cometadata/datacite-rtg-text-other-reclassification-records huggingface dataset:
Rural locals, distant states : citizenship in contemporary rural Georgia
Creators: name: Mataradze, Teona
Publisher: name: Universitäts- und Landesbibliothek Sachsen-Anhalt
Year: 2015
Subjects: subject: 320

description: Diese Doktorarbeit untersucht gegenwärtige Bedingungen und Prozesse des Übergangs zu Demokratie und Marktwirtschaft im ländlichen Georgien. Dabei befasst sie sich mit den Beziehungen zwischen Bürger und Staat. Sie basiert auf ethnologischer Forschung, welche 2006-2007 im Dorf Sac’ire im T’q’ibuli Bezirk durchgeführt wurde. Die Forschung zeigt, dass drei, u.a. von T.H. Marshall (1998 [1963]) diskutierte, Bündel von Rechten für das Verhalten der Einwohner relevant sind. Die Diskussion der politischen Rechte der Einwohner und das Kämpfen um soziale Rechte zeigt, wie bürgerliche, politische und soziale Rechte ineinandergreifen und teilweise Verhandlungsgegenstand sind. Angesichts der Armut wird Migration zur hauptsächlichen Überlebensstrategie. Indem Migranten zu abwesenden Bürgern werden und Geld nach Hause schicken, übernehmen sie die Rolle des Staates bei der Bereitstellung von wirtschaftlicher Unterstützung für die Dorfbewohner, wobei sie aber jeglichen Kontakt mit staatlichen Stellen, durch die Manipulation von Staatsbürgerschafts-, Pass- und Visasystemen, vermeiden.
description: This PhD thesis examines the new conditions and processes in the transition to democracy and a market economy in rural Georgia and focuses especially on citizen-state relationships. It is based on anthropological research carried out in 2006-2007 in the village Sac’ire (T’q’ibuli district). The study shows that three sets of rights (civil, political and social) discussed by T.H. Marshall (1998 [1963]) and others are relevant for understanding local citizenship practices. The discussion of the political rights of locals and their striving for social rights shows how civil, political and social rights are interdependent and sometimes an object of negotiation. In the face of poverty, migration becomes a main strategy for survival. By becoming absent citizens, migrants, send money home and take on the state’s role of providing economic support for the villagers, but also avoid official state channels wherever possible by manipulating citizenship, passport and visa regimes.
Experience with the KeyNote Trust Management System: Applications and Future Directions
Creators: name: Blaze, Matt
name: Ioannidis, John
name: Keromytis, Angelos D.
Publisher: name: Columbia University
Year: 2003
Subjects: Computer science

description: Access control in distributed systems has been an area of intense research in recent years. One promising approach has been that of trust management, whereby authentication and authorization decisions are combined in a unified framework for evaluating security policies and credentials. In this paper, we report on our experience of the past seven years using the PolicyMaker and the KeyNote trust management systems in a variety of projects. We start with a brief overview of trust management in general, and KeyNote in particular; we describe several applications of trust management; we then discuss various features we found missing from our initial version of KeyNote, which would have been useful in the various applications it was used. We conclude the paper with our plans for future research.
A benefit costing process for lean six sigma programs
Creators: name: Margaret Crowdle, Mary
name: McDermott, Olivia
name: Trubetskaya, Anna
Publisher: name: University of Limerick
Year: 2023
Subjects: classificationCode: 40
subject: Engineering

description: Purpose – This study aimed to bridge the gap between the financial measurement of process improvement ideas and Lean Six Sigma measurements. It was required to increase employee engagement in process improvement initiatives. Design/methodology/approach – Through both a practical and theoretical application of the Design for Lean Six Sigma methodology, the researcher was able to design a process and a benefit measuring methodology that was acceptable by finance and aligns with the benefits expected from the elimination of the Lean wastes. Findings – The project found that benefit measurement methodology is not understood by most employees, which leads to a lack of engagement in working on improvements. The result of the study was a model for employees to identify and quantify these benefits. This has resulted in a model for cost-benefit analysis aligning financial costs with non-value add waste costs and cost of poor-quality costs resulting in increased process improvement ideas and activity. Research limitations/implications – While this study was limited to one company, applying this methodology could benefit any company experiencing the same difficulties. Originality/value – This is one of the first studies to try and cost the benefits of LSS projects both from an organisational and generic viewpoint.
Structural driving forces and their spectroscopic signatures: from protonation dynamics to amyloid formation
Creators: name: Hoffmann, Felix
Publisher: name: Universitäts- und Landesbibliothek Sachsen-Anhalt
Year: 2018
Subjects: subject: 500 Naturwissenschaften und Mathematik 540 Chemie 540 Chemie und zugeordnete Wissenschaften

description: Im Rahmen dieser Arbeit wurde das komplexe Zusammenspiel von hydrophilen und hydrophoben Wechselwirkungen auf molekularer und submolekularer Ebene untersucht. Hierbei wurden die spektroskopischen Signaturen dieser Wechselwirkungen für ultraschnelle Protonierungsprozesse im elektronisch angeregten Zustand, für kleine organische Moleküle und Metabolite, sowie für punktmutierte Amyloid β Fibrillen berechnet. Mithilfe von Molekulardynamiksimulationen und quantenchemischen Berechnungen wurden Zusammenhänge zwischen den strukturellen und dynamischen Eigenschaften dieser Systeme, wie zum Beispiel Wasserstoffbrückenbindungen und Protonentransferwege, und spektroskopischen Parametern hergestellt. Die Ergebnisse dieser Arbeit ermöglichen so die Interpretation entsprechender experimenteller Daten.
description: This dissertation addresses the complex interplay of hydrophilic and hydrophobic interactions at the molecular and submolecular level. Their spectroscopic signatures are calculated for ultrafast excited-state protonation phenomena in solution, small organic molecules and metabolites, and point-mutated amyloid β (1-40) fibrils. These systems contain hydrogen bonds and proton transfer pathways, which exhibit characteristic spectroscopic features. Using atomistic molecular dynamics simulations and quantum chemical calculations, the corresponding experiments could be successfully interpreted.
A Simple Correlation-Based Model of Intelligibility for Nonlinear Speech Enhancement and Separation
Creators: name: Boldt, Jesper B.
name: Ellis, Daniel P. W.
Publisher: name: Columbia University
Year: 2009
Subjects: Electrical engineering
Artificial intelligence

description: Applying a binary mask to a pure noise signal can result in speech that is highly intelligible, despite the absence of any of the target speech signal. Therefore, to estimate the intelligibility benefit of highly nonlinear speech enhancement techniques, we contend that SNR is not useful; instead we propose a measure based on the similarity between the time-varying spectral envelopes of target speech and system output, as measured by correlation. As with previous correlation-based intelligibility measures, our system can broadly match subjective intelligibility for a range of enhanced signals. Our system, however, is notably simpler and we explain the practical motivation behind each stage. This measure, freely available as a small Matlab implementation, can provide a more meaningful evaluation measure for nonlinear speech enhancement systems, as well as providing a transparent objective function for the optimization of such systems.
Cross-domain Collaborative Anomaly Detection: So Far Yet So Close
Creators: name: Boggs, Nathaniel Gordon
name: Hiremagalore, Sharath
name: Stavrou, Angelos
name: Stolfo, Salvatore
Publisher: name: Columbia University
Year: 2011
Subjects: Computer science

description: Web applications have emerged as the primary means of access to vital and sensitive services such as online payment systems and databases storing personally identifiable information. Unfortunately, the need for ubiquitous and often anonymous access exposes web servers to adversaries. Indeed, network-borne zero-day attacks pose a critical and widespread threat to web servers that cannot be mitigated by the use of signature-based intrusion detection systems. To detect previously unseen attacks, we correlate web requests containing user submitted content across multiple web servers that is deemed abnormal by local Content Anomaly Detection (CAD) sensors. The cross-site information exchange happens in real-time leveraging privacy preserving data structures. We filter out high entropy and rarely seen legitimate requests reducing the amount of data and time an operator has to spend sifting through alerts. Our results come from a fully working prototype using eleven weeks of real-world data from production web servers. During that period, we identify at least three application-specific attacks not belonging to an existing class of web attacks as well as a wide-range of traditional classes of attacks including SQL injection, directory traversal, and code inclusion without using human specified knowledge or input.
Measuring the Human Factor of Cyber Security
Creators: name: Bowen, Brian M.
name: Devarajan, Ramaswamy
name: Stolfo, Salvatore
Publisher: name: Columbia University
Year: 2011
Subjects: Computer science

description: This paper investigates new methods to measure, quantify and evaluate the security posture of human organizations especially within large corporations and government agencies. Computer security is not just about technology and systems. It is also about the people that use those systems and how their vulnerable behaviors can lead to exploitation. We focus on measuring enterprise-level susceptibility to phishing attacks. Results of experiments conducted at Columbia University and the system used to conduct the experiments are presented that show how the system can also be effective for training users. We include a description of follow-on work that has been proposed to DHS that aims to measure and improve the security posture of government departments and agencies, as well as for comparing security postures of individual agencies against one another.
The Distinctiveness and Stability of Employee Attitudes Toward Change and Their Relationship with Leadership: A Longitudinal Study
Creators: name: Henricks, Matthew David
name: Bednall, Timothy
name: Kehoe, E James
Publisher: name: Swinburne
Year: 2025
Subjects: classificationCode: 3507
subject: Strategy, management and organisational behaviour
classificationCode: 35
subject: Commerce, management, tourism and services
classificationCode: 3505
subject: Human resources and industrial relations

description: We examined state-readiness for change and trait-resistance to change, and assessed the distinctiveness of the two constructs, their stability over a four-to-six-month period, and the capacity for each to be influenced by transformational leadership. Equivalence testing suggested that each construct was measuring a distinct phenomenon. However, neither readiness for a specific change (state-readiness) nor resistance to organizational change in general (trait-resistance) were particularly stable over time (rs = .31, .30). In addition, while transformational leadership was significantly correlated with both state-readiness and trait-resistance at Time 1 (rs = .40, –.24), it was only significantly correlated with state-readiness at Time 2 (r = .34). Transformational leadership at Time 1 had a small predictive relationship with state-readiness several months later at Time 2 (r = .20). However, this predictive relationship was no longer significant after controlling for precursory and contemporaneous employee attitudes toward change. Results are discussed with a particular focus on the management of unplanned change events such as the recent Covid-19 pandemic. The implications of this research for traditional versus emerging leadership ontologies are also explored.MAD statementIn the aftermath of the COVID-19 pandemic, where workplaces were required to implement major changes with little advance notice, the stability of employee attitudes toward change has been a critical consideration. The present study suggests that organizations may approach their preparations for future unplanned changes with a degree of optimism. Employee attitudes toward change may be less stable than previously suggested. Our findings revealed that the behaviour of designated leaders had only a small and temporary association with employee attitudes toward change. The study suggests the promise of emerging leadership perspectives that reconceptualize leadership as a collective social process driven by all employees during times of significant change.
A study of potential sporadic amyotrophic lateral sclerosis biomarkers in cerebrospinal fluid
Creators: name: Kostesky, Trisha Ehren
Publisher: name: University of British Columbia
Year: 2011

description: Sporadic Amyotrophic Lateral Sclerosis (sALS) is a debilitating and fatal neurodegenerative disease of unknown etiology. It currently has no biochemical marker to confirm a clinical diagnosis, and this has negative consequences for patients when it comes to initiating early medical intervention and participating in therapeutic trials. Valid biomarkers can be useful for diagnostic and prognostic indications as well as providing insight into disease pathogenesis and identifying targets for therapeutic interventions. Cerebrospinal fluid (CSF) may be a particularly valuable source of biomarkers because it is in close anatomical proximity to the brain and spinal cord, thus making it a better reflection of biochemical alterations resulting from neurodegenerative disease. This study examined the proteome profile of CSF from sALS patients and controls to identify candidate biomarkers that might aid in the diagnosis of sALS and possibly provide insight into disease pathogenesis. An antibody microarray technique was used to measure the expression levels of various cell signalling proteins in the CSF of sALS patients and healthy controls. The results identified a number of protein changes in sALS CSF, including a considerable decrease in the level of ephrin type-A receptor 1 tyrosine kinase (EphA1) relative to control CSF. Follow-up validation studies by Western blotting with CSF samples from a separate cohort of 19 sALS patients, 21 healthy controls and 10 neurological disease controls confirmed a statistically significant decrease in EphA1 levels. As a diagnostic test, EphA1 levels in CSF had a statistically significant ability to discriminate between sALS patients and controls. Receptor levels also had a positive correlation with age at onset of sALS symptoms, indicating that this potential biomarker may be capable of identifying people who are prone to an earlier onset of disease. The Eph family of tyrosine kinase receptors engage in complex bidirectional signalling that functions as a major form of contact-dependent communication between cells, and mediates a variety of cellular responses. As research begins to further elucidate these multifaceted signalling mechanisms, imbalances in Eph receptor functioning are increasingly implicated in a variety of pathologies in the central nervous system that are related to some of the major features of ALS.
BotSwindler: Tamper Resistant Injection of Believable Decoys in VM-Based Hosts for Crimeware Detection
Creators: name: Bowen, Brian M.
name: Prabhu, Pratap
name: Kemerlis, Vasileios
name: Sidiroglou, Stelios
name: Keromytis, Angelos D.
name: Stolfo, Salvatore
Publisher: name: Columbia University
Year: 2010
Subjects: Computer science

description: We introduce BotSwindler, a bait injection system designed to delude and detect crimeware by forcing it to reveal during the exploitation of monitored information. The implementation of BotSwindler relies upon an out-of-host software agent that drives user-like interactions in a virtual machine, seeking to convince malware residing within the guest OS that it has captured legitimate credentials. To aid in the accuracy and realism of the simulations, we propose a low overhead approach, called virtual machine verification, for verifying whether the guest OS is in one of a predefined set of states. We present results from experiments with real credential-collecting malware that demonstrate the injection of monitored financial bait for detecting compromises. Additionally, using a computational analysis and a user study, we illustrate the believability of the simulations and we demonstrate that they are sufficiently human-like. Finally, we provide results from performance measurements to show our approach does not impose a performance burden.
Hydrodynamic Instability and Heat Transfer Analysis of Nanoflow in Semi-Porous Microchannels
Creators: name: Zargartalebi, Mohammad
Publisher: name: Schulich School of Engineering
Year: 2019
Subjects: subject: Nanoparticles, LBM, Microchannel, Heat Transfer, Flow Dynamics
subject: Applied Sciences
subject: Engineering
subject: Engineering--Chemical

description: This dissertation focuses on the simulation of nanofluid and fluid flow in a semi-porous microchannel. Despite the wide applications of nanoparticles in recent years, there are still some nano-exclusive phenomena which render the performance of the nanofluid unpredictable. The nano-scale specific properties can be positive or negative depending on the nanoparticle and the surrounding conditions, ignoring which, result in imprecise predictions. Therefore, this dissertation analyzes the hydrodynamic and thermal behavior of nanofluid and fluid flow in semi-porous microchannels, employing the Lattice Boltzmann method. First, the flow instabilities in nanofluid flow in a porous microchannel are studied. It is shown that the nanoparticle effect on instability is highly-dependent on its properties and the surrounding conditions. It is also revealed that nanoparticles behave differently at various viscous regimes, and the instability is controlled by the physical and chemical properties of the nanoparticles. The second part focuses on the heat transfer behavior of the porous microchannel in the presence of nanofluid. It is shown that the nanoparticle distribution plays important roles in heat transfer. Particle size and surface energy are also found to change the whole picture of heat transfer and therefore, a characteristic curve is introduced, using which, nanoparticles can safely improve heat removal. In the third section, the analysis of the second part is extended to randomly distributed pin-based microchannels with special attention to nanoparticle adsorption on pin surfaces. Statistical analysis shows that various random realizations behave differently, and an averaged behavior can be found. Nanoparticle adsorption on the pin surface is found to have double-edged effects and can be beneficial or detrimental to heat removal. Finally, the hydrodynamic and thermal behavior of partially-porous microchannel are analyzed. It is revealed that, unlike the fully-porous microchannel, the thermal performance of these systems is complicated. The study shows existence of hydrodynamic and thermal critical porous medium heights where the impact of the porous medium becomes imperative. A particle tracing technique is adopted to explain the underlying physics and a mathematical model is proposed to explain the interplay between the critical points and the hydrodynamic, geometric, and thermal parameters.
The impact of controlled breeding on milk production in pastoral goats in northern Kenya: an application of polynomial growth curve fitting
Creators: name: Hary, Ingo
Publisher: name: Humboldt-Universität zu Berlin
Year: 2003
Subjects: subject: 630 Landwirtschaft und verwandte Bereiche

description: This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.
description: The paper investigates the effect of controlled seasonal breeding on milk production in a herd of Small East African (SEA) goats. Polynomial growth curve models were fitted to both daily and cumulative milk yield data obtained from an experiment conducted over a period of 4 years (1984–88) under simulated pastoral herd management in Isiolo District, northern Kenya. The experimental treatment consisted of six different mating seasons per year, which were replicated three times over the course of the experiment.Milk yields in the first 2 weeks of lactation were negatively affected (<400 g/day) when kidding took place between June and September, whereas maximum initial yields of about 450 to 550 g/day were achieved at the onset and during the long rainy season. Multiple peaks in milk yield curves were observed when a rainy season occurred after about the first half of the lactation period. In terms of total amount of milk produced until 28 weeks of lactation, the production system could benefit from the introduction of a restricted breeding management allowing does to be bred in the period from June to November, with total milk yields being estimated at approximately 60 kg of milk. Maximum milk production until weaning can be expected to be achieved by does mated between October and January (between 46 and 48 kg of milk). The present experiment has revealed that mating just prior to or during the long rainy season leads to low milk yields until weaning and significantly increases the incidence of early kid deaths.It is concluded that evaluating milk production in goat herds exposed to strong seasonal changes in forage supply is perhaps best carried out in terms of cumulative milk yields, instead of average daily yields, which are subject to large fluctuations. Furthermore, under these conditions fitting polynomial growth curves to longitudinal milk yield data using the general linear mixed model appears to be more appropriate than the estimation of non-linear algebraic lactation curves.
Automating the Injection of Believable Decoys to Detect Snooping
Creators: name: Bowen, Brian M.
name: Kemerlis, Vasileios
name: Rabhu, Pratap
name: Keromytis, Angelos D.
name: Stolfo, Salvatore
Publisher: name: Columbia University
Year: 2010
Subjects: Computer science

description: We propose a novel trap-based architecture for enterprise networks that detects "silent" attackers who are eavesdropping network traffic. The primary contributions of our work are the ease of injecting, automatically, large amounts of believable bait, and the integration of various detection mechanisms in the back-end. We demonstrate our methodology in a prototype platform that uses our decoy injection API to dynamically create and dispense network traps on a subset of our campus wireless network. Finally, we present results of a user study that demonstrates the believability of our automatically generated decoy traffic.
Locating Singing Voice Segments within Music Signals
Creators: name: Berenzweig, Adam
name: Ellis, Daniel P. W.
Publisher: name: Columbia University
Year: 2001
Subjects: Electrical engineering
Artificial intelligence

description: A sung vocal line is the prominent feature of much popular music. It would be useful to locate the portions of a musical track during which the vocals are present reliably, both as a 'signature' of the piece and as a precursor to automatic recognition of lyrics. We approach this problem by using the acoustic classifier of a speech recognizer as a detector for speech-like sounds. Although singing (including a musical background) is a relatively poor match to an acoustic model trained on normal speech, we propose various statistics of the classifier's output in order to discriminate singing from instrumental accompaniment. A simple HMM allows us to find a best labeling sequence for this uncertain data. On a test set of forty 15 second excerpts of randomly-selected music, our classifier achieved around 80% classification accuracy at the frame level. The utility of different features, and our plans for eventual lyrics recognition, are discussed.
MCAA Call to Minimise the Impact of Brexit on Research
Creators: name: Policy Working Group
name: UK Chapter
Publisher: name: Zenodo
Year: 2019

description: The Marie Curie Alumni Association (MCAA) has been following the evolution of the Brexit negotiations with major concern. We join the broader scientific community in emphasising that it is imperative for the UK, and to some extent for the ERA, that research and innovation cooperation programmes between the UK and the EU are maintained after Brexit. Independent of the scenario that plays out, the MCAA urges that the British government prioritizes association to Horizon Europe and unrestricted UK-EU mobility for researchers. For more from the Marie Curie Alumni Association, please see: https://zenodo.org/communities/mcaa
Evaluating music sequence models through missing data
Creators: name: Bertin-Mahieux, Thierry
name: Grindlay, Graham C.
name: Weiss, Ron J.
name: Ellis, Daniel P. W.
Publisher: name: Columbia University
Year: 2011
Subjects: Electrical engineering

description: Building models of the structure in musical signals raises the question of how to evaluate and compare different modeling approaches. One possibility is to use the model to impute deliberately removed patches of missing data, then to compare the model's predictions with the part that was removed. We analyze a corpus of popular music audio represented as beat-synchronous chroma features, and compare imputation based on simple linear prediction to more complex models including nearest neighbor selection and shift-invariant probabilistic latent component analysis. Simple linear models perform best according to Euclidean distance, despite producing stationary results which are not musically meaningful. We therefore investigate alternate evaluation measures and observe that an entropy difference metric correlates better with our expectations for musically consistent reconstructions. Under this measure, the best-performing imputation algorithm reconstructs masked sections by choosing the nearest neighbor to the surrounding observations within the song. This result is consistent with the large amount of repetition found in pop music.
Eignung von Wetterindexversicherungen zur Risikoreduzierung in Ackerbaubetrieben : eine Analyse in Regionen Deutschlands mit moderaten Standortbedingungen
Creators: name: Urban, Juliane Amelie Clarissa
Publisher: name: Universitäts- und Landesbibliothek Sachsen-Anhalt
Year: 2019
Subjects: subject: 368

description: Volatile Kosten, Erträge und Preise führen zu Erfolgsschwankungen. Zur Risikoreduzierung können Landwirte Instrumente wie Wetterindexversicherungen (WIV) einsetzen. Diese setzen i.d.R. an einzelnen Risikoquellen an. Durch die diversen Risikoquellen bemisst sich ihre Wirkung erst anhand der Schwankungen einer übergeordneten Erfolgsgröße. Vor diesem Hintergrund wird das Potenzial von WIVs analysiert, um die Volatilität des einzelbetrieblichen Gesamtdeckungsbeitrags zu reduzieren. Als Maßstab diente die Hedgingeffektivität (HE). Methodisch wurden eine historische Simulation und ein Risikoprogrammierungsansatz angewandt. Die HE fiel überwiegend sehr gering aus oder das Risiko erhöhte sich sogar. Zudem variierte die HE in Abhängigkeit von der Hedgingstrategie und der einzelbetrieblichen Situation. Aufgrund der Vielzahl von Risikoquellen sind zwingend die Schwankungen einer übergeordneten Erfolgsgröße zu betrachten. Nur dann können fundierte Risikomanagemententscheidungen abgeleitet werden.
description: The economic success of farming is subject to fluctuations due to volatile costs, yields and prices. To reduce performance risk, weather index insurances (WII) can be used. These instruments usually address a single risk factor. Its capacity to reduce farm specific performance risk, however, must be evaluated by measuring how WII reduce the volatility of a relevant performance figure. The aim of this study is to analyze how WII reduce the volatility of farm specific total gross margins. Measure is the hedging efficiency (HE), which is determined by a historic simulation and a risk programming approach. For most analyzed farms the HE was quite low or performance risk increased using WII. The whole-farm HE varies depending on the hedging strategy and is highly farm specific. Due to the influence of other risk factors, it is necessary to analyze the HE of WII with regard to a relevant superordinate performance figure. This is important to derive well-grounded risk management decisions.
TAPI: Transactions for Accessing Public Infrastructure
Creators: name: Blaze, Matt
name: Ioannidis, John
name: Ioannidis, Sotiris
name: Keromytis, Angelos D.
name: Nikander, Pekka
name: Prevelakis, Vassilis
Publisher: name: Columbia University
Year: 2003
Subjects: Computer science

description: This paper describes TAPI, an offline scheme intended for general Internet-based micropayments. TAPI, which extends and combines concepts from the KeyNote Microchecks and OTPCoins architectures, encodes risk management rules in bank-issued users' credentials which are in turn used to acquire small-valued payment tokens. The scheme has very low transaction overhead and can be tuned to use different risk strategies for different environments and clients.
A Large-Scale Evaluation of Acoustic and Subjective Music Similarity Measures
Creators: name: Berenzweig, Adam
name: Logan, Beth
name: Ellis, Daniel P. W.
name: Whitman, Brian
Publisher: name: Columbia University
Year: 2003
Subjects: Electrical engineering
Artificial intelligence

description: Subjective similarity between musical pieces and artists is an elusive concept, but one that must be pursued in support of applications to provide automatic organization of large music collections. In this paper, we examine both acoustic and subjective approaches for calculating similarity between artists, comparing their performance on a common database of 400 popular artists. Specifically, we evaluate acoustic techniques based on Mel-frequency cepstral coefficients and an intermediate 'anchor space' of genre classification, and subjective techniques which use data from The All Music Guide, from a survey, from playlists and personal collections, and from web-text mining. We find the following: (1) Acoustic-based measures can achieve agreement with ground truth data that is at least comparable to the internal agreement between different subjective sources. However, we observe significant differences between superficially similar distribution modeling and comparison techniques. (2) Subjective measures from diverse sources show reasonable agreement, with the measure derived from co-occurrence in personal music collections being the most reliable overall. (3) Our methodology for largescale cross-site music similarity evaluations is practical and convenient, yielding directly comparable numbers for different approaches. In particular, we hope that our information-retrieval-based approach to scoring similarity measures, our paradigm of sharing common feature representations, and even our particular dataset of features for 400 artists, will be useful to other researchers.
Additional file 1 of Renal interferon-inducible protein 16 expression is associated with disease activity and prognosis in lupus nephritis
Creators: name: Wang, Xueyao
name: Fu, Shaojie
name: Yu, Jinyu
name: Ma, Fuzhe
name: Zhang, Lihong
name: Wang, Jiahui
name: Wang, Luyu
name: Tan, Yue
name: Yi, Huanfa
name: Wu, Hao
name: Xu, Zhonggao
Publisher: name: figshare
Year: 2023
Subjects: subject: Biophysics
subject: Biochemistry
subject: Medicine
subject: Cell Biology
subject: Genetics
subject: FOS: Biological sciences
subject: Molecular Biology
subject: Physiology
subject: Chemical Sciences not elsewhere classified
subject: Immunology
subject: FOS: Clinical medicine
subject: Biological Sciences not elsewhere classified
subject: Developmental Biology
subject: Marine Biology
subject: Cancer

description: Additional file 1.
The Million Song Dataset
Creators: name: Bertin-Mahieux, Thierry
name: Ellis, Daniel P. W.
name: Whitman, Brian
name: Lamere, Paul
Publisher: name: Columbia University
Year: 2011
Subjects: Information science

description: We introduce the Million Song Dataset, a freely-available collection of audio features and metadata for a million contemporary popular music tracks. We describe its creation process, its content, and its possible uses. Attractive features of the Million Song Database include the range of existing resources to which it is linked, and the fact that it is the largest current research dataset in our field. As an illustration, we present year prediction as an example application, a task that has, until now, been difficult to study owing to the absence of a large set of suitable data. We show positive results on year prediction, and discuss more generally the future development of the dataset.
Effect of addition of different additives: Magnesium sulfate and dexamethasone versus plain bupivacaine in ultrasound-guided erector spinae plane block in pediatrics undergoing repair of inguinal hernia
Creators: name: Aref, Fatma Ahmed Mostafa
name: Abdelaziz, Nabila Mohammed
name: Elazazzi, Hesham Mohammed
name: Fahmy, Niven Gerges
Publisher: name: Taylor & Francis
Year: 2023
Subjects: subject: Medicine
subject: Cell Biology
subject: Genetics
subject: FOS: Biological sciences
subject: Physiology
subject: Immunology
subject: FOS: Clinical medicine
subject: Biological Sciences not elsewhere classified

description: Erector spinae plane (ESP) block has been evaluated in many studies in pediatric surgeries by the use of postoperative rescue analgesia which is the objective parameter assessing the efficacy of the technique in controlling postoperative pain. Adjuvants were used with ESP block to densify its postoperative analgesia. Magnesium sulfate was used for suppressing somatic, endocrine and autonomic reflexes induced by noxious stimuli during surgery. Dexamethasone is a highly potent glucocorticoid that has been used in different regional anesthesia to prolong the anesthetic effect of the local anesthesia by inducing local vasoconstriction. Sixty pediatric patients underwent inguinal hernia repair under general anesthesia, and then they were assigned randomly into three groups that received ESP block either with local anesthetic alone or with magnesium sulfate or dexamethasone. Our study revealed no statistical significance among the three groups as regards demographic and vital data. Children’s Hospital Eastern Ontario Pain Scale score for postoperative assessment of magnesium sulfate and dexamethasone which were added to bupivacaine in ESP block had a better score than bupivacaine alone with high statistical significance. Also, magnesium sulfate and dexamethasone had a delayed first-dose postoperative rescue analgesia with significant statistical value (P value = 0.002) and total postoperative doses of postoperative rescue analgesia were lesser in magnesium sulfate and dexamethasone groups with marked statistical significance (P value < 0.001). As regards complications, there were minor ones in the form of mild bruising and mild pain at injection site with no statistical significance between the three groups (P value = 0.108). In our study, magnesium sulfate and dexamethasone added to bupivacaine in ESP block prolonged the duration of postoperative pain control and decreased the consumption of postoperative analgesia than bupivacaine alone. No major complications were recorded in our study in the three groups which solidify the safety of the technique.
Clustering beat-chroma patterns in a large music database
Creators: name: Bertin-Mahieux, Thierry
name: Weiss, Ron J.
name: Ellis, Daniel P. W.
Publisher: name: Columbia University
Year: 2010
Subjects: Electrical engineering
Information science

description: A musical style or genre implies a set of common conventions and patterns combined and deployed in different ways to make individual musical pieces; for instance, most would agree that contemporary pop music is assembled from a relatively small palette of harmonic and melodic patterns. The purpose of this paper is to use a database of tens of thousands of songs in combination with a compact representation of melodic-harmonic content (the beat-synchronous chromagram) and data-mining tools (clustering) to attempt to explicitly catalog this palette — at least within the limitations of the beat-chroma representation. We use online k-means clustering to summarize 3.7 million 4-beat bars in a codebook of a few hundred prototypes. By measuring how accurately such a quantized codebook can reconstruct the original data, we can quantify the degree of diversity (distortion as a function of codebook size) and temporal structure (i.e. the advantage gained by joint quantizing multiple frames) in this music. The most popular codewords themselves reveal the common chords used in the music. Finally, the quantized representation of music can be used for music retrieval tasks such as artist and genre classification, and identifying songs that are similar in terms of their melodic-harmonic content.
Using Voice Segments to Improve Artist Classification of Music
Creators: name: Berenzweig, Adam
name: Ellis, Daniel P. W.
name: Lawrence, Steve
Publisher: name: Columbia University
Year: 2002
Subjects: Electrical engineering
Artificial intelligence

description: Is it easier to identify musicians by listening to their voices or their music? We show that for a small set of pop and rock songs, automatically-located singing segments form a more reliable basis for classification than using the entire track, suggesting that the singer‘s voice is more stable across different performances, compositions, and transformations due to audio engineering techniques than the instrumental background. The accuracy of a system trained to distinguish among a set of 21 artists improves by about 15% (relative to the baseline) when based on segments containing a strong vocal component, whereas the system suffers by about 35% (relative) when music-only segments are used. In another experiment on a smaller set, however, performance drops by about 35% (relative) when the training and test sets are selected from different albums, suggesting that the system is learning album-specific properties possibly related to audio production techniques, musical stylistic elements, or instrumentation, even when attention is directed toward the supposedly more stable vocal regions.
DEP Bulletin: Volume 36 Issue 16
Creators: name: No Name Supplied
Publisher: name: No Publisher Supplied
Year: 2012

description: The DEP bulletin is a semi-monthly publication of the New Jersey Department of Environmental Protection. It contains a list of construction permit applications recently filed or acted upon by the Department along with a calendar of events of interest, a schedule of public hearings, and Environmental Impact Statements acted upon during the period.
Effects of high-dose L-carnitine supplementation on diaphragmatic function in patients with respiratory failure: A randomized clinical trial
Creators: name: Abdalla, Waleed
name: Ammar, Mona A.
name: Ali, Asmaa
name: Ragab, Dina
name: Taeimah, Mohamed
Publisher: name: Taylor & Francis
Year: 2023
Subjects: subject: Biochemistry
subject: Medicine
subject: Cell Biology
subject: Physiology
subject: FOS: Biological sciences
subject: Cancer
subject: Science Policy
subject: Hematology

description: Evaluation of diaphragmatic function by bedside ultrasound provides information on the degree of disability and the response to treatment intervention in respiratory failure patients with associated respiratory muscle fatigue. This study aimed to assess the impact of high and low-dose L-carnitine supplementation on diaphragmatic muscle function. This was a prospective, randomized, controlled clinical trial (trial registration number NCT05322447), for which approval was obtained from our institutional ethics committee (R80/2021). Participating patients were randomly assigned to two groups of 30 patients each. In the low-dose group, L-carnitine was administered at a dose of 6 g/day. The high-dose group received an intravenous infusion of 18 g/day of L-carnitine. On days 0, 3, and 7, diaphragmatic function was assessed by ultrasound, and serum levels of L-carnitine were measured. Both diaphragmatic excursion (DE) and diaphragmatic thickening fraction (DTf) measurements were positively correlated with serum L-carnitine levels (+r = 0.58 and +r = 0.61, respectively; p< 0.001). High-dose L-carnitine independently influenced the DE only, both in an unadjusted model (p = 0.04) and after adjustment for age and sex (p = 0.02). However, it had no significant effect on DTf, either before (p = 0.25) or after (p = 0.17) adjustment. Serum levels of L-carnitine are positively correlated with the two measures of diaphragmatic function (DE and DTf). Moreover, high-dose L-carnitine supplementation had rapid and significant positive effects on DE. This improvement indirectly enhanced patient outcomes and resulted in shorter stays in the Intensive Care Unit and hospital.
Large-scale cover song recognition using hashed chroma landmarks
Creators: name: Bertin-Mahieux, Thierry
name: Ellis, Daniel P. W.
Publisher: name: Columbia University
Year: 2011
Subjects: Artificial intelligence

description: Cover song recognition, also called version identification, can only be solved by exposing the underlying tonal content of music. Apart from obvious applications in copyright enforcement, techniques for cover identification can also be used to find patterns and structure in music datasets too large for any musicologist to even listen to. Much progress has been made on cover song recognition, but work to date has been reported on datasets of at most a few thousand songs, using algorithms that simply do not scale beyond the capacity of a small portable music player. In this paper, we consider the problem of finding covers in a database of a million songs, and we only consider algorithms that can deal with such data. Using a fingerprinting-inspired model, we present the first results of cover song recognition on the Million Song Dataset. This task has been renewed by the availability of so many tracks, and this work is intended to be the first step towards a practical solution.
Anchor Space for Classification and Similarity Measurement of Music
Creators: name: Berenzweig, Adam
name: Ellis, Daniel P. W.
name: Lawrence, Steve
Publisher: name: Columbia University
Year: 2003
Subjects: subject: Electrical engineering
subject: Mathematics
subject: FOS: Mathematics

description: This paper describes a method of mapping music into a semantic space that can be used for similarity measurement, classification, and music information retrieval. The value along each dimension of this anchor space is computed as the output from a pattern classifier which is trained to measure a particular semantic feature. In anchor space, distributions that represent objects such as artists or songs are modeled with Gaussian mixture models, and several similarity measures are defined by computing approximations to the Kullback-Leibler divergence between distributions. Similarity measures are evaluated against human similarity judgements. The models are also used for artist classification to achieve 62% accuracy on a 25-artist set, and 38% on a 404-artist set (random guessing achieves 0.25%). Finally, we describe a music similarity browsing application that makes use of the fact that anchor space dimensions are meaningful to users.
Correction to: Safety and efficacy of nivolumab in combination with sunitinib or pazopanib in advanced or metastatic renal cell carcinoma: the CheckMate 016 study
Creators: name: Amin, Asim
name: Plimack, Elizabeth R
name: Ernstoff, Marc S
name: Lewis, Lionel D
name: Bauer, Todd M
name: McDermott, David F
name: Carducci, Michael
name: Kollmannsberger, Christian
name: Rini, Brian I
name: Heng, Daniel Y C
name: Knox, Jennifer
name: Voss, Martin H
name: Spratlin, Jennifer
name: Berghorn, Elmer
name: Yang, Lingfeng
name: Hammers, Hans J
Publisher: name: University of Calgary
Year: 2019

description: .
Modeling User Search Behavior for Masquerade Detection
Creators: name: Ben Salem, Malek
name: Stolfo, Salvatore
Publisher: name: Columbia University
Year: 2011
Subjects: Computer science

description: Masquerade attacks are a common security problem that is a consequence of identity theft. This paper extends prior work by modeling user search behavior to detect deviations indicating a masquerade attack. We hypothesize that each individual user knows their own file system well enough to search in a limited, targeted and unique fashion in order to find information germane to their current task. Masqueraders, on the other hand, will likely not know the file system and layout of another user's desktop, and would likely search more extensively and broadly in a manner that is different than the victim user being impersonated. We identify actions linked to search and information access activities, and use them to build user models. The experimental results show that modeling search behavior reliably detects all masqueraders with a very low false positive rate of 1.1%, far better than prior published results. The limited set of features used for search behavior modeling also results in large performance gains over the same modeling techniques that use larger sets of features.
EasyVPN: IPsec Remote Access Made Easy
Creators: name: Benvenuto, Mark C.
name: Keromytis, Angelos D.
Publisher: name: Columbia University
Year: 2003
Subjects: Computer science

description: Telecommuting and access over a Wireless LAN require strong security at the network level. Although IPsec is well-suited for this task, it is difficult to configure and operate a large number of clients. To address this problem, we leverage the almost universal deployment and use of web browsers capable of SSL/TLS connections to web servers and the familiarity of users with such an interface. We use this mechanism to create configurations and certificates that will be downloaded to the user's machine and be used by a program to perform all configuration on the user's system. Our system builds on common security protocols and standards such as IKE, X.509, and SSL/TLS to provide users with a secure-access environment that "just works." One of the main goals of the system is ease of use both for the users and the system administrators that maintain the infrastructure. We describe our implementation that uses Linux FreeS/WAN and Windows to show the practicality of the approach.
Protective effect of prebiotic and exercise intervention on knee health in a rat model of diet-induced obesity
Creators: name: Rios, Jaqueline Lourdes
name: Bomhof, Marc R.
name: Reimer, Raylene A.
name: Hart, David A.
name: Collins, Kelsey H.
name: Herzog, Walter
Publisher: name: Kinesiology
Year: 2019

description: Obesity, and associated metabolic syndrome, have been identified as primary risk factors for the development of knee osteoarthritis (OA), representing nearly 60% of the OA patient population. In this study, we sought to determine the effects of prebiotic fibre supplementation, aerobic exercise, and the combination of the two interventions, on the development of metabolic knee osteoarthritis in a high-fat/high-sucrose (HFS) diet-induced rat model of obesity. Twelve-week-old male Sprague-Dawley rats were randomized into five groups: a non-exercising control group fed a standard chow diet, a non-exercising group fed a HFS diet, a non-exercising group fed a HFS diet combined with prebiotic fibre supplement, an exercise group fed a HFS diet, and an exercise group fed a HFS diet combined with prebiotic fibre supplement. Outcome measures included knee joint damage, percent body fat, insulin sensitivity, serum lipid profile, serum endotoxin, serum and synovial fluid cytokines and adipokines, and cecal microbiota. Prebiotic fibre supplementation, aerobic exercise, and the combination of the two interventions completely prevented knee joint damage that is otherwise observed in this rat model of obesity. Prevention of knee damage was associated with a normalization of insulin resistance, leptin levels, dyslipidemia, gut microbiota, and endotoxemia in the HFS-fed rats.