Miracle-dz/UniFAR-FTUs huggingface dataset:
Chapter # IMPROVING THE SOFTWARE PROCESS WITH USABILITY ASPECTS

Software development organizations are paying more and more attention to the usability of their software products, due to the increasing importance attached to usability as a critical software quality attribute. The HCI (Human-Computer Interaction) field offers techniques aimed at producing a software product with the desired usability level, but their use is often not integrated into SE (software engineering) development processes. The integration of HCI techniques into SE practice is not an easy endeavor, since both fields speak different languages and they deal with software development from different perspectives. This chapter presents a characterization of selected HCI techniques and activities using SE terminology and concepts, according to what kind of activity they belong to and at what development stage their application contributes to a greater extent to the usability of the final software product. Software developers may then manage usability activities and techniques, include them in their schedule, and understand in which activities usability techniques have to be coordinated with SE techniques. The proposed characterization is aimed at software development organizations with a mature development process that are looking to enhance their process with usability aspects. The only requirement for the current software development process applied at the organization is that it be iterative, since this is a key characteristic for any effort directed at raising the usability level of the final software product.
Implications of trajectory generation strategies for tubular continuum robots

Tubular continuum robots are particularly useful for minimally invasive surgery due to their small size and ability to dexterously manipulate in constrained environments. The robot can be used teleoperated or operated (semi-)autonomously. In both cases, safe manipulation has to be ensured considering constraints from the patient's unique anatomy and pathology to prevent injury of nerves, vessels, and soft tissue. While probabilistic path planning methods have been proposed for tubular continuum robots which generate sequences of collision free configurations in obstructed environments, these methods do usually not explicitly consider different trajectory generations. In this paper, we evaluate four trajectory generation strategies in terms of the resulting Cartesian paths and spatial extent of the course of motion. We demonstrate the implication of the different strategies on both collision free path planning and an example medical scenario. In conclusion, consideration of trajectory generation strategies is indispensable, if the distance between intermediate configurations increases - even though those intermediate configurations might be collision free.
Comparing the Clinical and Histological Diagnosis of Leprosy and Leprosy Reactions in the INFIR Cohort of Indian Patients with Multibacillary Leprosy

Background The ILEP Nerve Function Impairment in Reaction (INFIR) is a cohort study designed to identify predictors of reactions and nerve function impairment in leprosy. The aim was to study correlations between clinical and histological diagnosis of reactions. Methodology/Principal Findings Three hundred and three newly diagnosed patients with World Health Organization multibacillary (MB) leprosy from two centres in India were enrolled in the study. Skin biopsies taken at enrolment were assessed using a standardised proforma to collect data on the histological diagnosis of leprosy, leprosy reactions and the certainty level of the diagnosis. The pathologist diagnosed definite or probable Type 1 Reactions (T1R) in 113 of 265 biopsies from patients at risk of developing reactions whereas clinicians diagnosed skin only reactions in 39 patients and 19 with skin and nerve involvement. Patients with Borderline Tuberculoid (BT) leprosy had a clinical diagnosis rate of reactions of 43% and a histological diagnosis rate of 61%; for patients with Borderline Lepromatous (BL) leprosy the clinical and histological diagnosis rates were 53.7% and 46.2% respectively. The sensitivity and specificity of clinical diagnosis for T1R was 53.1% and 61.9% for BT patients and 61.1% and 71.0% for BL patients. Erythema Nodosum Leprosum (ENL) was diagnosed clinically in two patients but histologically in 13 patients. The Ridley-Jopling classification of patients (n = 303) was 42.8% BT, 27.4% BL, 9.4% Lepromatous Leprosy (LL), 13.0% Indeterminate and 7.4% with non-specific inflammation. This data shows that MB classification is very heterogeneous and encompasses patients with no detectable bacteria and high immunological activity through to patients with high bacterial loads. Conclusions/Significance Leprosy reactions may be under-diagnosed by clinicians and increasing biopsy rates would help in the diagnosis of reactions. Future studies should look at sub-clinical T1R and ENL and whether they have impact on clinical outcomes.
A systematic search for very massive galaxies at z > 4

Motivated by the claimed discovery of a very massive galaxy (HUDF-JD2; M≃ 5 × 1011 M⊙) at extreme redshift (z= 6.5) within the Hubble Ultra Deep Field (HUDF), we have completed a systematic search for comparably massive galaxies with z > 4 among the 2688 galaxies in our KS < 23.5 (AB) catalogue within the CDFS/GOODS-South field. This search was conducted using redshift estimates based on the recently completed, uniquely-deep 11-band (B, V, i, z, J, H, KS, 3.6 μ m, 4.5 μm, 5.8 μm, 8.0 μm) imaging in this 125-arcmin2 field, ≃ 25 times larger than the NICMOS HUDF. To ensure completeness, our approach places no special emphasis on the standard V-drop, i-drop or z-drop criteria commonly used to pre-select candidate high-redshift galaxies. Initial spectral fitting, based on published catalogue SExtractor photometry, led us to conclude that at least 2669 of the galaxies in our sample lie at z 4 have been previously proposed. We carried out a detailed investigation of the 19 remaining z > 4 candidates, performing aperture photometry on all images, and including marginal detections and formal non-detections in the fitting process. This led to the rejection of a further 13 galaxies to lower redshift. Moreover, subjecting HUDF-JD2 to the same analysis, we find that it almost certainly lies at 2 < z < 3, rather than the extreme redshift favoured by Mobasher et al. The six remaining candidates appear to be credible examples of galaxies in the redshift range z= 4–6, with plausible stellar ages. However, refitting with allowance for extreme values of extinction, we find that, even for these objects, statistically acceptable solutions can be found at z 4 candidates are detected at 24 μm. This was also the case for HUDF-JD2, and provides further circumstantial evidence in favour of the moderate-redshift dusty solutions. We conclude that there is no convincing evidence for any galaxy with M > 3 × 1011 M⊙ and z > 4 within the 125-arcmin2 GOODS-South field. We briefly discuss the implications of this null result, and revised expectations for the much larger (0.8 deg2), and deeper near-infrared UKIDSS Ultra Deep Survey now underway with the WFCAM on the UKIRT.
Atomic carbon at redshift ~2.5

Using the IRAM 30 m telescope we detected the lower fine structure line of neutral carbon (C I$(\rm ^3\! P_1\to{}^3\! P_0)$, $\nu_{\rm rest} = 492$ GHz) towards three high–redshift sources: IRAS FSC 10214 ($z=2.3$), SMM J14011+0252 ($z=2.5$) and H1413+117 (Cloverleaf quasar, $z=2.5$). SMM J14011+0252 is the first high–redshift, non–AGN source in which C I has been detected. The C I$(\rm ^3\! P_1\to{}^3\! P_0)$ line from FSC 10214 is almost an order of magnitude weaker than previously claimed, while our detection in the Cloverleaf is in good agreement with earlier observations. The C I$(\rm ^3\! P_1\to{}^3\! P_0)$ linewidths are similar to the CO widths, indicating that both lines trace similar regions of molecular gas on galactic scales. Derived C I$(\rm ^3\! P_1\to{}^3\! P_0)$ masses for all three objects are of order few $\times10^7$ $M_{\odot}$ and the implied C I$(\rm ^3\! P_1\to{}^3\! P_0)$/ 12 CO($J=3\to2$) line luminosity ratio is about 0.2. This number is similar to values found in local galaxies. We derive a C I abundance of $5\times10^{-5}$ which implies significant metal enrichment of the cold molecular gas at redshifts 2.5 (age of the universe 2.7 Gyr). We conclude that the physical properties of systems at large lookback times are similar to today's starburst/AGN environments.
Magnetic Cursor: Improving Target Selection in Freehand Pointing Interfaces

We present the magnetic cursor, a technique that aims to make distant freehand interaction with targets easier in large-screen public display applications. The magnetic cursor automatically warps to a selectable object that is close by, moves slower while on the object, and shows the relative cursor location visually to the user. Two designs of the magnetic cursor were compared to the snap-to-target technique in a 19 participant user study. Results indicate that the magnetic cursor design with weaker magnetism effect outperforms the other techniques in terms of target selection efficiency. Subjective feedback indicates that snap-to-target and the magnetic cursor design with weaker magnetism effect meet the participants' expectations for freehand pointing and are preferred to unassisted pointing and the magnetic cursor with stronger magnetism. Our findings suggest that the visual feedback of cursor location and short, static activation threshold for the magnetism effect can help users maintain the cursor within the active motor space of a target, especially when several selectable targets are situated in close proximity.
Effect on Soil Properties of BcWRKY1 Transgenic Maize with Enhanced Salinity Tolerance

Maize (Zea mays L.) is the most important cereal crop in the world. However, soil salinity has become a major problem affecting plant productivity due to arable field degradation. Thus, transgenic maize transformed with a salinity tolerance gene has been developed to further evaluate its salt tolerance and effects on agronomic traits. It is necessary to analyze the potential environmental risk of transgenic maize before further commercialization. Enzyme activities, physicochemical properties, and microbial populations were evaluated in saline and nonsaline rhizosphere soils from a transgenic maize line (WL-73) overexpressing BcWRKY1 and from wild-type (WT) maize LH1037. Measurements were taken at four growth stages (V3, V9, R1, and R6) and repeated in three consecutive years (2012–2014). There was no change in the rhizosphere soils of either WL-73 or WT plants in the four soil enzyme activities, seven soil physicochemical properties, and the populations of three soil organisms. The results of this study suggested that salinity tolerant transgenic maize had no adverse impact on soil properties in soil rhizosphere during three consecutive years at two different locations and provided a theoretical basis for environmental impact monitoring of salinity tolerant transgenic maize.
Comparing You = Comparing Me

We examine whether individuals respond to comparisons involving romantic partners as they would to comparisons involving the self. Four studies (N = 2,210) using recalled (Studies 1-3) and actual (Study 4) comparisons about attractiveness (Study 1) and relationship skills (Studies 2-4) demonstrated that individuals high in self-other overlap decrease domain relevance following upward but not downward comparisons to protect their positive partner perceptions. This strategy was absent among those low in self-other overlap. Study 2 demonstrated that this effect extends to best friends, but not casual friends, due to the degree of self-other overlap. Furthermore, when reminded of their partner’s inferiority in a domain, high overlap participants maintained positive global partner perceptions, whereas low overlap participants’ global perceptions were negatively affected (Study 3). These results suggest that individuals do experience partner-other comparisons as if they were directly involved, but only if their partner is incorporated into their self-identity.
EVALUATION OF REMOTE SENSING IMAGE SEGMENTATION QUALITY – FURTHER RESULTS AND CONCEPTS

Primarily due to the progresses in spatial resolution of satellite imagery, the methods of segment-based image analysis for generating and updating geographical information are becoming more and more important. In the studies of Neubert and Meinel (2003) and Meinel and Neubert (2004) the capabilities of available segmentation programmes for high resolution remote sensing data were assessed and compared. This paper intends to supplement the preceding studies by considering recently available software. Moreover, a self-implemented optimised segmentation algorithm for the image processing software HALCON is included in the test. The achieved segmentation quality of each programme is evaluated on the basis of an empirical discrepancy method using pansharpened multi-spectral IKONOS data. Furthermore, an overview of further methods for quantitative image segmentation quality evaluation is given. Finally, the qualitative and quantitative outcomes are compared and contrasted to the previously tested software solutions. The stated results provide an approach to determine each programme’s performance and appropriateness for specific segmentation tasks. * Corresponding author.
Instant message classification in Finnish cyber security themed free-form discussion

Instant messaging enables rapid collaboration between professionals during cyber security incidents. However, monitoring discussion manually becomes challenging as the number of communication channels increases. Failure to identify relevant information from the free-form instant messages may lead to reduced situational awareness. In this paper, the problem was approached by developing a framework for classification of instant message topics of cyber security-themed discussion in Finnish. The program utilizes open source software components in morphological analysis, and subsequently converts the messages into Bag-of-Words representations before classifying them into predetermined incident categories. We compared support vector machines (SVM), multinomial naïve Bayes, and complement naïve Bayes (CNB) classification methods with five-fold cross-validation. A combination of SVM and CNB achieved classification accuracy of over 85 %, while multiclass SVM achieved 87 % accuracy. The implemented program recognizes cyber security-related messages in IRC chat rooms and categorizes them accordingly.
Nanostructured Thermoelectrics: Big Efficiency Gains from Small Features

The field of thermoelectrics has progressed enormously and is now growing steadily because of recently demonstrated advances and strong global demand for cost‐effective, pollution‐free forms of energy conversion. Rapid growth and exciting innovative breakthroughs in the field over the last 10–15 years have occurred in large part due to a new fundamental focus on nanostructured materials. As a result of the greatly increased research activity in this field, a substantial amount of new data—especially related to materials—have been generated. Although this has led to stronger insight and understanding of thermoelectric principles, it has also resulted in misconceptions and misunderstanding about some fundamental issues. This article sets out to summarize and clarify the current understanding in this field; explain the underpinnings of breakthroughs reported in the past decade; and provide a critical review of various concepts and experimental results related to nanostructured thermoelectrics. We believe recent achievements in the field augur great possibilities for thermoelectric power generation and cooling, and discuss future paths forward that build on these exciting nanostructuring concepts.
Region analysis through close contour transformation using growing neural gas

In our work we aim to explore a general framework that addresses the fundamental problem of universal unsupervised extraction of semantically meaningful visual regions. To this end this paper describes a novel region analysis technique using a self-organising map, the growing neural gas, which is adapted so as to improve modelling speed as well as to ensure a double-linkage chain around all region contours to simplify shape analysis. While the growing neural gas has been extensively applied to shape modelling, it has never explicitly been used for curvature analysis, contour description and region similarity. Once a contour network has been obtained, a transformation is applied that converts the closed contour to an open one, facilitating the use of certain angular descriptors. Discriminative descriptors derived from the properties of regions, their contours and their transformed contours are established and define a feature vector used for the representation of regions based on the appearance and contour information.
Density Evolution in the Degree-correlated Stochastic Block Model

There is a recent surge of interest in identifying the sharp recovery thresholds for cluster recovery under the stochastic block model. In this paper, we address the more refined question of how many vertices that will be misclassified on average. We consider the binary form of the stochastic block model, where $n$ vertices are partitioned into two clusters with edge probability $a/n$ within the first cluster, $c/n$ within the second cluster, and $b/n$ across clusters. Suppose that as $n \to \infty$, $a= b+ \mu \sqrt{ b} $, $c=b+ \nu \sqrt{ b} $ for two fixed constants $\mu, \nu$, and $b \to \infty$ with $b=n^{o(1)}$. When the cluster sizes are balanced and $\mu \neq \nu$, we show that the minimum fraction of misclassified vertices on average is given by $Q(\sqrt{v^*})$, where $Q(x)$ is the Q-function for standard normal, $v^*$ is the unique fixed point of $v= \frac{(\mu-\nu)^2}{16} + \frac{ (\mu+\nu)^2 }{16} \mathbb{E}[ \tanh(v+ \sqrt{v} Z)],$ and $Z$ is standard normal. Moreover, the minimum misclassified fraction on average is attained by a local algorithm, namely belief propagation, in time linear in the number of edges. Our proof techniques are based on connecting the cluster recovery problem to tree reconstruction problems, and analyzing the density evolution of belief propagation on trees with Gaussian approximations.
Practicing mindfulness as a means for enhancing workplace pro-environmental behaviors among managers

As ecological concerns become pressing, attempts to address these remain limited to enforcing laws, while alternative ways of encouraging workplace pro-environmental behaviors (WPEBs), such as cultivating mindfulness, remain unexplored. Informed by theories of PEBs from OB-IO literature, we offer propositions detailing the role that practicing mindfulness plays in (directly and indirectly) enhancing managerial propensity to engage in WPEBs. Our paper contributes to extant literature: (1) on theories of PEBs, by showing that some of the same theories that apply to the private domain also hold for commercial organizations; (2) relating mindfulness to PEBs, by expanding the exploration from personal and consumer domains to managerial contexts; and (3) on interventions to enhance WPEBs, by exposing the underlying mechanism of ‘how’ practicing mindfulness enhances managerial engagement in WPEBs. We call for companies to offer more mindfulness-based training programs to employees, since such initiatives complement laws and other interventions in supporting WPEBs.
A Behavior Based Kernel for Policy Search via Bayesian Optimization

We expand on past successes applying Bayesian Optimization (BO) to the Reinforcement Learning (RL) problem. BO is a general method of searching for the maximum of an unknown objective function. The BO method explicitly aims to reduce the number of samples needed to identify the optimal solution by exploiting a probabilistic model of the objective function. Much work in BO has focused on Gaussian Process (GP) models of the objective. The performance of these models relies on the design of the kernel function relating points in the solution space. Unfortunately, previous approaches adapting ideas from BO to the RL setting have focused on simple kernels that are not well justified in the RL context. We show that a new kernel can be motivated by examining an upper bound on the absolute difference in expected return between policies. The resulting kernel explicitly compares the behaviors of policies in terms of the trajectory probability densities. We incorporate the behavior based kernel into a BO algorithm for policy search. Results reported on four standard benchmark domains show that our algorithm significantly outperform alternative state-of-the-art algorithms.
OPN‐a induces muscle inflammation by increasing recruitment and activation of pro‐inflammatory macrophages

What is the central question of this study? What is the functional relevance of OPN isoform expression in muscle pathology? What is the main finding and its importance? The full‐length human OPN‐a isoform is the most pro‐inflammatory isoform in the muscle microenvironment, acting on macrophages and myoblasts in an RGD‐integrin‐dependent manner. OPN‐a upregulates expression of tenascin‐C (TNC), a known Toll‐like receptor 4 (TLR4) agonist. Blocking TLR4 signalling inhibits the pro‐inflammatory effects of OPN‐a, suggesting that a potential mechanism of OPN action is by promoting TNC–TLR4 signalling.
An approximately strategy-proof mechanism for radio spectrum allocation

In wireless networks, a recent trend is to make spectrum access dynamic for the sake of efficient utilization of spectrum. In this case, one promising approach is using auction-based market mechanism where available channels are periodically allocated to users. Two of the key objectives in designing an auction mechanism are strategy-proofness and social welfare maximization. It is hard to design a practical auction achieving both objectives. Prior work either do not consider strategy-proofness or do not guarantee performance ratio. In this paper, we achieve a tradeoff between supporting strong strategy-proofness and maximizing social welfare. We design a polynomial-time spectrum auction mechanism that is approximately strategy-proof which bounds the profit gain of a bidder from a lying bid, and yields an allocation with approximate social welfare. Through simulations, we show that our mechanism improves performance by about 30% in terms of social welfare and spectrum utilization, compared to the state-of-art mechanisms.
Market Structure, Reputation, and the Value of Quality Certification

Quality certification programs help consumers identify high-quality products or sellers in markets with information asymmetries. Using data from eBay UK's online marketplace, we study how certification's impact on demand varies with market- and seller- level attributes, exploiting variation in sellers' certification status within groups of near-identical listings. The positive effects of eBay's "top rated seller" certification are stronger for categories with few other certified sellers, in more competitive markets, and for sellers with shorter records of past performance. These findings indicate certification provides more value when certification is rare, the product space is crowded, and for sellers lacking established reputations. (JEL D12, D82, L15, L86)
Privacy-Preserving Singular Value Decomposition

In this paper, we propose secure protocols to perform Singular Value Decomposition (SVD) for two parties over horizontally and vertically partitioned data. We propose various secure building blocks for the computations of QR algorithm so that it is privacy-preserving. Some of the proposed secure building blocks include Secure Matrix Multiplication, $(x+y)^{-1}$, and $\sqrt{x+y}$. Together, they allow us to derive Privacy-Preserving SVD (PPSVD) based on a privacy-preserving QR algorithm. Finally we conduct experiments to evaluate the proposed secure building blocks and protocols. The results show that the proposed protocols for SVD achieve high accuracy for matrices of small and medium size.