Miracle-dz/UniFAR-FTUs huggingface dataset:
Operating at a Distance - How a Teleoperated Surgical Robot Reconfigures Teamwork in the Operating Room

This paper investigates how a teleoperated surgical robot reconfigures teamwork in the operating room by spatially redistributing team members. We report on findings from two years of fieldwork at two hospitals, including interviews and video data. We find that while in non-robotic cases team members huddle together, physically touching, introduction of a surgical robot increases physical and sensory distance between team members. This spatial rearrangement has implications for both cognitive and affective dimensions of collaborative surgical work. Cognitive distance is increased, necessitating new efforts to maintain situation awareness and common ground. Moreover, affective distance is introduced, decreasing sensitivity to shared and non-shared affective states and leading to new practices aimed at restoring affective connection within the team. We describe new forms of physical, cognitive, and affective distance associated with teleoperated robotic surgery, and the effects these have on power distribution, practice, and collaborative experience within the surgical team.
View Inter-Prediction GAN: Unsupervised Representation Learning for 3D Shapes by Learning Global Shape Memories to Support Local View Predictions

In this paper, we present a novel unsupervised representation learning approach for 3D shapes, which is an important research challenge as it avoids the manual effort required for collecting supervised data. Our method trains an RNNbased neural network architecture to solve multiple view inter-prediction tasks for each shape. Given several nearby views of a shape, we define view inter-prediction as the task of predicting the center view between the input views, and reconstructing the input views in a low-level feature space. The key idea of our approach is to implement the shape representation as a shape-specific global memory that is shared between all local view inter-predictions for each shape. Intuitively, this memory enables the system to aggregate information that is useful to better solve the view inter-prediction tasks for each shape, and to leverage the memory as a viewindependent shape representation. Our approach obtains the best results using a combination of L2 and adversarial losses for the view inter-prediction task. We show that VIP-GAN outperforms state-of-the-art methods in unsupervised 3D feature learning on three large-scale 3D shape benchmarks.
Calculation of Pulse Signal Propagation in Periodic Structures with Mode Expansion in Time Domain Method

Mode Expansion in Time Domain (METD) method, also known as Mode Basis Method, was developed for solution of problem of pulse signal propagation in periodic structures. General formulae of the method are given. For simple example of periodic structure the mode basis is constructed, System of Evolutionary Equation (SEE) for amplitudes of expansion over this basis is obtained, effective numerical method for SEE solution is presented. The method convergence was proved, calculation results were compared with FDTD results. Numerical efficiency of METD in comparison with FDTD is explained and demonstrated.
Heterologous expression of a Glyoxalase I gene from sugarcane confers tolerance to several environmental stresses in bacteria

Glyoxalase I belongs to the glyoxalase system that detoxifies methylglyoxal (MG), a cytotoxic by-product produced mainly from triose phosphates. The concentration of MG increases rapidly under stress conditions. In this study, a novel glyoxalase I gene, designated as SoGloI was identified from sugarcane. SoGloI had a size of 1,091 bp with one open reading frame (ORF) of 885 bp encoding a protein of 294 amino acids. SoGloI was predicted as a Ni2+-dependent GLOI protein with two typical glyoxalase domains at positions 28–149 and 159–283, respectively. SoGloI was cloned into an expression plasmid vector, and the Trx-His-S-tag SoGloI protein produced in Escherichia coli was about 51 kDa. The recombinant E. coli cells expressing SoGloI compared to the control grew faster and tolerated higher concentrations of NaCl, CuCl2, CdCl2, or ZnSO4. SoGloI ubiquitously expressed in various sugarcane tissues. The expression was up-regulated under the treatments of NaCl, CuCl2, CdCl2, ZnSO4 and abscisic acid (ABA), or under simulated biotic stress conditions upon exposure to salicylic acid (SA) and methyl jasmonate (MeJA). SoGloI activity steadily increased when sugarcane was subjected to NaCl, CuCl2, CdCl2, or ZnSO4 treatments. Sub-cellular observations indicated that the SoGloI protein was located in both cytosol and nucleus. These results suggest that the SoGloI gene may play an important role in sugarcane’s response to various biotic and abiotic stresses.
Mimisbrunnur: AI-Assisted Authoring for Interactive Storytelling

Authoring in the context of Interactive Storytelling (IS) is inherently difficult, and there is a need for authoring tools that both enable and assist authors in the creation of new content. In this paper, we discuss our approach for creating an AI-assisted authoring tool via the concept of mixed-initiative systems. We introduce our tool, Mimisbrunnur, which uses this concept to assist authors in the creation of story content. We explain how the tool functions and introduce its fundamental components, including Natural Language Processing, a Suggestion Generator, and three authoring modules.
Region-Based Co-Seismic Ground Displacement Dectection Using Optical Aerial Imagery

Ground analysis is important after an earthquake occurred in order to understand the surface variations. By optical imagery before and after a disaster, this paper tries to find the co-seismic ground displacement using region-based image patches. By comparing the similarity of pre- and post-event orthophotos, regions of ground changes can be detected. Conjugate objects were then recognized through feature extraction and image matching. An image with pose parameters can estimate the three-dimensional positions of those objects in the world space. Thus, three-dimensional geometric correlation between the pre- and post-event objects can measure the ground displacement. The results indicate that the proposed approach is able to estimate the co-seismic ground displacements based on the spatial information from optical imagery. In addition, surface shifts can be identified based on the spatial correlations.
Evaluating the Ability of LSTMs to Learn Context-Free Grammars

While long short-term memory (LSTM) neural net architectures are designed to capture sequence information, human language is generally composed of hierarchical structures. This raises the question as to whether LSTMs can learn hierarchical structures. We explore this question with a well-formed bracket prediction task using two types of brackets modeled by an LSTM. Demonstrating that such a system is learnable by an LSTM is the first step in demonstrating that the entire class of CFLs is also learnable. We observe that the model requires exponential memory in terms of the number of characters and embedded depth, where a sub-linear memory should suffice. Still, the model does more than memorize the training input. It learns how to distinguish between relevant and irrelevant information. On the other hand, we also observe that the model does not generalize well. We conclude that LSTMs do not learn the relevant underlying context-free rules, suggesting the good overall performance is attained rather by an efficient way of evaluating nuisance variables. LSTMs are a way to quickly reach good results for many natural language tasks, but to understand and generate natural language one has to investigate other concepts that can make more direct use of natural language’s structural nature.
Geraniin Differentially Modulates Chromosome Stability of Colon Cancer and Noncancerous Cells by Oppositely Regulating their Spindle Assembly Checkpoint

Geraniin has been reported to specifically induce apoptosis in multiple human cancers, but the underlying mechanism is poorly defined. The spindle assembly checkpoint (SAC) is a surveillance system to ensure high‐fidelity chromosome segregation during mitosis. Weakening of SAC to enhance chromosome instability (CIN) can be therapeutic because very high levels of CIN are lethal. In this study, we have investigated the effects of geraniin on the SAC of colorectal cancer HCT116 cells and noncancerous colon epithelial CCD841 cells. We find that treatment of HCT116 cells with geraniin leads to dose‐dependent decrease of cell proliferation, colony formation, and anchorage‐independent growth. Geraniin is found to induce apoptosis in mitotic and postmitotic HCT116 cells. Furthermore, geraniin weakens the SAC function of HCT116 cells by decreasing the transcriptional expression of several SAC kinases (particularly Mad2 and Bub1), which in turn leads to premature anaphase entry, mitotic aberrations, and CIN in HCT116 cells. In contrast, the proliferation of CCD841 cells is slightly inhibited by geraniin. Even more interestingly, geraniin increases the transcriptional expression of several SAC kinases (e.g., Mad1 and BubR1) to strengthen SAC efficiency, which contributes to the reduction of mitotic aberrations and CIN in CCD841 cells. Altogether, our findings reveal that the SAC pathway in human colon cancer and noncancerous cell lineages responses oppositely to geraniin treatment, resulting CIN promotion and suppression, respectively. Specific abrogation of SAC to induce catastrophic CIN in HCT116 cells may account for the selective anticancer action of geraniin. Environ. Mol. Mutagen. 60:254–268, 2019. © 2018 Wiley Periodicals, Inc.
PENGARUH PROMOSI KESEHATAN TERHADAP PERUBAHAN PERILAKU MEROKOK KARYAWAN (Studi Kasus Di Rumah Sakit Umum Daerah dr. Zainoel Abidin Banda Aceh)

Perilaku merokok adalah bentuk nyata yang dilakukan individu terhadap kebiasaan merokok. Determinan perilaku merokok dapat disebabkan oleh banyak faktor baik internal dan eksternal individu. Perilaku merokok pada karyawan di Rumah Sakit Umum Zainoel Abidin di Banda Aceh merupakan suatu fenomena perilaku merokok karyawan. Strategi pengurangan perilaku merokok karyawan dilakukan dengan upaya promosi kesehatan. Penelitian ini merupakan penelitian tindakan yang dimaksudkan untuk menganalisis perubahan perilaku merokok pada karyawan. Sampel untuk penelitian ini adalah staf perokok laki-laki sebanyak 152 orang. Data dianalisis dengan Uji Wilxocon Rank, Chi Square Test, t-dependent, dan Uji Regresi Multi Logistik pada tingkat kepercayaan 95%. Hasil penelitian menunjukkan bahwa intervensi promosi kesehatan terdiri dari pemberdayaan, dukungan sosial, dan advokasi untuk meningkatkan pengetahuan, sikap, dan secara statistik berpengaruh secara signifikan terhadap meningkatnya perilaku merokok pada karyawan dan mengembangkan konsep perilaku berhenti merokok. Intervensi promosi kesehatan, pengetahuan dan sikap karyawan mempengaruhi perilaku karyawan berhenti merokok. Intervensi promosi kesehatan melalui program konseling (perorangan, kelompok dan massa), pemberian leaflet, pemasangan poster di dalam Rumah Sakit, dan pemasangan tanda dilarang merokok terbukti efektif meningkatkan pengetahuan, sikap positif dan dapat mengurangi perilaku merokok karyawan. Teruslah evaluasi, pantau dan perkuat kebijakan pelarangan merokok di Rumah Sakit, serta peningkatan promosi kesehatan melalui pemberdayaan karyawan, membangun kemitraan, advokasi dan partisipasi semua elemen Rumah Sakit. Kata Kunci: Intervensi Promosi Kesehatan, Perilaku Merokok Karyawan.
Nitric oxide synthase enzymology in the 20 years after the Nobel Prize

This review briefly summarizes what was known about NOS enzymology at the time of the Nobel Prize award in 1998 and then discusses from the author's perspective some of the advances in NOS enzymology over the subsequent 20 years, focused on five aspects: the maturation process of NOS enzymes and its regulation; the mechanism of NO synthesis; the redox roles played by the 6R‐tetrahydrobiopterin cofactor; the role of protein conformational behaviour in enabling NOS electron transfer and its regulation by NOS structural elements and calmodulin, and the catalytic cycling pathways of NOS enzymes and their influence on NOS activity.
Linear Spectral Unmixing via Matrix Factorization: Identifiability Criteria for Sparse Abundances

In hyperspectral unmixing and in many other areas (e.g., chemometrics, topic modeling, archetypal analysis) simplex-structured matrix factorization (SSMF) plays an essential role as suggested by years of research efforts devoted to this theme. Specifically, SSMF factorizes a data matrix into two matrix factors with one factor (i.e., the abundances) constrained to have its columns lying in the unit simplex. SSMF criteria include the well-known Craig's seminal minimum-volume enclosing simplex (MVES), originally proposed for blind hyperspectral unmixing, and the recently introduced maximum-volume inscribed ellipsoid (MVIE). The identifiability analysis of those criteria is essential to understand their fundamental behavior and also to devise effective SSMF algorithms tailored to the specificities of the different application scenarios. Our analysis is motivated by a simple fact taking place in most remotely sensed hyperspectral mixtures: in most pixels, only a subset of the materials is present. This is to say that the abundances exhibit a form of sparsity and thus lie in the boundary of the data simplex. We then derive some elegant sufficient condition, showing that as long as data points are locally well spread, perfect SSMF identifiability of both criteria can be guaranteed.
Incremental learning algorithms and applications

Incremental learning refers to learning from streaming data, which arrive over time, with limited memory resources and, ideally, without sacrificing model accuracy. This setting fits different application scenarios where lifelong learning is relevant, e.g. due to changing environments , and it offers an elegant scheme for big data processing by means of its sequential treatment. In this contribution, we formalise the concept of incremental learning, we discuss particular challenges which arise in this setting, and we give an overview about popular approaches, its theoretical foundations, and applications which emerged in the last years.
Cochlear Reflectance and Otoacoustic Emission Predictions of Hearing Loss.

OBJECTIVES Cochlear reflectance (CR) is the cochlear contribution to ear-canal reflectance. CR is a type of otoacoustic emission (OAE) that is calculated as a transfer function between forward pressure and reflected pressure. The purpose of this study was to compare wideband CR to distortion-product (DP) OAEs in two ways: (1) in a clinical-screening paradigm where the task is to determine whether an ear is normal or has hearing loss and (2) in the prediction of audiometric thresholds. The goal of the study was to assess the clinical utility of CR. DESIGN Data were collected from 32 normal-hearing and 124 hearing-impaired participants. A wideband noise stimulus presented at 3 stimulus levels (30, 40, 50 dB sound pressure level) was used to elicit the CR. DPOAEs were elicited using primary tones spanning a wide frequency range (1 to 16 kHz). Predictions of auditory status (i.e., hearing-threshold category) and predictions of audiometric threshold were based on regression analysis. Test performance (identification of normal versus impaired hearing) was evaluated using clinical decision theory. RESULTS When regressions were based only on physiological measurements near the audiometric frequency, the accuracy of CR predictions of auditory status and audiometric threshold was less than reported in previous studies using DPOAE measurements. CR predictions were improved when regressions were based on measurements obtained at many frequencies. CR predictions were further improved when regressions were performed on males and females separately. CONCLUSIONS Compared with CR measurements, DPOAE measurements have the advantages in a screening paradigm of better test performance and shorter test time. The full potential of CR measurements to predict audiometric thresholds may require further improvements in signal-processing methods to increase its signal to noise ratio. CR measurements have theoretical significance in revealing the number of cycles of delay at each frequency that is most sensitive to hearing loss.
Satisfaction With the Self-Assessment of University Students Through e-Coping With Academic Stress UtilityTM

The general purpose of this report is: (1) research was to check whether the degree of satisfaction with the self-assessment activity of university students was related to the scores obtained and the degree of different variables, associated with level of Self-Regulation; (2) to present the online utility, e-Coping with Academic StressTM, as a technological development in Educational Psychology; (3) analyze the possibilities of transfer of this technological innovation. A total of 929 university students, coming from a public university, participated in the use of this online utility. University students can use the tool’s online inventories to make self-assessments in the different variables of Studying, Learning and Performing under Stress (SLPS Competency Model). Descriptives, correlational and inferential analyzes (ANOVAs and MANOVAs) were carried out. The results allowed to know the profile of competences of the analyzed university students, in addition to the degree of satisfaction with the self-evaluation. Finally, we communicate possible actions and options available for transfer of this resulting technology, through RD transfer contracts arranged directly or with other universities.
Arginine-rich cell-penetrating peptides induce membrane multilamellarity and subsequently enter via formation of a fusion pore

Significance The passive translocation mechanism of arginine-rich cell-penetrating peptides has puzzled the scientific community for more than 20 y. In this study we propose a hitherto unrecognized mechanism of passive cell entry involving fusion of multilamellar structures generated by the cell-penetrating peptides. The geometry of entry for this mechanism is completely different from previously suggested direct translocation mechanisms, leading to another paradigm for designing molecular carriers for drug delivery to the cell. Arginine-rich cell-penetrating peptides do not enter cells by directly passing through a lipid membrane; they instead passively enter vesicles and live cells by inducing membrane multilamellarity and fusion. The molecular picture of this penetration mode, which differs qualitatively from the previously proposed direct mechanism, is provided by molecular dynamics simulations. The kinetics of vesicle agglomeration and fusion by an iconic cell-penetrating peptide—nonaarginine—are documented via real-time fluorescence techniques, while the induction of multilamellar phases in vesicles and live cells is demonstrated by a combination of electron and fluorescence microscopies. This concert of experiments and simulations reveals that the identified passive cell penetration mechanism bears analogy to vesicle fusion induced by calcium ions, indicating that the two processes may share a common mechanistic origin.
İlköğretim Okulu Öğretmenlerinin Sınıf Yönetimi Tarzları ile Demokratik Değerlere İlişkin Görüşleri Arasındaki İlişki

Bu calismanin amaci ilkogretim okulu ogretmenlerinin sinif yonetimi tarzlarini, demokratik degerlere iliskin goruslerini ve bu iki gorus arasindaki iliskiyi belirlemektir. Tarama modelindeki arastirmanin orneklemi Kutahya il merkezindeki ilkogretim okullarinda gorev yapan 300 ogretmenden olusmaktadir. Bulgulara gore ilkogretim okulu ogretmenleri daha cok, takdir edilen sinif yonetimi tarzina sahiptir. Ogretmenlerin sinif yonetimi tarzlari cinsiyetlerine gore degismezken, otoriter sinif yonetimi tarzlari brans; takdir edilen sinif yonetimi tarzlari egitim durumu ve yas; basibos sinif yonetimi tarzlari brans, egitim durumu ve kideme gore degismektedir. Ogretmenler demokratik degerlere yuksek duzeyde katilim gostermistir. Ogretmenlerin demokratik degerlere iliskin gorusleri cinsiyet ve bransa gore degismezken, egitim durumu, yas ve kideme gore degismektedir. Ayrica ogretmenlerinin demokratik degerlere iliskin gorusleri ile sinif yonetimi tarzlari arasinda dusuk duzeyde anlamli iliskiler vardir.
Aftereffects of Self-Control on Positive Emotional Reactivity

According to the process model of ego depletion, exercising self-control causes shifts in motivation and attention that may increase positive emotional reactivity. In an initial study and a preregistered replication, participants exercised self-control (or not) on a writing task before reporting their emotional responses to positive, negative, and neutral images. In Study 1 (N = 256), we found that exercising (vs. not exercising) self-control increased positive emotional responses to positive images among more extroverted individuals. In Study 2 (N = 301), we found that exercising self-control increased positive reactivity independent of extroversion. These findings support the process model of ego depletion and suggest that exercising self-control may influence responding that does not entail self-control (i.e., positive emotional reactivity)—an outcome that is not anticipated by the limited resource model of self-control.
Activity Tracking Affordances: Identification and Instrument Development

Activity tracking apps -such as Fitbit or Nike+ Running- are positioned to enhance people's motivation towards physical activity and healthy behavior. Though various ‘motivational’ features are incorporated, the effectiveness of these apps is often mixed and raises concerns about the ‘one-size-fits-all‘ applicability. To get a better understanding about the nature of using activity tracking apps, this paper employs the lens of affordances and identifies eight particular salient affordances in activity tracking: Self-Monitoring, Performance Analysis, Exercise Guidance, Rewards, Social Comparison, Watching Others, Social Recognition, and Self-Presentation. Moreover, this study develops a corresponding measurement instrument evaluated using q-sort methodology. Avenues for future research are highlighted involving the set of affordances and their instruments and practical implications are given.
Scalable-Effort ConvNets for Multilevel Classification

This work introduces the concept of scalable-effort Convolutional Neural Networks (ConvNets), an effort-accuracy scalable model for classification of data at multilevel abstraction. Scalable-effort ConvNets are able to adapt at run-time to the complexity of the classification problem, i.e. the level of abstraction defined by the application (or context), and reach a given classification accuracy with minimal computational effort. The mechanism is implemented using a single-weight scalable-precision model rather than an ensemble of quantized weight models; this makes the proposed strategy highly flexible and particularly suited for embedded architectures with limited resource availability. The paper describes (i) a hardware/software vertical implementation of scalable-precision multiply&accumulate arithmetic, (ii) an accuracy-constrained heuristic that delivers near-optimal layer-by-layer precision mapping at a predefined level of abstraction. It also reports the validation for three state-of-the-art nets, i.e. AlexNet, SqueezeNet and MobileNet, trained and tested with ImageNet. Collected results show scalable-effort ConvNets guarantee flexibility and substantial savings: 47.07% computational effort reduction at minimum accuracy, or 30.6% accuracy improvement at maximum effort w.r. t. standard flat ConvNets (average over the three benchmarks for high-level classification).