Miracle-dz/UniFAR-FTUs huggingface dataset:
The Hyperlinked Scandinavian News Ecology

The article presents a network analysis of 22,861,013 geocoded external hyperlinks, collected from 230 Danish, 220 Norwegian and 208 Swedish news websites in 2016. The analysis asks what the structural properties of the Scandinavian media systems—including its geography and ownership structures—mean for news outlets’ centrality within the hyperlinked news ecology. The analysis finds that whereas incumbent legacy media occupy central positions, about one third of the network is absent from the hyperlinked interaction, primarily local, independently owned newspapers. A multiple linear regression analysis shows that national distribution and corporate ownership correlates to network centrality more than other predictors. As brokers in the network consist of the large, legacy, capital-based news organisations, hyperlink connectivity is primarily characterised by proximity to the centres of power, corporate ownership, agenda setting incumbency and national distribution.
Learning expressive linkage rules from sparse data

A central problem in the context of the Web of Data as well as in data integration in general is to identify entities in different data sources that describe the same real-world object. There exists a large body of research on entity resolution. Interestingly, most of the existing research focuses on entity resolution on dense data, meaning data that does not contain too many missing values. This paper sets a different focus and explores learning expressive linkage rules from as well as applying these rules to sparse data, i.e. data exhibiting a large amount of missing values. Sparse data is a common challenge in application domains such as e-commerce, online hotel booking, or online recruiting. We propose and compare three entity resolution methods that employ genetic programming to learn expressive linkage rules from sparse data. First, we introduce the GenLinkGL algorithm which learns groups of matching rules and applies specific rules out of these groups depending on which values are missing from a pair of records. Next, we propose GenLinkSA, which employs selective aggregation operators within rules. These operators exclude misleading similarity scores (which result from missing values) from the aggregations, but on the other hand also penalize the uncertainty that results from missing values. Finally, we introduce GenLinkComb, an algorithm which combines the central ideas of the previous two into one integrated method. We evaluate all methods using six benchmark datasets: three of them are e-commerce product datasets, the other datasets describe restaurants, movies, and drugs. We show improvements of up to 16% F-measure compared to handwritten rules, on average 12% F-measure improvement compared to the original GenLink algorithm, 15% compared to EAGLE, 8% compared to FEBRL, and 5% compared to CoSum-P.
Improving Distributed Similarity Join in Metric Space with Error-bounded Sampling

Given two sets of objects, metric similarity join finds all similar pairs of objects according to a particular distance function in metric space. There is an increasing demand to provide a scalable similarity join framework which can support efficient query and analytical services in the era of Big Data. The existing distributed metric similarity join algorithms adopt random sampling techniques to produce pivots and utilize holistic partitioning methods based on the generated pivots to partition data, which results in data skew problem since both the generated pivots and the partition strategies have no quality guarantees. To address the limitation, we propose SP-Join, an end-to-end framework to support distributed similarity join in metric space based on the MapReduce paradigm, which (i) employs an estimation-based stratified sampling method to produce pivots with quality guarantees for any sample size, and (ii) devises an effective cost model as the guideline to split the whole datasets into partition in map and reduce phases according to the sampled pivots. Although obtaining an optimal set of partitions is proven to be NP-Hard, SP-Join adopts efficient partitioning strategies based on such a cost model to achieve an even partition with explainable quality. We implement our framework upon Apache Spark platform and conduct extensive experiments on four real-world datasets. The results show that our method significantly outperforms state-of-the-art methods.
Topochemical Engineering of Cellulose-Based Functional Materials

Topochemical engineering is a method of designing the fractionation (disassembly) and fabrication (assembly) of highly engineered functional materials using a combination of molecular and supramolecular techniques. Cellulose is one of the naturally occurring biopolymers, currently considered to be an important raw material for the design and development of sustainable products and processes. This feature article deals with new insights into how cellulose can be processed and functionalized using topochemical engineering in order to create functional fibers, enhance biopolymer dissolution in water-based solvents, and control the shaping of porous materials. Subsequently, topochemical engineering of cellulose offers a variety of morphological structures such as highly engineered fibers, functional cellulose beads, and reactive powders that find relevant applications in pulp bleaching, enzyme and antimicrobial drug carriers, ion exchange resins, photoluminescent materials, waterproof materials, fluorescent materials, flame retardants, and template materials for inorganic synthesis. The topochemical engineering of biopolymers and biohybrids is an exciting and emerging area of research that can boost the design of new bioproducts with novel functionalities and technological advancements for biobased industries.
Impact of Time to Start Treatment Following Infection with Application to Initiating HAART in HIV‐Positive Patients

Summary We estimate how the effect of antiretroviral treatment depends on the time from HIV‐infection to initiation of treatment, using observational data. A major challenge in making inferences from such observational data arises from biases associated with the nonrandom assignment of treatment, for example bias induced by dependence of time of initiation on disease status. To address this concern, we develop a new class of Structural Nested Mean Models (SNMMs) to estimate the impact of time of initiation of treatment after infection on an outcome measured a fixed duration after initiation, compared to the effect of not initiating treatment. This leads to a SNMM that models the effect of multiple dosages of treatment on a time‐dependent outcome, in contrast to most existing SNNMs, which focus on the effect of one dosage of treatment on an outcome measured at the end of the study. Our identifying assumption is that there are no unmeasured confounders. We illustrate our methods using the observational Acute Infection and Early Disease Research Program (AIEDRP) Core01 database on HIV. The current standard of care in HIV‐infected patients is Highly Active Anti‐Retroviral Treatment (HAART); however, the optimal time to start HAART has not yet been identified. The new class of SNNMs allows estimation of the dependence of the effect of 1 year of HAART on the time between estimated date of infection and treatment initiation, and on patient characteristics. Results of fitting this model imply that early use of HAART substantially improves immune reconstitution in the early and acute phase of HIV‐infection.
Building Blocks of Assistant Based Speech Recognition for Air Traffic Management Applications

In air traffic control rooms around the world paper flight strips are replaced through different digital solutions. This enables other systems to access the instructed air traffic controller (ATCo) commands and use them for other purposes. Digital flight strip solutions, however, require manual input from the ATCo and, therefore, increase the workload. Recently the AcListant® project has validated that Assistant Based Speech Recognition (ABSR, which integrates a speech recognizer with an assistant system) could be a solution to avoid this increase of workload. However, adaptation of ABSR to new environments usually requires a lot of data, time and expertise, which makes the process expensive. The MALORCA project used machine learning (ML) algorithms to provide a generic, cheap and effective approach for adaptation. Therefore, ABSR was divided into conceptual modules that contain generic parts (building blocks) and domain specific models. As first show case ABSR was auto-matically adapted with radar data and voice recordings from Prague and Vienna approach. The fully trained system reaches command recognition rates (RR) of 92% (Prague) resp. 83% (Vienna) and command recognition error rates (ER) of 0.6% (Prague) resp. 3.2% (Vienna). The building blocks and models and their effect on RR and ER are presented in this paper.
Efficient Regulation

Regulation of economic activity is ubiquitous around the world, yet standard theories predict it should be rather uncommon. I argue that the ubiquity of regulation is explained not so much by the failure of markets, or by asymmetric information, as by the failure of courts to solve contract and tort disputes cheaply, predictably, and impartially. The approach accounts for the ubiquity of regulation, for its growth over time, as well as for the fact that contracts themselves are heavily regulated. It also makes predictions, both across activities and across jurisdictions, for the efficiency of regulation and litigation as strategies of enforcing efficient conduct.
Title A Hybrid System Approach to the Analysis and Design ofPower Grid Dynamic Performance

We describe an approach to the analysis and design of power grid dynamic performance based on hybrid systems theory. Power grid is a large-scale Cyber-Physical System for transmission of electrical energy. The joint dynamics of physical processes and cyber elements in power grids are typical of a mixture of continuous and discrete behaviors, that is, hybrid dynamics. We address problems on stability that are basic concerns in the performance of current and future power grids with the hybrid dynamics. Measures for stability of power grids are interpreted as safety specifications in hybrid system models and are translated into restrictions on the systems’ reachable sets of states. Algorithmic reachability analysis of hybrid systems enables analysis of safe initial states and hence quantitative estimation of stability regions. Also it contributes to synthesis of safe initial states as well as switching conditions in order to satisfy safety specifications in a power grid. We demonstrate the approach for two problems on transient stability of the single machine-infinite bus system and on fault release control of a multi-machine power grid.
FABP4 suppresses proliferation and invasion of hepatocellular carcinoma cells and predicts a poor prognosis for hepatocellular carcinoma

Adipocyte fatty acid‐binding protein (FABP4) is abundant in macrophage and adipocyte. It is known to be involved in lipid metabolism. The role of FABP4 has been reported in various cancers, such as non‐small cell lung cancer, breast cancer, ovarian cancer, and prostatic cancer. However, its role remains unclear in hepatocellular carcinoma (HCC). In our study, we investigated the expression of FABP4 at both mRNA and protein levels, and by examining 175 cases of patients with cancer of the liver tissue microarray, the significance between the expression of FABP4 and clinical characteristics had been discussed. We found that FABP4 was lowly expressed in HCC tissues compared to the corresponding tissue adjacent, and the expression of FABP4 was significantly associated with the tumor size, PVTT, recurrence‐free survival and overall survival. Moreover, multivariate Cox regression analysis indicated that the expression of FABP4, Alb, AFP, HBsAg, and PVTT were independent risk factors for overall survival, and the expression of FABP4, AFP, GGT, tumor size, and encapsulation were independent risk factors for HCC recurrence. In addition, we revealed that FABP4 suppressed HCC cell proliferation and invasion in vitro. Moreover, overexpression of FABP4 led to inhibit tumor growth and decreased tumor volume in vivo. These phenotypes were associated with altered expression of Snail and p‐STAT3. Our studies thus suggest that FABP4 could be a potential target for HCC chemotherapy.
Microbial community and methanol conversion during long-term continuous operation of a methanol-fed UASB reactor

A mesophilic (35 ̊C) UASB reactor was operated for treating synthetic wastewater containing methanol as sole carbon source at various organic loading rate. The reactor was successfully operated at OLR 30kg COD/m 3 /d for approximately 300 days with over 95% soluble CODCr removal efficiency. Granules of 0.1 to 2 mm in diameter mainly consist of aggregated coccoid cells. Specific methanogenic activity tests indicate that the methanol-methane pathway and the methanol-H2/CO2-methane pathway are predominant in the methane fermentation of the methanol. The results of cloning and fluorescence in situ hybridization analysis suggests that Methanomethylovorans hollandica were predominant in the reactor, and formed a large cluster as a granule, which is different from the Methanosarcina-dominant community previously considered in the researches on anaerobic methanol treatment.
Mouse adenovirus type 1 and human adenovirus type 5 differ in endothelial cell tropism and liver targeting

For adenovirus vectors derived from human serotype 5 (Ad5), the efficiency and safety after intravascular delivery is hindered by their sequestration in nontarget tissues, predominantly the liver. The latter is largely dictated by adenovirus binding to blood coagulation zymogens. In addition, several target cells, such as endothelial and smooth muscle cells, are difficult to transduce by Ad5 due to the low expression of the primary coxsackie‐adenovirus receptor (CAR). Therefore, alternative adenovirus serotypes are being explored.
Truth and Bias in M&A Target Fairness Valuations: Appraising the Appraisals

In U.S. M&A transactions, target directors are effectively required to seek and consider a “fairness opinion” and supporting valuations before accepting a takeover offer. Despite their legal status, critics have argued that these valuations are biased, and that even unbiased valuations would not be useful to public companies, which can use their pre-deal stock price as an appraisal of their value. I develop and implement tests for the usefulness and the bias of fairness opinion valuations, and find tight evidence for both. They impound information about fundamental mispricing in targets, and prospective deal synergies, which could make them useful to directors in exercising their duties. They also exhibit predictable bias: providers toggle their discount-rate assumptions ex post to rationalize negotiated deal prices. However, this bias has been constrained by judicial scrutiny in recent years. These findings suggest that third-party appraisal could have a useful role in M&A governance, and suggest avenues for reform.
Conflicts in Knowledge Management : Vistiting the Hidden Partner

As knowledge gains a reputation for being a critical resource in the information-intensive economy, organizations have doubled their efforts in trying to extract value from knowledge management policies. One particular aspect of knowledge management, which has gone unnoticed in academic research, is the presence of conflicts in knowledge activities. By adopting a conflict perspective of knowledge activities, this study arrives at a two-dimensional framework that defines knowledge conflicts in terms of its type and nature. Central to this paper is the fundamental idea that conflicts form an integral part of knowledge management and depending on how they are managed; conflicts may be formidable partners or dangerous adversaries in the corporate quest for knowledge-derived competitiveness.
Job Stress and Burnout among Academic Career Anaesthesiologists at an Egyptian University Hospital.

OBJECTIVES There is compelling evidence that anaesthesiology is a stressful occupation and, when this stressful occupation is associated with an academic career, the burnout level is high. This study aimed to assess the predictors and prevalence of stress and burnout, associated sociodemographic characteristics, and job-related features. METHODS A cross-sectional survey study was carried out at Mansoura University Hospital in Egypt among 98 anaesthesiologists who had academic careers. The English version of the Maslach Burnout Inventory-Human Services Survey (MBI-HSS) scale and the Workplace Stress Scale of the American Institute of Stress were used to measure job stress and burnout. Data were analysed according to the guidelines for data processing and an analysis of the scales used. RESULTS The participation rate of this study was 73.1%, where 69.4% were encountering job stress, while 62.2% experienced emotional exhaustion, 56.1% depersonalisation, and 58.2% reduced personal capacity. There was a significant positive correlation between job stress and MBI-HSS subscales. Residents and assistant lecturers were the most affected group. The strongest significant single predictor of all burnout dimensions was a lack of job support. CONCLUSION Stress and burnout among academic anaesthesiologists were caused by the lack of job support; this was especially true among residents and assistant lecturers. We can conclude that a well-organised institutional strategy to mitigate the heavy professional demands of academic anaesthesiologists' will relieve their stress and burnout.
Toward the obsolescence of the schizophrenia hypothesis

tually represses creative ways of understanding and taking responsibility for ourselves and our lives. The medical model stands for constricted consciousness and the standardization of behavior. Here is the question I would like to see addressed in public debates: Is an extra degree of social control, one that often hurts and humiliates people, worth the price of endarkenment and enfeeblement? At a time when the human species is threatened with selfextinction, can we afford to blind and cripple ourselves with a politically convenient deception? 01990 The Institute of Mind and Behavior. lnc. The Journal of Mind and Behavior Summer and Autumn 1990. Volume II. Numbers 3 and 4 Pages 259 1131284 1381 ISSN 0271-01l7 ISB~ 0-930195-05-1
Micropatterning as a tool to identify regulatory triggers and kinetics of actin-mediated endothelial mechanosensing

ABSTRACT Developmental processes, such as angiogenesis, are associated with a constant remodeling of the actin cytoskeleton in response to different mechanical stimuli. The mechanosensitive transcription factors MRTF-A (MKL1) and YAP (also known as YAP1) are important mediators of this challenging adaptation process. However, it is as yet unknown whether both pathways respond in an identical or in a divergent manner to a given microenvironmental guidance cue. Here, we use a micropatterning approach to dissect single aspects of cellular behavior in a spatiotemporally controllable setting. Using the exemplary process of angiogenesis, we show that cell–cell contacts and adhesive surface area are shared regulatory parameters of MRTF and YAP on rigid 2D surfaces. By analyzing MRTF and YAP under laminar flow conditions and during cell migration on dumbbell-shaped microstructures, we demonstrate that they exhibit different translocation kinetics. In conclusion, our work promotes the application of micropatterning techniques as a cell biological tool to study mechanosensitive signaling in the context of angiogenesis. Summary: A specifically tailored set of micropatterns is used as a cell biological tool to study the regulation of mechanosensitive transcription factors in an angiogenesis model.
RE-EVALUATION OF SURFACE RUPTURE PARAMETERS AND FAULTING SEGMENTATION OF THE 2001 KUNLUNSHAN EARTHQUAKE ( MW 7 . 8 ) , NORTHERN TIBETAN PLATEAU , CHINA

The 14 November 2001, Mw=7.8 Kunlunshan earthquake ruptured the westernmost part of the Kunlun Fault, northern Tibetan Plateau. The main segment affected by this event was the Kusaihu segment. Field investigations allowed us to constrain the length, the width and the co-seismic horizontal displacement distribution of the Kunlunshan earthquake rupture zone. The mapped surface rupture zone starts from 90.257°E in the west and ends at 94.795°E in the east with a total length of 426 km. It consists of three main sections, the western strike-slip section, the transtensional section and the eastern strike-slip section. The rupture zone is oriented N100o±10oE on average. The distribution of the co-seismic horizontal displacements is characterized by multiple peaks departing clearly from a general bell-shape distribution. Reassessment of the maximum co-seismic horizontal left-lateral displacement yields a value of 7.6±0.4m at the site (35.767oN, 93.323oE) consistent with independent measurements derived from Insar and seismology. From this site the horizontal displacement decreases unevenly to both the west and east. Co-seismic vertical (reverse) displacement is also noted at the eastern end of the rupture but it remains much smaller than the horizontal component. The width of the rupture zone varies from site to site from several meters to few kilometers. The maximum width measured reaches 8km along the Yuxi Feng subsection where a large number of shaking related cracks were well developed.
Coffee plant – pollinator interactions : a review

Coffee (genus Coffea L.) is one of the most critical global agricultural crops. Many studies have focused on coffee plants and their associated insects. This review will summarize work specifically relating to coffee plant – pollinator interactions. We review the current status of coffee as a worldwide commodity, botanical aspects of coffee, and insects associated with coffee pollination, and we assess the current understanding of the role of different pollinator taxa in increasing fruit set and yield. Résumé : Le café (le genre Coffea L.) représente une des cultures agricoles globales les plus importantes. Plusieurs études se sont intéressées aux caféiers et aux insectes qui leur sont associés. Notre rétrospective résume les travaux reliés spécifiquement aux interactions caféiers–pollinisateurs. Nous examinons le statut actuel du café comme denrée mondiale, les aspects botaniques du café et les insectes associés à la pollinisation du café et nous évaluons la compréhension actuelle des rôles des différents taxons de pollinisateurs dans l’augmentation de la nouaison et du rendement. [Traduit par la Rédaction]
Semi-Tomographic Gamma Scanning Technique for Non-Destructive Assay of Radioactive Waste Drums

Segmented gamma scanning (SGS) and tomographic gamma scanning (TGS) are two traditional detection techniques for low and intermediate level radioactive waste drum. This paper proposes one detection method named semi-tomographic gamma scanning (STGS) to avoid the poor detection accuracy of SGS and shorten detection time of TGS. This method and its algorithm synthesize the principles of SGS and TGS. In this method, each segment is divided into annual voxels and tomography is used in the radiation reconstruction. The accuracy of STGS is verified by experiments and simulations simultaneously for the 208 liter standard waste drums which contains three types of nuclides. The cases of point source or multi-point sources, uniform or nonuniform materials are employed for comparison. The results show that STGS exhibits a large improvement in the detection performance, and the reconstruction error and statistical bias are reduced by one quarter to one third or less for most cases if compared with SGS.