Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of isoenergetic overfeeding of either carbohydrate or fat in young men

Ten pairs of normal men were overfed by 5 MJ/d for 21 d with either a carbohydrate-rich or a fat-rich diet (C- and F-group). The two subjects in each pair were requested to follow each other throughout the day to ensure similar physical activity and were otherwise allowed to maintain normal daily life. The increase in body weight, fat free mass and fat mass showed great variation, the mean increases being 1·5 kg, 0·6 kg and 0·9 kg respectively. No significant differences between the C- and F-group were observed. Heat production during sleep did not change during overfeeding. The RQ during sleep was 0·86 and 0·78 in the C- and F-group respectively. The accumulated faecal loss of energy, DM, carbohydrate and protein was significantly higher in the C- compared with the F-group (30, 44, 69 and 51 % higher respectively), whereas the fat loss was the same in the two groups. N balance was not different between the C- and F-group and was positive. Fractional contribution from hepatic de novo lipogenesis, as measured by mass isotopomer distribution analysis after administration of [1-13C]acetate, was 0·20 and 0·03 in the C-group and the F-group respectively. Absolute hepatic de novo lipogenesis in the C-group was on average 211 g per 21 d. Whole-body de novo lipogenesis, as obtained by the difference between fat mass increase and dietary fat available for storage, was positive in six of the ten subjects in the C-group (mean 332 (SEM 191) g per 21 d). The change in plasma leptin concentration was positively correlated with the change in fat mass. Thus, fat storage during overfeeding of isoenergetic amounts of diets rich in carbohydrate or in fat was not significantly different, and carbohydrates seemed to be converted to fat by both hepatic and extrahepatic lipogenesis.
Cascode MOSFET-MESFET RF power amplifier on 150nm SOI CMOS technology

Metal-semiconductor-field-effect-transistors (MESFETs) have been fabricated using a 150 nm partially depleted silicon-on-insulator CMOS technology. A peak fT of 40 GHz and peak breakdown voltages of up to 12V were measured. Comparatively, the CMOS transistors on the same process have a maximum steady-state voltage limit of 1.95V. TOM3 model for MESFET developed in ADS. The demonstrated high cut-off frequency and high voltage operation capability make the SOI MESFET a good device candidate for integrated radio frequency (RF) power amplifiers (PA). A cascoded MOS-MES RF PA architecture is proposed and simulated in ADS using the TOM3 model. Simulation results show 75% PAE while delivering 24dBm output power.
"What Do You Want to Do Next?" Providing the User with More Freedom in Adaptive Spoken Dialogue Systems

Spoken dialogue is a suitable form for user interaction in intelligent environments because of its low demands to presentation hardware (e.g. microphone and speaker set) and its low cognitive demand. That means that the user can still do something else while communicating with a spoken dialogue system (SDS). In this paper, we investigate the demands to modern SDSs in intelligent environments and how to provide the user with more freedom by using constraint programming techniques for dialogue management. For this we present an architecture which allows for adaptivity and freedom in SDSs.
MULTI-WAVELENGTH OBSERVATIONS OF THE RADIO MAGNETAR PSR J1622–4950 AND DISCOVERY OF ITS POSSIBLY ASSOCIATED SUPERNOVA REMNANT

We present multi-wavelength observations of the radio magnetar PSR J1622–4950 and its environment. Observations of PSR J1622–4950 with Chandra (in 2007 and 2009) and XMM (in 2011) show that the X-ray flux of PSR J1622–4950 has decreased by a factor of ∼50 over 3.7 years, decaying exponentially with a characteristic time of τ = 360 ± 11 days. This behavior identifies PSR J1622–4950 as a possible addition to the small class of transient magnetars. The X-ray decay likely indicates that PSR J1622–4950 is recovering from an X-ray outburst that occurred earlier in 2007, before the 2007 Chandra observations. Observations with the Australia Telescope Compact Array show strong radio variability, including a possible radio flaring event at least one and a half years after the 2007 X-ray outburst that may be a direct result of this X-ray event. Radio observations with the Molonglo Observatory Synthesis Telescope reveal that PSR J1622–4950 is 8′ southeast of a diffuse radio arc, G333.9+0.0, which appears non-thermal in nature and which could possibly be a previously undiscovered supernova remnant (SNR). If G333.9+0.0 is an SNR then the estimates of its size and age, combined with the close proximity and reasonable implied velocity of PSR J1622–4950, suggest that these two objects could be physically associated.
Cervical nodal necrosis is an independent survival predictor in nasopharyngeal carcinoma: an observational cohort study

Purpose Most nasopharyngeal carcinoma (NPC) patients present with locoregionally advanced disease at the time of diagnosis; however, there is a lack of consensus on specific prognostic factors potentially improving overall survival, especially in late-stage disease. Herein, we conducted a retrospective study to evaluate various potential prognostic factors in order to provide useful information for clinical treatment of T3/T4-stage NPC. Patients and methods A total of 189 previously untreated NPC patients were enrolled in the current study. All patients received intensity-modulated radiotherapy. Survival, death, relapse-free survival (both local and regional), and metastasis were recorded during follow-up. Factors affecting patient survival were assessed by using univariate and multivariate analyses. Results The median follow-up time was 69 months. The 5-year local-regional recurrence-free survival, distant metastasis-free survival, progression-free survival (PFS), and overall survival (OS) of the entire group were 89.8%, 71.5%, 66.3%, and 68.9%, respectively. Univariate analysis revealed significant differences in the 5-year PFS (58.5% vs 72.5%, P=0.015) and OS (59.5% vs 75.8%, P=0.033) rates of patients with and without cervical nodal necrosis (CNN). Subgroup analyses revealed that CNN was associated with poorer distant metastasis-free survival and PFS among patients with N2 stage (P=0.046 and P=0.005) and with poorer PFS among patients with T3 or III stage (all P=0.022). Multivariate analysis revealed CNN to be an independent prognostic factor for PFS and OS (PFS: adjusted hazard ratio, 1.860; 95% CI: 1.134–3.051; P=0.014; OS: adjusted hazard ratio, 1.754; 95% CI: 1.061–2.899; P=0.028). Conclusion CNN is a potential independent negative prognostic factor in NPC patients. Our results suggest that stratification of NPC patients based on their CNN status should be considered as part of NPC disease management.
Speech Summarization without Lexical Features for Mandarin Presentation Speech

We present the first known empirical study on speech summarization without lexical features for Mandarin presentation speeches. We evaluate acoustic, lexical and structural features as predictors of summary sentences. We find that the summarizer yields good performance at the average F-measure of 0.625 even by using the combination of acoustic and structural features alone, which are independent of lexical features. In addition, we show that our summarizer performs surprisingly well at the average F-measure of 0.513 by using only acoustic features. These findings enable us to summarize speech without placing a stringent demand on speech recognition accuracy.
Mental models: What do you mean by data science?

This research-in-progress investigates the diverse comprehension and definition of the Data Science. This field is rapidly growing in popularity around the world. There are numerous degree programs being rolled out at both the graduate and undergraduate levels. However, there is notable inconsistency in the approach to this highly regarded area of study. The individual components and the focus of data science have produced misconceptions in academia as well as in industry. As the build out approaches broad saturation, this seems like an ideal time to define what is considered Data Science. Mental models will be created from focus group interactions. Each session will represent participants from homogenous backgrounds (e.g. computer science or management information systems). We will compare the models, analyzing the variations and commonalities from the data. Results of this study will increase general understanding of data science. Implications for universities and industry practitioners will be discussed.
A PROVABLE SCHEME FOR HOMOMORPHIC OBFUSCATIONS IN SOFTWARE SECURITY

Computer and communication industries develop so rapidly that the demand for software becomes larger and larger and the demand for software protections, such as copyright and anti-tampering defense, are more and more important to software users and developers. There are some technical measures for software protections, such as hardware-based protections, network filters, cryptosystems, etc. Software obfuscation is one of these measures. It protects software from unauthorized modification by making software more obscure so that it is hard for the potential attacker to understand the obfuscated software. In software obfuscation, we can obfuscate the control flow and the data flow of the software. In this paper, we explore an obfuscation based on residue number coding, which is a method widely used in hardware design, high precision integer arithmetic, and cryptography [1]. Recently, it has used as an obfuscation that encoded variables in the original program to hide the true meaning of these variables [2]. There is some discussion about the division of residue numbers in [2], but the technique proposed there is incorrect. In this paper, we establish a provable residue number encoding for software obfuscation, especially a provable algorithm for division by several constants in residue numbers.
Fast learning algorithm for Gaussian models to analyze video objects with parameter size

Size of objects in scenes is an important parameter of video surveillance systems. From the analysis of object's size we can build an objects size model in scenes. The basic idea derives from automatic calibration to different perspectives. To build such a model of object's size from the real time video data we utilize Gaussians and real-time fast learning algorithm from literature. The built model is used for real-time surveillance systems.
QPOs in CVs: An executive summary

An overview is given of the properties of the various kinds of quasi‐periodic luminosity modulations observed in cataclysmic variables (CVs). The two principal types, known in the CV literature as dwarf nova oscillations and quasi‐periodic oscillations, have similarities to the high and low frequency quasi‐periodic oscillations in X‐Ray binaries. There is a further well observed class known as longer period dwarf nova oscillations. In CVs the observed interrelations between these oscillations suggests a model of magnetically controlled accretion onto a rapidly rotating equatorial belt of accreted gas. Non‐radial oscillations of the central white dwarf are observed in some systems.
TNF-α Receptor Signaling and IL-10 Gene Therapy Regulate the Innate and Humoral Immune Responses to Recombinant Adenovirus in the Lung1

Recombinant adenovirus-mediated gene therapy has demonstrated great promise for the delivery of genes to the pulmonary epithelium. However, dose-dependent inflammation and local immune responses abbreviate transgene expression. The purpose of these studies was to determine the role of TNF-α and individual TNF receptor signaling to adenovirus clearance and immune responses, and whether coexpression of human IL-10 could reduce inflammation and extend the duration of transgene expression in the lung. β-Galactosidase expression in mice receiving intratracheal instillation of Adv/β-gal (adenovirus construct expressing β-galactosidase) was transient (less than 14 days), but a significant early increase of β-galactosidase expression was seen in mice lacking either or both TNF-α receptors. Absence of TNF-α or the p55 receptor significantly attenuated the Ab response to both adenovirus and β-galactosidase. Human IL-10 expression in the lung suppressed local TNF-α production following AdV/hIL-10 (adenovirus construct expressing human IL-10) delivery, but did not lead to increased or prolonged transgene expression when coexpressed with β-galactosidase. Expression of human IL-10 following AdV/hIL-10 instillation extended at least 14 days, was nonimmunogenic, and suppressed the development of neutralizing Abs against adenoviral proteins as well as against human IL-10. We conclude that TNF-α signaling through both the p55 and p75 receptor plays important roles in the clearance of adenoviral vectors and the magnitude of the humoral immune response. Additionally, although coexpression of human IL-10 with β-galactosidase had only modest effects on transgene expression, we demonstrate that AdV/hIL-10 is well tolerated, has extended expression compared with β-galactosidase, and is nonimmunogenic in the lung.
Dissecting the Sociality of Emotion

In recent years, scholars have come to understand emotions as dynamic and socially constructed—the product of interdependent cultural, relational, situational, and biological influences. While researchers have called for a multilevel theory of emotion construction, any progress toward such a theory must overcome the fragmentation of relevant research across various disciplines and theoretical frameworks. We present affect control theory as a launching point for cross-disciplinary collaboration because of its empirically grounded conceptualization of social mechanisms operating at the interaction, relationship, and cultural levels, and its specification of processes linking social and individual aspects of emotion. After introducing the theory, we illustrate its correspondence with major theories of emotion construction framed at each of four analytical levels: cultural, interactional, individual, and neural.
MIDO space-time codes from associative and nonassociative cyclic algebras

Nonassociative division algebras have been recently proposed as an alternative way to design fully-diverse space-time codes. In particular, nonassociative cyclic algebras provide division algebras more easily than their associative counter-part. In this paper, we propose a few space-time code constructions coming from both associative and nonassociative cyclic algebras of degree 4, suitable for 4 transmit and 2 receive antennas, which furthermore exhibit good fast-decodability.
Global effects in Figure / Ground segregation by a model with only local interactions

Figure/Ground segregation is a fundamental problem in visual processing. Edges often arise because of occlusion, along the bounding contour of the occluding object. Having detected an edge, the visual system therefore has to decide whether it is there due to occlusion, and if so, which side of it belongs to the front surface (“the Figure”). This is known as the border ownership problem. Determining the border ownership of an edge cannot be done locally: it requires integrating information from an image region which contains the entire Figure or large portions of it. Thus, a neuron whose receptive field is small compared to the Figure cannot compute border ownership of an edge of that Figure in isolation. Recently it was reported that the responses of V2 cells to an edge can be strongly modulated by the polarity of border ownership of the edge (Zhou et al.2000). These effects must therefore be the product of computations done by a network of neurons. One possibility is that such networks rely on direct long-range connections (of the scale of the Figure) and/or feedback from areas with cells of large receptive fields. The model presented here offers an alternative. It is shown that network of small receptive field cells which interact only locally can nevertheless compute Figure/Ground segregation. The long-range effects emerge as a result of iterative propagation of information through a cascade of short-range connections. The model produces results similar to those observed perceptually: it prefers enclosed, convex and/or smaller regions as the Figure. Our results suggest that considerable portions of Figure/Ground segregation can be accomplished by early visual cortex, without a need for feedback from higher areas.
Nonparametric elicitation for heavy-tailed prior distributions

In the context of statistical analysis, elicitation is the process of translating someone’s beliefs about some uncertain quantities into a probability distribution. The person’s judgements about the quantities are usually fitted to some member of a convenient parametric family. This approach does not allow for the possibility that any number of distributions could fit the same judgements. In this paper, elicitation of an expert’s beliefs is treated as any other inference problem: the facilitator of the elicitation exercise has prior beliefs about the form of the expert’s density function, the facilitator elicits judgements about the density function, and the facilitator’s beliefs about the expert’s density function are updated in the light of these judgements. This paper investigates prior beliefs about an expert’s density function and shows how many different types of judgement can be handled by this method. This elicitation method begins with the belief that the expert’s density will roughly have the shape of a t density. This belief is then updated through a Gaussian process model using judgements from the expert. The method gives a framework for quantifying the facilitator’s uncertainty about a density given judgements about the mean and percentiles of the expert’s distribution. A property of Gaussian processes can be manipulated to include judgements about the derivatives of the density, which allows the facilitator to incorporate mode judgements and judgements on the sign of the density at any given point. The benefit of including the second type of judgement is that substantial computational time can be saved.
MicroRNA-21 Increases Proliferation and Cisplatin Sensitivity of Osteosarcoma-Derived Cells

Osteosarcoma is the most common primary bone tumor and poor prognosis for osteosarcoma patients is mainly due to chemotherapy resistance. MicroRNAs are important to maintain pathophysiological mechanisms of cancer and influence cell sensitivity to chemotherapy. In this study, we tested the functions of microRNA-21 for malignant features as well as for drug resistance of osteosarcoma. We used Northern blot to measure microRNA-21 levels in osteosarcoma-derived cell lines. MicroRNA-21 activity was modulated by either expressing a sponge to decrease its activity in an osteosarcoma-derived cell line expressing high levels of microRNA-21 or by introducing pri-microRNA-21 in a cell line with low endogenous levels. Cell migration was determined in a scratch assay and cell proliferation was measured by performing growth curve analysis. Sensitivity of the cells towards chemotherapeutics was investigated by performing cell viability assays and calculating the IC50 values. While cell migration was unaffected by modulated microRNA-21 levels, microRNA-21 inhibition slowed proliferation and exogenously expressed microRNA-21 promoted this process. Modulated microRNA-21 activity failed to effect sensitivity of osteosarcoma-derived cell lines to doxorubicin or methotrexate. Contrarily, reduction of microRNA-21 activity resulted in enhanced resistance towards cisplatin while ectopic expression of microRNA-21 showed the opposite effect. Increased microRNA-21 levels repressed the expression of Sprouty2 and ectopic expression of Sprouty2 was able to largely rescue the observed effects of microRNA-21 in osteosarcoma. In summary, our data indicate that in osteosarcoma microRNA-21 expression is an important component for regulation of cell proliferation and for determining sensitivity to cisplatin.
A new hybrid schema-sharing technique for multitenant applications

This paper presents a new schema-sharing technique for multitenant applications. Our approach is built on top of the Extension table method and makes use of the native XML data support to store the additional data supplied by each tenant. Our proposed technique can be used to implement multitenancy on top of a standard relational database. This paper also describes an implementation of our approach using a real-world case study aiming at improving the communication channel of information related to drinking water quality parameters used by all stakeholders involved in the water treatment process in Ireland. These include the Environmental Protection Agency, the Health Service Executive, drinking water treatment plant staff, local authorities and everybody consuming water.
Fuzzy-Set Based Sentiment Analysis of Big Social Data

Computational approaches to social media analytics are largely limited to graph theoretical approaches such as social network analysis (SNA) informed by the social philosophical approach of relational sociology. There are no other unified modelling approaches to social data that integrate the conceptual, formal, software, analytical and empirical realms. In this paper, we first present and discuss a theory and conceptual model of social data. Second, we outline a formal model based on fuzzy set theory and describe the operational semantics of the formal model with a real-world social data example from Facebook. Third, we briefly present and discuss the Social Data Analytics Tool (SODATO) that realizes the conceptual model in software and provisions social data analysis based on the conceptual and formal models. Fourth, we use SODATO to fetch social data from the Facebook wall of a global brand, H&M and conduct a sentiment classification of the posts and comments. Fifth, we analyse the sentiment classifications by constructing crisp as well as the fuzzy sets of the artefacts (posts, comments, likes, and shares). We document and discuss the longitudinal sentiment profiles of artefacts and actors on the facebook page. Sixth and last, we discuss the analytical method and conclude with a discussion of the benefits of set theoretical approaches based on the social philosophical approach of associational sociology.
RELIEF Algorithm and Similarity Learning for k-NN

: In this paper, we study the links between RELIEF , a well-known feature re-weighting algorithm and SiLA , a similarity learning algorithm. On one hand, SiLA is interested in directly reducing the leave-one-out error or 0 − 1 loss by reducing the number of mistakes on unseen examples. On the other hand, it has been shown that RELIEF could be seen as a distance learning algorithm in which a linear utility function with maximum margin was optimized. We ﬁrst propose here a version of this algorithm for similarity learning, called RBS (for RELIEF - Based Similarity learning). As RELIEF , and unlike SiLA , RBS does not try to optimize the leave-one-out error or 0 − 1 loss, and does not perform very well in practice, as we illustrate on several UCI collections. We thus introduce a stricter version of RBS , called sRBS , aiming at relying on a cost function closer to the 0 − 1 loss. Moreover, we also developed Positive, semi-deﬁnite (PSD) versions of RBS and sRBS algorithms, where the learned similarity matrix is projected onto the set of PSD matrices. Experiments conducted on several datasets illustrate the different behaviors of these algorithms for learning similarities for kNN classiﬁcation. The results indicate in particular that the 0 − 1 loss is a more appropriate cost function than the one implicitly used by RELIEF . Furthermore, the projection onto the set of PSD matrices improves the results for RELIEF algorithm only.