Miracle-dz/UniFAR-FTUs huggingface dataset:
Pluripotent Human Stem Cells A Novel Tool in Drug Discovery

The need for new and improved pharmacotherapies in medicine, high late-stage compound attrition in drug discovery, and upcoming patent expirations is driving interest by the pharmaceutical industry in pluripotent stem cells for in vitro modeling and early-stage testing of toxicity and target engagement. In particular, human embryonic and induced pluripotent stem cells represent potentially cost-effective and accessible sources of organ-specific cells that foretell in vivo human tissue response to new chemical entities. Here we consider the potential of these cells as novel tools for drug development, including toxicity screening and metabolic profiling. We hold that despite various challenges to translating proof-of-concept screening platforms to industrial use, the promise of research is considerable, and close to being realized.
Synergistic anticancer effect of Grb2 and ITGA1 on cancer cells highly expressing Grb2 through suppressing ERK phosphorylation.

BACKGROUND Growth factor receptor bound protein 2 (Grb2) is known to be an adaptor protein that provides a critical link between cell surface growth factor receptors and the MAPK signaling. It was shown that high expression of Grb2 enhances cancer cells proliferation, invasion and malignant transformation. OBJECTIVE In this study, we aimed to systemically understand the function of Grb2 in cancer. METHODS The expression of Grb2 in different cancer cell lines was examined from a publicly available database and we chose two cancer cell lines highly expressing Grb2 to investigate the role of Grb2. To systemically understand the function of Grb2 in cancer cells, proteomic profiles also were analyzed. RESULT The results suggested that downregulation of Grb2 reduced cell proliferation in Hela cells and Jurkat cells. In addition, knockdown of Grb2 reduced the expression of ITGA1 and inhibited the phosphorylation of ERK. Intriguingly, simultaneous inhibition of Grb2 and ITGA1 resulted in a greater inhibition of phosphorylated ERK than either inhibition of Grb2 or ITGA1, and thus triggered marked apoptosis in Hela cells and Jurkat cells. These results suggest a synergistic anticancer effect of Grb2 and ITGA1 mediated by the ERK pathway in cancer cells highly expressing Grb2. In conclusion, we provided evidence that inhibition of Grb2 and ITGA1 might be an attractive target for therapeutic intervention against the cancer growth of cancers with high Grb2 expression.
Audiovisual production and perception of contrastive focus in French: a multispeaker study

This study examines the visual cues to prosodic contrastive focus in Hexagonal French and their role in visual speech perception. Two audiovisual corpora were recorded (from two male native speakers of French) consisting of sentences with a subject-verb-object (SVO) syntactic structure. Four conditions were studied: focus on each phrase (S,V,O) and broad focus. The corpora were first acoustically validated. Then lip area and jaw opening were extracted from the video. For each speaker, we identified a set of visible correlates of contrastive focus. The combined results showed that there were consistent visible articulatory correlates of contrastive focus across speakers: a) an increase in lip area and its first derivative on the focused item b) a lengthening of the focal syllables. There were also speaker-specific strategies in the amount of a) prefocal anticipation or b) post-focal hypo-articulation. Visual only perception tests were then conducted to see if the identified correlates were valid cues in perception. They showed that contrastive focus was well perceived visually for both speakers. The scores were better for the first speaker who displayed greater focal hyper-articulation. We also found that presence and salience of the visual cues enhances perception.
Some Mathematics of Network Analysis

= 0Each partition determines an equivalence relation (and vice versa). Let us denote by˘ the relation determined by partition C. A block model consists of structures obtainedby identifying all units from the same cluster of the clustering C. The partition (ideally)is constructed by using structural information contained in R and actors in the samepartitioned class are equivalent to each other in terms of R alone. Such actors sharea common structural position within the network. (In general the statement can beextended to include fR
OpenCache: A software-defined content caching platform

Network operators recognise that Content Delivery Networks are essential for meeting user Internet application and content demands. The infrastructure must be tightly integrated to provide request routing, content caching, load balancing, scalability and reliability, whilst minimising deployment time and complexity. A major step towards achieving these goals is to embrace recent Software Defined Network and Network Function Virtualisation objectives and design principles. This paper outlines the OpenCache API; an interface used to define the behaviour and operation of an SDN-based content delivery platform in real-time. We demonstrate the applicability and effectiveness of such an API by implementing load-balancing and fail-over functionalities as part of an experimental deployment.
A range-based navigation system for autonomous underwater vehicles

Single-beacon range-based navigation systems for underwater vehicles rely on a vehicle’s motion to obtain range measurements at different locations in order to estimate its position. This motivates the study of optimal trajectories for improving the accuracy of the position estimate while respecting mission related criteria. The performance index used to compare different trajectories is the determinant of a properly defined Fisher Information Matrix (FIM). Assuming that heading measurements are available, the problem is studied for 2D and 3D, including the case when depth measurements can be obtained. Analytical and numerical solutions are derived. Examples of optimal or close-to-optimal trajectories obtained are (i) circumferences around the beacon for 2D, (ii) cylindrical helices for 3D and (iii) a circumference around the beacon, in the same horizontal plane, for 3D including depth measurements. Additionally for 2D, the case of two vehicles using the same beacon and exchanging range information is studied, for which concentric trajectories that circumnavigate the beacon are shown to be optimal. An approach to deal with the case where the initial position of the vehicle is known to lie in a region of uncertainty is presented. A navigation algorithm consisting of an optimal trajectory planner and a minimum-energy estimator is proposed and tested in the simulation of a practical scientific scenario.
Self-Stabilizing Failure Detector Algorithms

This paper revisits the interconnection of self-stabilization and fault-tolerance. Self-stabilizing algorithms are able to recover from arbitrary system states given that from some point in time on, there are no faults. Fault-tolerance, on the other hand, refers to algorithms that cope with systems where a (bounded) part of the system (e.g. at most f out of n processes) may fail permanently. In previous work [16] we considered the interconnection of these two paradigms, i.e., algorithms that recover from arbitrary states despite of permanent faults. We have shown that in certain settings, problems as failure detection cannot be solved. This paper presents ways to circumvent this impossibility result.
LYRICS-TO-AUDIO ALIGNMENT AND PHRASE-LEVEL SEGMENTATION USING INCOMPLETE INTERNET-STYLE CHORD ANNOTATIONS

We propose two novel lyrics-to-audio alignment methods which make use of additional chord information. In the ﬁrst method we extend an existing hidden Markov model (HMM) for lyrics alignment [1] by adding a chord model based on the chroma features often used in automatic audio chord detection. However, the textual transcriptions found on the Internet usually provide chords only for the ﬁrst among all verses (or choruses, etc.). The second method we propose is therefore designed to work on these incomplete transcriptions by ﬁnding a phrase-level segmentation of the song using the partial chord information available. This segmentation is then used to constrain the lyrics alignment. Both methods are tested against hand-labelled ground truth annotations of word beginnings. We use our ﬁrst method to show that chords and lyrics complement each other, boosting accuracy from 59.1% (only chroma feature) and 46.0% (only phoneme feature) to 88.0% (0.51 seconds mean absolute displacement). Alignment performance decreases with incomplete chord annotations, but we show that our second method compensates for this information loss and achieves an accuracy of 72.7%.
Exploring Spatial Growth Pattern of Settlements in Customary Land – A study of Adams Rural , KwaZulu-Natal .

For centuries migration has been known to be a trend where people move from an area with poor resources to that which promises better life. In modern day the pattern is that of people moving from rural to urban areas. There is an unusual trend unfolding in Adams Rural, a rural area south of Durban in South Africa, where the migration norms appear to have been reversed. People have been moving from urban areas to this rural area. This trend is observable as an increase in human settlements over the past decade and is confirmed by annual aerial imagery of the area captured by the eThekwini Municipality. The increasing demand for settlements has placed pressure on customary stakeholders to provide more land for residential purpose’s resulting in loss of land previously reserved for agriculture predominantly in the form of sugarcane plantation. This research employs Geographic Information System (GIS) technology and change detection performed on selected orthophoto imagery to assess spatial change patterns, and to quantify the amount and rate of change in human settlements of Adams Rural during the period 2001 to 2012. The results show that spatial coverage of human settlements has more than doubled with commensurate loss in agricultural land. Demographic data for 2001 and 2011 obtained from statistics South Africa (Statistics SA) also confirms that the population of the area has more than doubled over the same period. The rate of increase in settlements varied between periods considered with the population increasing proportionately.
Afadin Regulates Puncta Adherentia Junction Formation and Presynaptic Differentiation in Hippocampal Neurons

The formation and remodeling of mossy fiber-CA3 pyramidal cell synapses in the stratum lucidum of the hippocampus are implicated in the cellular basis of learning and memory. Afadin and its binding cell adhesion molecules, nectin-1 and nectin-3, together with N-cadherin, are concentrated at puncta adherentia junctions (PAJs) in these synapses. Here, we investigated the roles of afadin in PAJ formation and presynaptic differentiation in mossy fiber-CA3 pyramidal cell synapses. At these synapses in the mice in which the afadin gene was conditionally inactivated before synaptogenesis by using nestin-Cre mice, the immunofluorescence signals for the PAJ components, nectin-1, nectin-3 and N-cadherin, disappeared almost completely, while those for the presynaptic components, VGLUT1 and bassoon, were markedly decreased. In addition, these signals were significantly decreased in cultured afadin-deficient hippocampal neurons. Furthermore, the interevent interval of miniature excitatory postsynaptic currents was prolonged in the cultured afadin-deficient hippocampal neurons compared with control neurons, indicating that presynaptic functions were suppressed or a number of synapse was reduced in the afadin-deficient neurons. Analyses of presynaptic vesicle recycling and paired recordings revealed that the cultured afadin-deficient neurons showed impaired presynaptic functions. These results indicate that afadin regulates both PAJ formation and presynaptic differentiation in most mossy fiber-CA3 pyramidal cell synapses, while in a considerable population of these neurons, afadin regulates only PAJ formation but not presynaptic differentiation.
The EFS-Server: A Web-Application for Feature Selection in Binary Classification

Feature selection methods are essential to identify a subset of features that improve the prediction performance of subsequent classification models and thereby also simplify their interpretability. Preceding studies showed the defectiveness in terms of specific biases of single feature selection methods, whereas an ensemble of feature selection techniques has the advantage to alleviate and compensate for such biases. With the development of the ensemble feature selection (EFS) method we take advantage of the benefits of multiple feature selection methods and combine their normalized outputs to a quantitative ensemble importance. Eight different feature selection methods have been used for the EFS approach. We evaluated the EFS method on a testset and it turned out that the subset of features retrieved by the EFS method showed a significantly improved performance in a subsequent logistic regression (LR) model compared to a model using all available features. EFS can be downloaded as an R-package or used in a websever at http://EFS.heiderlab. de.
Neural-network compensation methods for capacitive micromachined accelerometers for use in telecare medicine

Transducers represent a key component of medical instrumentation systems. In this paper, sensors that perform the task of measuring the physical quantity of acceleration are discussed. These sensors are of special significance since, by integrating their output signals, accelerometers can additionally provide measures of velocity and position. Applications for such measurements, and thus of accelerometers, range from early diagnosis procedures for tremor-related diseases (e.g. Parkinson's disease) to monitoring daily patterns of patient activity using telemetry systems. The system-level requirements in such applications are considered, and two novel neural-network transducer designs developed by the authors are presented, which aim to satisfy such requirements. Both designs are based on a micromachined sensing element with capacitive signal pickoff. The first is an open-loop design utilizing a direct-inverse control strategy, while the second is a closed-loop design, where electrostatic actuation is used as a form of feedback. Both transducers are nonlinearly compensated, capable of self-testing, and provide digital outputs.
Identifying and Mitigating Cyber Attacks that could cause Physical Damage to Industrial Control Systems

Physical control systems are increasingly controlled by reconfigurable, network-enabled devices to increase flexibility and ease commissioning and maintenance. Such capability creates vulnerabilities. Devices may be remotely reprogrammed by a malicious actor to act in unintended ways, causing physical damage to mechanical equipment, infrastructure, and life and limb. In this paper, past examples of actual damage to cyberphysical systems are shown, threats posed by software-controlled Variable Frequency Drives (VFDs) are analyzed, and a small-scale version of an attack on ubiquitous VFD equipment is demonstrated.
Tracking and representing others’ mental states

Few things matter more than the mental states of those nearby. Their ignorance defines limits on cooperation and presents opportunities to exploit in competition. (If she’s seen where you stashed those mealworms she’ll pilfer them when you’re gone, leaving you without breakfast. And you won’t get that grape if he hears you sneaking past.) What others feel, see and know can also provide information about events otherwise beyond your ken. It’s no surprise, then, that abilities to track others’ mental states are widespread. Many animals, including scrub jays (Clayton, Dally and Emery 2007), ravens (Bugnyar, Reber and Buckner 2016), goats (Kaminski, Call and Tomasello 2006), dogs (Kaminski et al. 2009), ring-tailed lemurs (Sandel, MacLean and Hare 2011), monkeys (Hattori, Kuroshima and Fujita 2009) and chimpanzees (Karg et al. 2015), reliably vary their actions in ways that are appropriate given facts about another’s mental states. What underpins such abilities to track others’ mental states?
Towards innovative environmental management in the agro-food industry

This article focuses on the problem: what external (stakeholder) and internal (structural/organizational) factors drive companies in the food- and agribusiness towards innovative environmental management? Innovative companies are those considered to have adopted a supply-chain perspective, instead of a focus on the single business unit. We propose that innovativeness is associated with stakeholder wishes (the government, the public environmental policy being a major influential factor), in combination with structural characteristics of the firm (like R&D-efforts, culture and managerial competences). We surveyed 492 companies in 2002, to get insight into the causes of innovativeness in the Dutch agri-food sector, and supplemented this data by means of a similar questionnaire in 2005. Structural equation modeling and correlation analysis were applied. The research provided evidence that companies are restricted by, and therefore not comfortable with, public environmental policies, which seem to obstruct innovativeness rather than stimulate it. Firms that (1) have enough internal (physical, financial, social) resources to innovate, and (2) are more embedded in a web of (commercial) stakeholder wishes, prove to be more innovative. Suggestions are made to shift the corporate and public policies towards a supply chain-oriented approach by granting benefits for vertical cooperation in supply-chains.
Sparse-TFM Imaging of Lamb Waves for the Near-Distance Defects in Plate-Like Structures

The ultrasonic phased array total focusing method (TFM) has the advantages of high imaging resolution and high sensitivity to small defects. However, it has a long imaging time and cannot realize near-distance defect imaging, which limits its application for industrial detection. A sparse-TFM algorithm is adopted in this work to solve the problem regarding rapid imaging of near- distance defects in thin plates. Green’s function is reconstructed through the cross-correlation of the diffuse full matrix captured by the ultrasonic phased array. The reconstructed full matrix recovers near-distance scattering information submerged by noise. A sparse array is applied to TFM for rapid imaging. In order to improve the imaging resolution, the location of active array elements in the sparse array can be optimized using the genetic algorithm (GA). Experiments are conducted on three aluminium plates with near-distance defects. The experimental results confirm that the sparse-TFM algorithm of Lamb waves can be used for near-distance defects imaging, which increases the computational efficiency by keeping the imaging accuracy. This paper provides a theoretical guidance for Lamb wave non-destructive testing of the near-distance defects in plate-like structures.
Stacking integration methodologies in 3D IC for 3D ultrasound image processing application: A stochastic flash ADC design case study

In three-dimensional integrated circuit (3D IC) systems that use through-silicon via (TSV) technology, a significant design consideration is the coupling noise to/from TSVs. In Analog/Mixed signal ICs, the TSV coupling effect can cause coupling noise disturbance and degrades the performance of sensitive analog devices. In this paper, two different stacking integrations for the sensor array and the 3D IC, are considered and compared. In the face-up stacking integration, the transducers' flip chip bonded pads are directly bonded to the integrated circuit. In facedown integration type, however, the connections from the sensor output signal to the front end electronics is done via the TSVs. The TSV coupling noise is compared for the two schemes using the existing TSV coupling noise model. To validate the impact of stacking integration on the coupling noise, an ADC case study was designed and implemented using 130nm device technology and Tezzaron TSV technology. The simulations results show that the face-up integration could suppress the coupling noise by 10db. Moreover, a 23% reduction in footprint is achieved in this stacking integration.
Leveraging machine learning and information retrieval techniques in software evolution tasks: summary of the first MALIR-SE workshop, at ASE 2013

The first International Workshop on MAchine Learning and Information Retrieval for Software Evolution (MALIR-SE) was held on the 11th of November 2013. The workshop was held in conjunction with the 28th IEEE/ACM International Conference on Automated Software Engineering (ASE) in Silicon Valley, California, USA. The workshop brought researchers and practitioners that were interested in leveraging machine learning and information retrieval techniques to automate various software evolution tasks. During the workshop, papers on the application of machine learning and information retrieval techniques to bug fix time prediction and anti-pattern detection were presented. There were also discussions on the presented papers and on future direction of research in the area.
Dynamics of a Self-interacting Scalar Field Trapped in the Braneworld for a Wide Variety of Self-interaction Potentials

We apply the dynamical systems tools to study the linear dynamics of a self-interacting scalar field trapped in the braneworld, for a wide variety of self-interaction potentials. We focus on Randall-Sundrum and on Dvali-Gabadadze-Porrati braneworld models exclusively. These models are complementary to each other: while the Randall-Sundrum brane produces UV) corrections to general relativity, the Dvali-Gabadadze-Porrati braneworld modifies Einstein's theory at large scales, i e. , produces IR modifications of general relativity. This study of the asymptotic properties of both braneworld models, shows - in the phase space - the way the dynamics of a scalar field trapped in the brane departs from standard general relativity behavior.