Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Inferior Epigastric Artery Perforator Flap Breast Reconstruction in Women With Previous Abdominal Incisions: A Comparison of Complication Rates

Background The deep inferior epigastric artery perforator (DIEP) flap is currently the most widely used method for autologous microsurgical breast reconstruction. There are mixed data in the literature regarding the impact of previous abdominal surgery on DIEP flap success in breast reconstruction. With this study, we take a closer look at the effect of prior abdominal surgery on DIEP flap and donor-site complications, with a particular focus on the different types of incisions and their influence on surgical outcomes. Methods A retrospective cohort study was conducted over a 6-year period. Five hundred forty-four consecutive DIEP flaps were divided into a control group (321 flaps) without previous abdominal surgery and an incision group (223 flaps) with previous abdominal surgery. A comparison between both groups was made in terms of flap and donor-site complications followed by a subgroup analysis based on single types of abdominal incisions. Results There were no significant differences between both groups in terms of age, body mass index, flap weight, smoking history, prior radiotherapy, diabetes, and coagulopathy (P > 0.05). The most common incision was low transverse incision (n = 116) followed by laparoscopy port (n = 103) and midline (n = 46) incisions. We found no significant differences between the control group and incision group in terms of flap complications. Subgroup analysis revealed that none of the 3 types of incision increase the flap or donor-site complications. Smoking and flap weight were the only 2 independent predictors for donor-site complications. Conclusions The results from this large series of consecutive DIEP flaps from our institution confirm that autologous breast reconstruction with DIEP flap can be safely performed in patients who have had previous abdominal surgeries; however, counseling patients about smoking is critical to avoid potential donor-site complications.
Named-Entity Tagging and Domain adaptation for Better Customized Translation

Customized translation need pay spe-cial attention to the target domain ter-minology especially the named-entities for the domain. Adding linguistic features to neural machine translation (NMT) has been shown to benefit translation in many studies. In this paper, we further demonstrate that adding named-entity (NE) feature with named-entity recognition (NER) into the source language produces better translation with NMT. Our experiments show that by just including the different NE classes and boundary tags, we can increase the BLEU score by around 1 to 2 points using the standard test sets from WMT2017. We also show that adding NE tags using NER and applying in-domain adaptation can be combined to further improve customized machine translation.
Implementation of a Brain-Computer Interface on a Lower-Limb Exoskeleton

In this paper, we propose to use brain-computer interface (BCI) to control a lower-limb exoskeleton. The exoskeleton follows the wearer’s motion intention through decoding of electroencephalography (EEG) signals and multi-modal cognition. Motion patterns as standing up, sitting down, and walking forward can be performed. We implemented two types of BCIs, one based on steady-state visual evoked potentials, which used canonical correlation analysis to extract the frequency the subject focused on. The other BCI is based on motor imagery, where the common spatial patterns method was employed to extract the features from the EEG signal. Then, the features were classified by support vector machine to recognize the intention of the subject. We invited four healthy subjects to participate in the experiments, including off-line and online. The off-line experiments trained the classifier and then were used online to test the performance of the BCI controlled exoskeleton system. The results showed high accuracy rate in motion intention classification tasks for both BCIs.
Towards a Trait Model of Video Game Preferences

ABSTRACT Typologies for understanding players’ preferences toward different gameplay styles have gained popularity in research. However, attempts to model players’ preferences are based on type models instead of trait models, contrary to the latest personality research. One such model, BrainHex, was designed as an interim model to enable investigations toward a definitive player trait model. However, it lacks empirical validation in support of its psychometric properties. The present work analyzed a dataset with over 50,000 respondents to devise a player traits model based off the BrainHex scale. Results indicate three player traits: action, esthetic, and goal orientation. Furthermore, we analyzed the games listed by participants as examples of what they enjoy, to understand which factors influence player preferences. Results illustrate that the emergent player traits and participants’ genders and attitudes toward story can partially explain player preferences toward certain games. Finally, we present the implications toward a definitive player traits model.
ChronosDB: Distributed, File Based, Geospatial Array DBMS

An array DBMS streamlines large N -d array management. A large portion of such arrays originates from the geospatial domain. The arrays often natively come as raster files while standalone command line tools are one of the most popular ways for processing these files. Decades of development and feedback resulted in numerous feature-rich, elaborate, free and quality-assured tools optimized mostly for a single machine. ChronosDB partially delegates in situ data processing to such tools and offers a formal N -d array data model to abstract from the files and the tools. ChronosDB readily provides a rich collection of array operations at scale and outperforms SciDB by up to 75× on average.
Secrecy Rate and Harvested Energy Trade-Off for MISO Channels with Finite-Alphabet Inputs

We focus on transmit signal design for multiple- input single-output (MISO) wiretap channels with simultaneous wireless information and power transfer (SWIPT). Assuming that the channel inputs are drawn from standard constellation sets, we formulate secrecy rate maximization problems subject to power and harvested energy constraints. We tackle these problems under two different assumptions on the channel state information (CSI) at the transmitter. First, we consider a scenario in which the transmitter knows the CSI for both the information receiver and the energy receiver (potential eavesdropper), and we propose a precoder optimization approach. Then, we investigate the case where only perfect CSI of the information receiver is available along with the statistical CSI of the energy receiver. Our numerical results demonstrate the efficacy of the proposed solutions.
Minimal Transport Networks with General Boundary Conditions

Vascular networks are used across the kingdoms of life to transport fluids, nutrients and cellular material. A popular unifying idea for understanding the diversity and constraints of these networks is that the conduits making up the network are organized to optimize dissipation or other functions within the network. However the general principles governing the optimal networks remain unknown. In particular Durand showed that under Neumann boundary conditions networks, that minimize dissipation should be trees. Yet many real transport networks, including capillary beds, are not simply connected. Previously multiconnectedness in a network has been assumed to provide evidence that the network is not simply minimizing dissipation. Here we show that if the boundary conditions on the flows within the network are enlarged to include physical reasonable Neumann and Dirichlet boundary conditions (i.e. constraints on either pressure or flow) then minimally dissipative networks need not be trees. To get to this result we show that two methods of producing optimal networks, namely enforcing constraints via Lagrange multipliers or via penalty methods, are equivalent for tree networks.
Improved Energy Efficiency of Massive MIMO-OFDM in Battery-Limited IoT Networks

We investigate the feasibility of improving the energy efficiency (EE) of massive multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems applied to a battery-limited Internet of Things (IoT) networks. Improving EE is especially important for battery limited IoT devices. We observe the uplink and downlink aspects of massive MIMO-OFDM-based IoT networks and categorize some of the effective methods to consider. As uplink aspect, we consider the uplink reference signal (RS) power control. Reducing uplink RS power could induce the battery saving of IoT devices but could cause an increase in channel estimation error. As downlink aspect, we consider the peak-to-average power ratio reduction of the OFDM signal and downlink transmitter power control. These techniques are well-known as effective EE improvement methods, but there is little work showing the actual EE gain in system perspective. In addition, we also consider the utilization of radio frequency energy transfer using unmanned aerial vehicles to extend the operating time of battery-limited IoT devices. We derive the theoretical closed-form approximations of spectral efficiency and EE when applying these methods and provide EE gains for various scenarios. Numerical results show that the theoretical analysis is in good agreement with the simulation results and thus can be used as useful tools to improve EE.
Design and Analysis for Dual Priority Scheduling

This paper considers Dual Priority (DP) scheduling of constrained deadline sporadic tasks on uniprocessor. The initial fixed priority of each job of a task is promoted to a higher priority (called, promoted priority) after a fixed time interval (called, promotion point) relative to the release time of that job. DP scheduling alters the default preemptive behavior of traditional fixed priority (FP) scheduling to efficiently utilize the processor as close as possible to that of the optimal earliest deadline first (EDF) scheduler. In this paper, we address some of the main challenges of DP scheduling including derivation of a sufficient schedulability test, determination of promotion point of each task1. To the best of our knowledge, this test is the first schedulability test for DP scheduling applicable to constrained deadline sporadic tasks. The test is applicable for any given promotion points of the tasks and has pseudo-polynomial time complexity. We also propose two different heuristics to assign the promotion points, and experimental results show that the proposed test achieves performance very close to that of EDF scheduling.
Supplementary Material to: Recovering Accurate 3D Human Pose in The Wild Using IMUs and a Moving Camera

This document contains additional experiments to the paper ”Recovering Accurate 3D Human Pose in The Wild Using IMUs and a Moving Camera”[1]. These experiments validate different aspects of VIP, our proposed method for combining IMU-based tracking with a single hand-held camera, and provide further details to the proposed 3DPW. In Section 1, we validate that the explicit modeling of IMU heading errors is an important ingredient of the proposed method. In Section 2 we evaluate tracking accuracy of VIP for an additional IMU sensor setup. In order to demonstrate the challenges of our newly recorded dataset in comparison to existing datasets, we evaluate three monocular 3D pose estimation methods in Section 3.
Content-Sensitive Characterization of Peer Interactions of Highly Engaged Users in an Online Community for Smoking Cessation: Mixed-Methods Approach for Modeling User Engagement in Health Promotion Interventions

Background Online communities provide affordable venues for behavior change. However, active user engagement holds the key to the success of these platforms. In order to enhance user engagement and in turn, health outcomes, it is essential to offer targeted interventional and informational support. Objective In this paper, we describe a content plus frequency framework to enable the characterization of highly engaged users in online communities and study theoretical techniques employed by these users through analysis of exchanged communication. Methods We applied the proposed methodology for analysis of peer interactions within QuitNet, an online community for smoking cessation. Firstly, we identified 144 highly engaged users based on communication frequency within QuitNet over a period of 16 years. Secondly, we used the taxonomy of behavior change techniques, text analysis methods from distributional semantics, machine learning, and sentiment analysis to assign theory-driven labels to content. Finally, we extracted content-specific insights from peer interactions (n=159,483 messages) among highly engaged QuitNet users. Results Studying user engagement using our proposed framework led to the definition of 3 user categories—conversation initiators, conversation attractors, and frequent posters. Specific behavior change techniques employed by top tier users (threshold set at top 3) within these 3 user groups were found to be goal setting, social support, rewards and threat, and comparison of outcomes. Engagement-specific trends within sentiment manifestations were also identified. Conclusions Use of content-inclusive analytics has offered deep insight into specific behavior change techniques employed by highly engaged users within QuitNet. Implications for personalization and active user engagement are discussed.
Response of carbon dioxide emissions to sheep grazing and N application in an alpine grassland - Part 1: Effect of sheep grazing

Widespread nitrogen (N) enrichment resulting from anthropogenic activities has led to great changes in car- bon exchange between the terrestrial biosphere and the atmo- sphere. Grassland is one of the most sensitive ecosystems to N deposition. However, the effect of N deposition on ecosys- tem respiration (Re) in grasslands has been conducted mainly in temperate grasslands, which are limited largely by water availability, with few studies focused on alpine grasslands that are primarily constrained by low temperatures. Failure to assess the magnitude of the response in Re outside the grow- ing season (NGS) in previous studies also limits our under- standing of carbon exchange under N deposition conditions. To address these knowledge gaps we used a combination of static closed chambers and gas chromatography in an alpine grassland from 2010 to 2011 to test the effects of N appli- cation on ecosystem respiration (Re) both inside and outside the growing season. There was no significant change in CO 2 emissions under N application. Re outside the growing sea- son was at least equivalent to 9.4 % of the CO2 fluxes dur- ing the growing season (GS). Annual Re was calculated to be 279.0-403.9 g CO2 m 2 yr 1 in Bayinbuluk alpine grass- lands. In addition, our results indicate that soil temperature was the dominant abiotic factor regulating variation in Re in the cold and arid environment. Our results suggest that short- term N additions exert no significant effect on CO 2 emissions in alpine grassland.
Energy-saving occupant behaviours in offices: change strategies

ABSTRACT As regulated energy consumption in buildings is reduced, the proportional importance of unregulated energy consumption increases. Reducing unregulated energy use in the commercial office requires an understanding of the factors that influence workplace behaviour. To date these factors have been assumed to be similar to those that influence behaviour in the home. However, the social dynamics of the workplace are different to those in the home. This study examines the degree to which theories of behaviour change generated largely in a domestic building setting could be used as the basis for designing interventions to reduce unregulated energy consumption in the workplace. It studies the unregulated energy consumption of 39 workers engaged in office-type activities in two separate locations. Following a 100-day monitoring period, three behaviour change interventions were developed and their impact measured over a 100-day period. Results from the study found, on average, an 18.8% reduction in energy use was achieved. Furthermore, by comparing pre- and post-intervention responses to an environmental questionnaire, it was evident that savings were realized without significant changes to pro-environmental attitude or perceived social norms, which may have implications for energy-saving interventions in the commercial sector.
Verification of iris image authenticity using fragile watermarking

This paper proposes and evaluates a watermarking-based approach to certify the authenticity of iris images when they are captured by a genuine equipment. In the proposed method, the iris images are secretly signed before being used in biometric processes, and the resulting signature is embedded into the JPEG carrier image in the DCT domain in a data-dependent way. Any alteration of the original (certified) image makes the signature no longer corresponding to this image and this change can be quickly identified at the receiver site. Hence, it is called fragile watermarking to differentiate this method from regular watermarking that should present some robustness against image alterations. There is no need to attach any auxiliary signature data, hence the existing, already standardized transmission channels and storage protocols may be used. The embedding procedure requires to remove some part of the original information. But, by using the BATH dataset comprising 32 000 iris images collected for 1 600 distinct eyes, we verify that the proposed alterations have no impact on iris recognition reliability, although statistically significant, small differences in genuine score distributions are observed when the watermark is embedded to both the enrollment and verification iris images. This is a unique evaluation of how the watermark embedding of digital signatures into the ISO CROPPED iris images (during the enrollment, verification or both) influences the reliability of a well-established, commercial iris recognition methodology. Without loss in generality, this approach is targeted to biometric-enabled ID documents that deploy iris data to authenticate the holder of the document. In this paper, a watermarking-based approach is designed for authentication of biometric data [1, 2], i.e., to assure that the data was generated by a certified sensor. Fig. 1 presents a general idea of the proposed methodology. Note that the certification of iris images stored within the document memory (template images) is independent of the certification of devices used when a subject is being verified, i.e., generating verification images. The certification process is also independent of the biometric recognition, as both processes (certification and biometrics) must not interfere with each other. In contrast to typical watermarking, which should be robust to small alterations in the carrier (for instance, with the aim of removing the watermark), this approach intentionally makes the
Does Conservation Status Matter if You’re Ugly? An Experimental Survey of Species Appeal and Public Support

Wildlife conservation is of the utmost importance to the preservation of a healthy planet, with the extinction of wild animals increasing at previously unseen rates. However, conservation is also becoming increasingly difficult without strong public support, and this often varies in extent and success when it comes to different species and taxa. There is considerable research investigating how the physical characteristics of species affect public support of their conservation. Results suggest species seen as more charismatic, or even more likeable, are more likely to gain support for their conservation, regardless of conservation status. This study aimed to identify whether conservation status, and concern for it, is as important of a consideration for endangered species that are not seen as simply likeable or appealing, or whether this tends to be more ignored for such species. We found that for the treatments/species we chose in our experiment, and in the context we distributed the survey in, their conservation status was a more significant factor than their perceived appeal when it came to public support for their conservation. These results have implications for wildlife conservation efforts, as it shows that appeal is not always the most important factor when attempting to garner support, and that influencing the perception of concern for certain species may be a more effective avenue than relying on appeal for successful wildlife conservation.
Job insecurity, employability and satisfaction among temporary and permanent employees in post-crisis Europe

Earlier studies established that perceived job insecurity is more strongly related to the experiences of permanent employees, and conversely that perceived employability is more strongly related to the experiences of temporary employees. This article challenges these results against the background of the 2008/2009 crisis using samples from the 2010 European Social Survey with employees from Continental and Mediterranean Europe. First, the authors argue that job insecurity has become a structural phenomenon that associates with temporary and permanent employees’ satisfaction in the same fashion, which found overall support. Second, they argue that employability may have become important for all employees, regardless of contract type, which was largely supported. A cause for concern is that the relationship between perceived job insecurity and satisfaction was comparatively stronger than the relationship between perceived employability and satisfaction. This may suggest that employees have not yet fully embraced ideas about employability as the new form of security.
Towards a Repeated Negotiating Agent that Treats People Individually: Cooperation, Social Value Orientation, & Machiavellianism

We present the results of a study in which humans negotiate with computerized agents employing varied tactics over a repeated number of economic ultimatum games. We report that certain agents are highly effective against particular classes of humans: several individual difference measures for the human participant are shown to be critical in determining which agents will be successful. Asking for favors works when playing with pro-social people but backfires with more selfish individuals. Further, making poor offers invites punishment from Machiavellian individuals. These factors may be learned once and applied over repeated negotiations, which means user modeling techniques that can detect these differences accurately will be more successful than those that don't. Our work additionally shows that a significant benefit of cooperation is also present in repeated games---after sufficient interaction. These results have deep significance to agent designers who wish to design agents that are effective in negotiating with a broad swath of real human opponents. Furthermore, it demonstrates the effectiveness of techniques which can reason about negotiation over time.
Stock returns and investors' mood: Good day sunshine or spurious correlation? ☆

This paper critically evaluates the signi ﬁ cant weather effect on stock return reported in two seminal studies of investors'moodonstockmarket.Itisfoundthattheirresearchdesignofmaximizingstatisticalpowerbypooling as many data points as possible is statistically ﬂ awed, with a consequence that the test is severely biased against the null hypothesis of no effect. Coupled with small effect size estimates and test statistics in ﬂ ated by massive samplesizes,thisstronglysuggestsspuriousstatisticalsigni ﬁ canceasanoutcomeofTypeIerror.Thealternatives tothe p -value criterion for statisticalsigni ﬁ cancesoundlysupportthe nullhypothesisof noweather effect. As an application, the effect of daily sunspot numbers on stock return is examined. Under the same research design as thatofaseminalstudy,thenumberofsunspotsisfoundtobehighlystatisticallysigni ﬁ cantalthoughitseconomic impact on stock return is negligible.