically consider learning a
global domain shift while ignoring the intra-affinity between classes, which
will hinder the performance of the algorithms. In this paper, we propose a
novel and general cross-domain learning framework that can exploit the
intra-affinity of classes to perform intra-class knowledge transfer. The
proposed framework, referred to as Stratified Transfer Learning (STL), can
dramatically improve the classification accuracy for cross-domain activity
recognition. Specifically, STL first obtains pseudo labels for the target
domain via majority voting technique. Then, it performs intra-class knowledge
transfer iteratively to transform both domains into the same subspaces.
Finally, the labels of target domain are obtained via the second annotation. To
evaluate the performance of STL, we conduct comprehensive experiments on three
large public activity recognition datasets~(i.e. OPPORTUNITY, PAMAP2, and UCI
DSADS), which demonstrates that STL significantly outperforms other
state-of-the-art methods w.r.t. classification accuracy (improvement of 7.68%).
Furthermore, we extensively investigate the performance of STL across different
degrees of similarities and activity levels between domains. And we also
discuss the potential of STL in other pervasive computing applications to
provide empirical experience for future research.Comment: 10 pages; accepted by IEEE PerCom 2018; full paper. (camera-ready
version
Association of vancomycin with lipid vesicles
Antibiotics play a pivotal role in modern medicine for the treatment of bacterial infection in patients. Membrane defines the boundary between single cell and its environment and is a main target for antibacterial agents. To better understand the mechanism of antibiotics action on microbes, we utilized liposome as membrane mimic model to study antibiotics interaction with bacterial membrane by variety of biophysical methods. Isothermal calorimetry and fluorescence photometry experiments were performed to examine interaction between antibiotics and liposome. We found that vancomycin, one of the most important antibiotics for the treatment of serious infections by gram-positive bacteria, binds to the liposome. The association between the drug and the liposome does not involve the tail part of the lipids. Moreover, the binding affinity increases along with the increment of liposome size. Of three major lipid components, phosphatidylglycerol is the preferential target for vancomycin binding. We also showed that vancomycin associates with vesicle derived from Staphylococcus aureus membrane in a similar manner as the binding to liposome. Our data suggested that vancomycin associates with bacterial membrane through direct interaction with lipid head groups with the extent of the association depending very much on specific type of lipids and curvature of local membrane structure
A new measurement of sequence conservation
<p>Abstract</p> <p>Background</p> <p>Understanding sequence conservation is important for the study of sequence evolution and for the identification of functional regions of the genome. Current studies often measure sequence conservation based on every position in contiguous regions. Therefore, a large number of functional regions that contain conserved segments separated by relatively long divergent segments are ignored. Our goal in this paper is to define a new measurement of sequence conservation such that both contiguously conserved regions and discontiguously conserved regions can be detected based on this new measurement. Here and in the following, conserved regions are those regions that share similarity higher than a pre-specified similarity threshold with their homologous regions in other species. That is, conserved regions are good candidates of functional regions and may not be always functional. Moreover, conserved regions may contain long and divergent segments.</p> <p>Results</p> <p>To identify both discontiguously and contiguously conserved regions, we proposed a new measurement of sequence conservation, which measures sequence similarity based only on the conserved segments within the regions. By defining conserved segments using the local alignment tool CHAOS, under the new measurement, we analyzed the conservation of 1642 experimentally verified human functional non-coding regions in the mouse genome. We found that the conservation in at least 11% of these functional regions could be missed by the current conservation analysis methods. We also found that 72% of the mouse homologous regions identified based on the new measurement are more similar to the human functional sequences than the aligned mouse sequences from the UCSC genome browser. We further compared BLAST and discontiguous MegaBLAST with our method. We found that our method picks up many more conserved segments than BLAST and discontiguous MegaBLAST in these regions.</p> <p>Conclusions</p> <p>It is critical to have a new measurement of sequence conservation that is based only on the conserved segments in one region. Such a new measurement can aid the identification of better local "orthologous" regions. It will also shed light on the identification of new types of conserved functional regions in vertebrate genomes <abbrgrp><abbr bid="B1">1</abbr></abbrgrp>.</p
Cram\'{e}r moderate deviations for the elephant random walk
We establish some limit theorems for one-dimensional elephant random walk,
including Berry-Esseen bounds, Cram\'{e}r moderate deviations and local limit
theorems. These limit theorems can be regarded as refinements of the central
limit theorems for the elephant random walk. Moreover, by these limit theorems,
we conclude that the domain of attraction of normal distribution mainly depends
on a memory parameter which lies between and $3/4.
Exploring Differentiated Economic Adaptation and Adaptability of Old Industrial Areas in Transitional China
My dissertation is concerned with uneven economic adaptation and adaptability of old industrial areas in an evolutionary and institutional, as well as a human agency perspective. There is a considerable literature in economic geography (EG), focusing on the role of firms and industry dynamics in affecting the evolution of old industrial areas (OIAs). However, little work has been done, both empirically and theoretically, on the role of state, multi-scalar institutions, politics and policies. Moreover, the majority of the re-search on the topic is very much based on single-case studies, whose evidence and knowledge is mainly derived from European and American contexts. Therefore, the key aim of the doctoral dissertation are to: 1) theoretically, integrate an institutional and geographical political economy perspective with the Evolutionary Economic Geography (EEG) approach, in order to give a better understanding of the evolutionary processes and mechanisms of OIAs. And 2) empirically, to examine the nature of uneven regional economic evolution, based on an in-depth comparison of two coal-mining regions in a post-crisis and non-western context.
My book pays more attention to how the state, more precisely, how the people within the state and state owned enterprises (SOEs) of OIAs, response and enact to changing environment for long-run industrial adaptation and adaptability. It does not simply focus on the micro behaviors of firms, states and people, but more on their embedded posi-tions and relationships of multi-scalar political-institutional frameworks and policy fields. The empirical research is based on in-depth case studies on two Chinese coal-mining re-gions (Zaozhuang in Shandong Province and Fuxin in Liaoning Province) both facing the ‘slow burn’ crisis of local coal resource exhaustion since 2000. The findings are mainly derived from a qualitative method of semi-structured interviews and evaluated by con-text analysis and statistical data description.
In this book, first and foremost, the concepts of path dependence, path creation and lock-ins are critically examined. The empirical evidence suggests that the effects of lock-ins in Chinese contexts are more politically constituted, due to the Chinese-specific ad-ministrative hierarchy system among SOEs and governments. Despite strong industrial path dependence and negative regional lock-ins, new paths are not restricted to emerge. Based on the notion of path plasticity, I conclude that the Chinese local state and its state leaders in OIAs are aware of how to balance the interests among multi-scalar polit-ical economies, and of how to flexibly read and enact locally according to multi-scalar institutional and policy conditions for potential industrial change. Secondly, given the ubiquitous influences of state elites in China, the book takes a closer look at how state officials mold specific institutional environment for industrial dynamics. The notion of place leadership has been critically adopted in the Chinese authoritarian context. It well explains the micro-level dynamics and characteristics of people on the evolution of Chinese OIAs. The book finds that although Chinese state elites do have formal power to effectively make and implement fast economic decisions and policy-fix, local institutional change still critically calls for informal leadership, such as interpretive and network leadership. New paths might be created quickly by local state leaders. But, without forming solid new supporting institutions, they may not generate positive im-pact for long-term regional development. The most important contribution of the book is the comparison of two Chinese mining regions. A new conceptual framework on analyzing and understanding uneven resilience of regions has been developed. It is built upon an in-depth conceptualization that de-constructs the dualism idea between adaptation and adaptability. And it redefines them in an interactive, dialectical and evolutionary way. The comparative study in China high-lights the importance of multi-scalar institutions and national political economy change in coordinating the behaviors of firms, local states and, the micro dynamics of their con-stitutive human agents in OIAs. The historically conditioned political distance between localities and the central state is essential. It can help to fundamentally understand the differen-tiated resilience of China’s OIAs. It should be placed at the core to explore the question of why some regions in China are able to manage endogenous place-based development of economies, while others fail to do such but mostly at the mercy of exogenous forces and assets. In the end, this book provides new evidence that EEG needs to be integrated into other related paradigms in EG, when it comes to understand the complex restructuring of OIAs. Besides the theoretical contributions, the book also put several policy recommendations for future development of OIAs in China and beyond.Die vorliegende Dissertation befasst sich mit ungleicher ökonomischer Anpassung und Anpassungsfähigkeit altindustrieller Gebiete aus einer evolutionären, institutionellen und akteurszentrierten Perspektive. In der wirtschaftsgeographischen Literatur gibt es bereits zahlreiche Beiträge die sich mit den Rollen von Unternehmen und industriellen Dynamiken für den Aufstieg und Niedergang altindustrieller Gebiete befassen. Wenige Beiträge haben sich allerdings sowohl empirisch als auch konzeptionell mit den Einflüssen von Staaten, multiskalaren Institutionen oder unterschiedlichen Strategien und Politiken befasst. Zudem fokussiert der Großteil der bisherigen Arbeiten Einzelfälle in Europa oder Nordamerika. Daraus ergeben sich die zwei Hauptziele dieser Doktorarbeit. 1) Theoretisch werden eine institutionelle Perspektive und Ansätzen der Politischen Ökonomie mit der Evolutionären Wirtschaftsgeographie in Verbindung gebracht, um zu einem tieferen Verständnis evolutionärer Prozesse und Mechanismen in altindustriellen Gebieten zu kommen. 2) Empirisch werden Facetten ungleicher regionaler Wirtschaftsentwicklung am Beispiel zweier Kohlebergbaugebiete untersucht, die sich beide in einer Nachkrisensituation befinden und einem nicht-westlichen Kontext zugehören.
Die Arbeit beleuchtet, wie der Staat - verstanden als handelnde Akteure in Staat und staatlichen Betrieben in altindustriellen Regionen - auf Umfeldänderungen reagiert, um langfristige industrielle Anpassung zu erreichen. Dabei geht die Arbeit über einen Fokus auf unternehmerische, staatliche oder individuelle Einzelhandlungen hinaus und konzentriert sich auf deren Einbettung und Beziehungen in einem multiskalaren, politisch-institutionellen Rahmen und Politikfeld. Die empirische Untersuchung basiert auf Tiefenstudien zweier chinesischer Kohlebergbauregionen (Zaozhuang in der Provinz Shandong und Fuxin in der Provinz Liaoning), die beide vom schleichenden Niedergang der lokalen Kohlereserven seit dem Jahr 2000 geprägt sind. Die Forschungsergebnisse beruhen größtenteils auf qualitativen Daten (halbstandardisierte Interviews), die durch eine Kontextanalyse ausgewertet und um eine deskriptive Analyse sekundärstatistischer Daten ergänzt wurden.
Der erste Beitrag dieser Doktorarbeit liegt in einer kritischen Bestandsaufnahme der Konzepte von Pfadabhängigkeiten, Pfadentstehungen und Lock-Ins. Die empirischen Einblicke deuten darauf hin, dass Lock-Ins im chinesischen Kontext stark politisch bedingt sind. Dies ist auf das spezifische administrative Hierarchiesystem zwischen staatseigenen Betrieben und Staaten zurückzuführen. Trotz starker industrieller Pfadabhängigkeit und negativer regionaler Lock-In-Effekte steht der Entstehung neuer Pfade nichts entgegen. Aufbauend auf dem Konzept der Pfadplastizität kommt die Arbeit zu dem Ergebnis, dass sich die chinesischen lokalen Staatsbehörden und die staatliche Führung in staatseigenen Betrieben der Interessenkonflikte zwischen den multiskalaren politischen Ökonomien bewusst sind, diese flexibel auslegen und gemäß der multiskalaren institutionellen und politischen Bedingungen hinsichtlich potentieller lokaler industrieller Veränderung auslegen.
Der zweite Beitrag liegt darin, dass der ubiquitäre Einfluss staatlicher Eliten in China auf industrielle Dynamiken genauer analysiert wird. Dazu wird untersucht, wie Staatsbeamte und lokale Führungspersönlichkeiten die entsprechenden institutionellen Kontexte formen. Der Gedanke der „Place Leadership“ wird kritisch an den autoritären chinesischen Kontext angepasst. So können die kleinmaßstäblichen Dynamiken und Charakteristika im Zusammenhang mit der Entstehung altindustrieller Regionen in China erläutert werden. Wie sich zeigt, verfügen die staatlichen Eliten über ein hohes Maß an formeller und exekutiver Macht, um wirtschaftliche und politische Entscheidungen zu fällen. Dennoch verdeutlichen die empirischen Ergebnisse, dass für institutionellen Wandel informelle Führungsformen wie interpretative oder netzwerkartige Führung nötig sind. Neue Pfade können zwar von lokalen staatlichen Anführern schneller erzeugt werden, aber ohne neue, unterstützende Institutionen bestehen kaum Aussichten darauf, langfristige Veränderungspotenziale der regionalen Entwicklung aufrechtzuerhalte.
Der Hauptbeitrag der Arbeit liegt im Vergleich der zwei chinesischen Bergbauregionen. Um deren ungleiche regionale Resilienz zur analysieren und zu verstehen wird ein neuartiger konzeptuelle Ansatz vorgeschlagen. In einer interaktiven, dialektischen und evolutionären Art überwindet dieser den Dualismus von Anpassung und Anpassungsfähigkeit und hebt die Rolle von multiskalaren Institutionen sowie von nationalem politisch-ökonomnischem Wandel für die Koordination unternehmerischen und lokal-staatlichen Handelns und derer Akteure in staatseigenen Betrieben hervor. Die historisch bedingte politische Distanz zwischen lokaler und nationaler Verwaltung und Regierung ist dabei grundlegend, um die verschiedenen Resilienzen und Anpassungsfähigkeiten chinesischer staatseigener Betriebe zu verstehen. Diese werden in das Zentrum der vergleichenden Fallstudie gerückt, um besser zu verstehen, warum einige Regionen in China dazu in der Lage sind endogene wirtschaftliche Entwicklungspotenziale zu steuern, während andere daran – zumeist aufgrund exogener Kräfte – scheitern.
Insgesamt leistet die vorliegende Dissertation einen Beitrag zur Erweiterung der Evolutionären Wirtschaftsgeographie, indem andere wirtschaftsgeographische Paradigmen und Perspektiven eingebunden werden und somit komplexe Restrukturierungsprozesse staatseigener Betriebe verstanden werden können. Neben diesem theoretischen Beitrag liefert die Arbeit politische Empfehlungen für die zukünftige Entwicklung altindustrieller Industrieregionen in China und andernorts
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