Miracle-dz/UniFAR-FTUs huggingface dataset:
Communication Chains: A Methodology for Assessing the Effects of the Internet on Communication and Travel

Although numerous researchers have investigated the impact on travel of specific telecommunications applications like telecommuting, only rarely has a broader look at the impact of electronic communications on multiple communications media, including travel, been attempted. This is no doubt due in part to the measurement challenges associated with such an attempt. Time-use diaries, activity diaries, or communication logs can provide opportunities for cross-sectional analysis, typically at a single point (or small interval) of time. However, these tools generally do not identify the chain of communication events cascading from a specific message, and thus are unable to capture behavioral linkages between events. Thus, for example, if a cross-sectional study using such a tool finds that greater Internet use is associated with more travel, it has not been established that the Internet use caused the travel; a third-party variable such as income, or a gregarious or variety-seeking personality, may be responsible for both effects separately. On the other hand, following communication chains in a precise and quantifiable way is a daunting task for both the researcher and the respondent. The methodology proposed in this study offers a practical middle ground between no data and perfect data on causal linkages. Specifically, for a given Internet activity, we simply ask the respondent to identify its causal antecedent and its likely communication consequences, by checking off the appropriate responses from a list. Obviously, by sacrificing precision and detail we lose the ability to quantify those consequences (e.g., in terms of miles of travel generated or substituted). However, we argue that the qualitative view of causal chains provided by this approach can offer valuable insights not possible from single cross-sectional studies alone. We analyze the relative strengths of effects of a given Internet activity in three ways. Using a 1994 sample of 148 early Internet adopters to illustrate the application of the methodology, we first tabulate the total presence, within the sample, of specific types of effects, to assess the net effect of Internet activities on other communication media. Second, we tabulate the frequency with which specific combinations of effects, or â€œpattern vectors,â€ occur in the sample. Finally, we use cluster analysis to identify latent types of communication chains having relatively similar causal relationships between Internet activities and other media. To establish a theoretical background and context for this study, we briefly summarize the relevant literature and develop a conceptual framework for understanding interactions among communications media. After introducing the survey instrument and methods of analysis, we apply the proposed methodology and discuss key empirical findings.
Verifying the reflective visitor pattern

Computational reflection allows a program to inspect and manipulate the structure or behaviour of itself at runtime. Often this means that it is possible to create more generic or adaptable programs in an elegant way. However, there is little support for specification and automatic verification of reflective programs. We address this problem by implementing, specifying, and verifying a reflective library using a Hoare-logic for a simple language with stored procedures. The latter is important since reflective metadata is modelled on the heap, thus method objects will be realised as stored procedures. We verify memory safety as well as functional correctness of an instance of the reflective visitor pattern, including the reflective library. The entire verification is carried out in our (semi-)automatic verification tool Crowfoot.
A complex of α6 integrin and E-cadherin drives liver metastasis of colorectal cancer cells through hepatic angiopoietin-like 6

Homing of colorectal cancer (CRC) cells to the liver is a non‐random process driven by a crosstalk between tumour cells and components of the host tissue. Here we report the isolation of a liver metastasis‐specific peptide ligand (CGIYRLRSC) that binds a complex of E‐cadherin and α6 integrin on the surface of CRC cells. We identify angiopoietin‐like 6 protein as a peptide‐mimicked natural ligand enriched in hepatic blood vessels of CRC patients. We demonstrate that an interaction between hepatic angiopoietin‐like 6 and tumoural α6 integrin/E‐cadherin drives liver homing and colonization by CRC cells, and that CGIYRLRSC inhibits liver metastasis through interference with this ligand/receptor system. Our results indicate a mechanism for metastasis whereby a soluble factor accumulated in normal vessels functions as a specific ligand for circulating cancer cells. Consistently, we show that high amounts of coexpressed α6 integrin and E‐cadherin in primary tumours represent a poor prognostic factor for patients with advanced CRC.
A new algorithm to Test Suite Reduction based on cluster analysis

Regression testing is a significant activity which occurs during the maintenance level of a software lifecycle. However, it requires a large amount of test cases to test new or modified parts of the software. To address the issue, Test Suite Reduction techniques have been presented. An appropriate technique should generate a minimized test suite which exercises different execution paths within a program while retaining the fault detection capability of the suite admissible. To achieve this, a heuristic algorithm is proposed in this paper. The new algorithm clusters test cases based on the similarity of their execution profiles and sample some representatives to form the reduced test suite. The results of applying the new algorithm to the Siemens suite and comparing to the H algorithm manifest interesting insights into the effectiveness of the proposed algorithm.
A novel engine to underlie the data transmission of social urban sensing applications

Social urban sensing is a new paradigm which exploits human-carried or vehicle-mounted sensors to ubiquitously collect data for large-scale urban sensing. A challenge of such scenario is how to transmit sensed data in situations where the networking infrastructure is intermittent or unavailable. In this context, this paper outlines our researches of a novel engine that uses Opportunistic Networks paradigm to underlie the data transmission of social urban sensing applications. It applies Situation awareness, Fuzzy logic and Machine Learning approaches to perform routing and decision-making process. As we know, this is the first paper to use such approaches in Smart Cities area with focus on social sensing application. As well as being original, the results from our simulations signals the way that further research can be carried out in this area.
On effective superpotentials and Kutasov duality

We derive the effective superpotential for an = 1 SU(Nc) gauge theory with one massless adjoint field and Nf massless fundamental flavors and cubic tree-level superpotential for the adjoint field. This is a generalization of the Affleck-Dine-Seiberg superpotential to gauge theories with one massless adjoint matter field. Using Kutasov's generalization of Seiberg duality, we then find the effective superpotential for a related theory with massive fundamental flavors.
KNOW At The Social Book Search Lab 2016 Mining Track

This paper describes our system for the mining task of the Social Book Search Lab in 2016. The track consisted of two task, the classiﬁcation of book request postings and the task of linking book iden-tiﬁers with references mentioned within the text. For the classiﬁcation task we used text mining features like n-grams and vocabulary size, but also included advanced features like average spelling errors found within the text. Here two datasets were provided by the organizers for this task which were evaluated separately. The second task, the linking of book titles to a work identiﬁer, was addressed by an approach based on lookup tables. For the dataset of the ﬁrst task our approach was ranked third, following two baseline approaches of the organizers with an accuracy of 91 percent. For the second dataset we achieved second place with an accuracy of 82 percent. Our approach secured the ﬁrst place with an F-score of 33.50 for the second task.
Population-Based Study of Blood Biomarkers in Prediction of Subacute Recurrent Stroke

Background and Purpose— Risk of recurrent stroke is high in the first few weeks after transient ischemic attack or stroke and clinical risk prediction tools have only limited accuracy, particularly after the hyperacute phase. Previous studies of the predictive value of biomarkers have been small, been done in selected populations, and have not concentrated on the acute phase or on intensively treated populations. We aimed to determine the predictive value of a panel of blood biomarkers in intensively treated patients early after transient ischemic attack and stroke. Methods— We studied 14 blood biomarkers related to inflammation, thrombosis, atherogenesis, and cardiac or neuronal cell damage in early transient ischemic attack or ischemic stroke in a population-based study (Oxford Vascular Study). Biomarker levels were related to 90-day risk of recurrent stroke as hazard ratio (95% confidence interval) per decile increase, adjusted for age and sex. Results— Among 1292 eligible patients, there were 53 recurrent ischemic strokes within 90 days. There were moderate correlations (r=0.40–0.61; P<0.0001) between the inflammatory biomarkers and between the cell damage and thrombotic subsets. Associations with risk of early recurrent stroke were weak, with significant associations limited to interleukin-6 (adjusted hazard ratio, 1.12; 1.01–1.24; P=0.033) and C-reactive protein (adjusted hazard ratio, 1.15; 1.02–1.30; P=0.022) after adjusting for age, sex, hypertension, smoking, and diabetes mellitus although P-selectin seemed to predict stroke after transient ischemic attack (adjusted hazard ratio, 1.28; 1.00–1.63; P=0.046). Conclusions— In the largest study to date, we found limited predictive use for early recurrent stroke for a panel of inflammatory, thrombotic, and cell damage biomarkers.
LL-37 Immunomodulatory Activity during Mycobacterium tuberculosis Infection in Macrophages

ABSTRACT Tuberculosis is one of the most important infectious diseases worldwide. The susceptibility to this disease depends to a great extent on the innate immune response against mycobacteria. Host defense peptides (HDP) are one of the first barriers to counteract infection. Cathelicidin (LL-37) is an HDP that has many immunomodulatory effects besides its weak antimicrobial activity. Despite advances in the study of the innate immune response in tuberculosis, the immunological role of LL-37 during M. tuberculosis infection has not been clarified. Monocyte-derived macrophages were infected with M. tuberculosis strain H37Rv and then treated with 1, 5, or 15 μg/ml of exogenous LL-37 for 4, 8, and 24 h. Exogenous LL-37 decreased tumor necrosis factor alpha (TNF-α) and interleukin-17 (IL-17) while inducing anti-inflammatory IL-10 and transforming growth factor β (TGF-β) production. Interestingly, the decreased production of anti-inflammatory cytokines did not reduce antimycobacterial activity. These results are consistent with the concept that LL-37 can modulate the expression of cytokines during mycobacterial infection and this activity was independent of the P2X7 receptor. Thus, LL-37 modulates the response of macrophages during infection, controlling the expression of proinflammatory and anti-inflammatory cytokines.
The Role of Contextual Associations in the Selection of Objects

This paper describes a sequence of experiments addressing basic questions about the control of visual attention and the relationship between attention and object recognition. This work reviews compelling findings addressing attentional control on the basis of high-level perceptual properties. In five experiments observers were presented with a rapid sequence of object photographs and instructed to either detect or selectively encode a verbally cued object category. When these object categories (e.g. “baseball”) were preceded by contextual images associated with a given object category (e.g. “baseball diamond”), observers were less likely to accurately report information about the target item. This effect obtained with both detection and discrimination measures. This evidence of attentional capture is particularly strong because associated contexts typically enhance object detection or discrimination, whereas here they harmed performance. These findings demonstrate that observers use relatively abstract and elaborated representations when selecting visual objects on the basis of category. Further, even when observers attempt to ignore depictions of associated contexts these images engage perceptual processing. That is, while participants were able to determine the target of their search categorically, they had relatively little control over the specific types of representations and information employed when performing an object search task. After reviewing these five experiments, conclusions regarding the use of object-context association knowledge in vision are addressed.
Quantitative Interpretation of Tracks for Determination of Body Mass

To better understand the biology of extinct animals, experimentation with extant animals and innovative numerical approaches have grown in recent years. This research project uses principles of soil mechanics and a neoichnological field experiment with an African elephant to derive a novel concept for calculating the mass (i.e., the weight) of an animal from its footprints. We used the elephant's footprint geometry (i.e., vertical displacements, diameter) in combination with soil mechanical analyses (i.e., soil classification, soil parameter determination in the laboratory, Finite Element Analysis (FEA) and gait analysis) for the back analysis of the elephant's weight from a single footprint. In doing so we validated the first component of a methodology for calculating the weight of extinct dinosaurs. The field experiment was conducted under known boundary conditions at the Zoological Gardens Wuppertal with a female African elephant. The weight of the elephant was measured and the walking area was prepared with sediment in advance. Then the elephant was walked across the test area, leaving a trackway behind. Footprint geometry was obtained by laser scanning. To estimate the dynamic component involved in footprint formation, the velocity the foot reaches when touching the subsoil was determined by the Digital Image Correlation (DIC) technique. Soil parameters were identified by performing experiments on the soil in the laboratory. FEA was then used for the backcalculation of the elephant's weight. With this study, we demonstrate the adaptability of using footprint geometry in combination with theoretical considerations of loading of the subsoil during a walk and soil mechanical methods for prediction of trackmakers weight.
Adding ischaemic hand exercise during occlusion of the brachial artery increases the flow‐mediated vasodilation in ultrasound studies of endothelial function

A non‐invasive method has been introduced to study endothelial function by evaluating flow‐mediated, endothelium‐dependent vasodilation of the brachial artery. One weakness of this method is that the post‐occlusion vasodilation response is very small in subjects above the age of 60 years, which is a problem when quantifying endothelial dysfunction above this age. We have therefore evaluated whether a higher post‐occlusion flow stimulus and a larger vasodilation response can be achieved by adding ischaemic hand exercise during the occlusion of the brachial artery. The subject population was men (n=12), aged 60 years, free from cardiovascular disease. B‐mode ultrasound images for the measurement of lumen diameter of the brachial artery were recorded before and after reactive hyperaemia induced by occlusion of the artery. Blood flow velocity was recorded intermittently using a Doppler technique. Hyperaemia was induced in two different ways: first by occlusion only and then by adding ischaemic hand exercise during the occlusion. The results showed that flow velocity was higher and the duration of flow increase was longer after ischaemic hand exercise compared with occlusion only. Two minutes after cuff pressure release, the increase in blood flow velocity was significantly higher after ischaemic hand work compared with occlusion only (P<0·01). The corresponding maximal lumen diameters after cuff pressure release were 4·63 ± 0·35 and 4·45 ± 0·34 respectively (P<0·01). The flow‐mediated vasodilation increased significantly from 2·24 ± 2·00% after occlusion only to 7·42 ± 3·32% after occlusion plus ischaemic hand exercise (P<0·01). In conclusion, this study showed that a maximal endothelial‐dependent vasodilation was not achieved after occlusion only in these 60‐year‐old men. Adding ischaemic hand exercise may therefore be of value when quantifying endothelial dysfunction in this age group.
Crystallization and preliminary X‐ray diffraction analysis of gingipain R2 from Porphyromonas gingivalis in complex with H‐D‐Phe‐Phe‐Arg‐chloromethylketone

Gingipain R2 is a 50 kDa proteinase from the oral pathogenic bacterium Porphyromonas gingivalis. This proteinase, which displays no significant sequence homology to any protein previously analyzed by X‐ray crystallography, has been crystallized using the vapor diffusion method. Two different crystal forms were obtained from a solution containing polyethylene glycol (MW 8,000) (space group P212121) or magnesium sulfate (space group R3) as precipitating agent. Complete diffraction data sets have been collected up to 2.0 and 2.9 Å resolution, respectively. Cell dimensions are a = 51.9 Å, b = 79.9 Å, and c = 99.6 Å (P212121), and a = b = 176.6 Å, and c = 143.4 Å (R3). Considerations of the possible values of Vm accounts for the presence of one monomer per asymmetric unit in the case of the orthorhombic crystal form, whereas the rhombohedral crystal form, together with the analysis of the self‐rotation function, could accommodate a tetramer in the asymmetric unit.
Reforming Consumer Directed Care in Germany : A Woodwork Effect ?

This paper evaluates the incidence and extent of support as well as the remuneration of formal and informal caregivers for recipients of a professionally assisted consumer-directed program, a personal budget, compared to recipients of standard types of home care benefits of the German long-term care insurance, i.e. agency services and cash payments. The evaluation makes use of a long-run social experiment at seven different sites in Germany with a random assignment into a treatment group of personal budget recipients and a control group of standard benefit recipients. Despite the experimental design, we have to deal with selection problems stemming from nonrandom assignment and non-random panel attrition. Hence, we apply a difference-in-differences estimator taking account of the non-random nature of panel attrition. The results show that personal budgets could be cost efficient compared to agency services, but are likely to be cost inefficient compared to cash payments.
Sensor-Based Gait Parameter Extraction With Deep Convolutional Neural Networks

Measurement of stride-related, biomechanical parameters is the common rationale for objective gait impairment scoring. State-of-the-art double-integration approaches to extract these parameters from inertial sensor data are, however, limited in their clinical applicability due to the underlying assumptions. To overcome this, we present a method to translate the abstract information provided by wearable sensors to context-related expert features based on deep convolutional neural networks. Regarding mobile gait analysis, this enables integration-free and data-driven extraction of a set of eight spatio-temporal stride parameters. To this end, two modeling approaches are compared: a combined network estimating all parameters of interest and an ensemble approach that spawns less complex networks for each parameter individually. The ensemble approach is outperforming the combined modeling in the current application. On a clinically relevant and publicly available benchmark dataset, we estimate stride length, width and medio-lateral change in foot angle up to <inline-formula><tex-math notation="LaTeX">$\boldsymbol{-0.15\pm 6.09}$</tex-math> </inline-formula> cm, <inline-formula><tex-math notation="LaTeX">$\boldsymbol{-0.09\pm 4.22}$</tex-math> </inline-formula> cm and <inline-formula><tex-math notation="LaTeX">$\boldsymbol{0.13 \pm 3.78^\circ }$</tex-math> </inline-formula> respectively. Stride, swing and stance time as well as heel and toe contact times are estimated up to <inline-formula><tex-math notation="LaTeX">$\boldsymbol{\pm 0.07}$</tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$\boldsymbol{\pm 0.05}$</tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$\boldsymbol{\pm 0.07}$</tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$\boldsymbol{\pm 0.07}$</tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\boldsymbol{\pm 0.12}$</tex-math></inline-formula> s respectively. This is comparable to and in parts outperforming or defining state of the art. Our results further indicate that the proposed change in the methodology could substitute assumption-driven double-integration methods and enable mobile assessment of spatio-temporal stride parameters in clinically critical situations as, e.g., in the case of spastic gait impairments.
Towards a language-independent intelligibility assessment of children with cleft lip and palate

We describe a novel evaluation system for the intelligibility assessment of children with CLP on standardized tests. The system is solely based on standard cepstral features in form of MFCCs. No other information like word alignments is used. So the system can be easily adapted to other languages. For each child one GMM is created by adaptation of a UBM to the speaker-specific MFCCs. The components of this GMM are concatenated in order to create a so-called GMM supervector. These GMM supervectors are then used as meta features for an SVR. We evaluated our language-independent system on two different datasets of children suffering from CLP. One dataset contains recordings of 35 German children, where the children named different pictograms. The other dataset contains recordings of 14 Italian speaking children, who repeated standardized sentences. On both datasets we achieved high correlations: up to 0.81 for the German dataset and 0.83 for the Italian dataset.