Miracle-dz/UniFAR-FTUs huggingface dataset:
Nearshore bathymetry estimation from UAV videos: on the influence of camera calibration

Measuring the nearshore bathymetry is critical in coastal management and morphodynamic studies. The recent advent of Unmanned Aerial Vehicles (UAVs), in combination with coastal video monitoring techniques, allows an alternative and low cost evaluation of the nearshore bathymetry. This work introduces a new methodology to obtain such bathymetries, and compares the results to echo-sounder ground truth data. The goal is to gain a better understanding on the influence of the camera calibration and stabilization on the inferred bathymetry. The results show how the proposed methodology allows accurate evaluations of the bathymetry, with overall root mean square errors in the order of 40 cm. It is shown that the intrinsic calibration of the camera, related to the lens distortion, is the most critical aspect. Here, the intrinsic calibration obtained directly during the flight yields the best results.
A Bayesian Model for Experiment Choice in Synthetic Biology

We are working on an experiment planning system for synthetic biology. As part of this effort, we wish to identify the most informative experiments to perform, based on our current state of knowledge about some de-sign or designs. To do so, we introduce a hierarchical Bayesian model of genetic circuits, assess its predictive adequacy, and explain how it is used to score candidate experiments. We conclude with a discussion of future research directions, including model extensions, improvements to the inference methods, and more ambitious uses of the predictive model.
Adaptive Gradient Methods, Normalization, and Weight Decay

This lecture considers three staples of modern deep learning systems: adaptive gradient methods (such as RMSprop and Adam), normalization layers (such as batch norm, weight norm, and layer norm), and weight decay. While the three parts of the lecture are somewhat independent, there are some threads that tie them together. All three components create surprising interactions between all the various knobs we have to tune to get a deep learning system to work. And, for the most part, one can reason pretty well about the behavior of these components using only elementary arithmetic; no fancy math required. The second component, normalization layers, is a particularly interesting case to consider because it’s often served as the canonical example of a deep learning architecture we don’t understand. To begin with, consider Rahimi (2017)’s NeurIPS 2017 Test of Time talk, which was remarkably well-delivered and entertaining, and launched a conversation about the state of scientific rigor in our field. He characterized the state of deep learning research as “alchemy,” in the sense of having discovered a wide array of pratical and useful tricks, but lacking a foundational understanding of the principles (analogously to not having an atomic theory). He cited BN, and in particular its justification in terms of ICS, as a specific example of this (emphasis mine):
Risk Behaviors among Young People: The Role of Developmental Assets

Youth risk behaviors have both personal and societal consequences and can also have grave economic cost if not addressed effectively. Positive Youth Development (PYD) as a theoretical framework proposes that facilitating developmental assets (i.e., internal and external assets, such as positive values and social support) among young people would lead to positive outcomes as well as a possible reduction in negative outcomes. The empirical evidence supporting these assertions mostly come from studies involving American samples. In the present study, we examine whether the experience of more developmental assets is associated with less engagement in three risk behaviors: drunkenness, violence and crime among 591 Norwegian students (55% girls), mean age 16.70 (SD = .90). Our results indicate that while several significant correlations were observed between developmental assets and risk behaviors, only two internal assets: positive values and social competence, and two external assets: support and boundaries and expectations were significant predictors of Resumen Las conductas de riesgo en los jóvenes tienen consecuencias tanto personales como sociales y también pueden tener un grave coste económico si no se abordan de manera eficaz. El marco teórico del Desarrollo Positivo Juvenil (DPJ) propone que fomentar los activos del desarrollo (internos y externos, como pueden ser los valores positivos y el apoyo social) entre los jóvenes conduciría a resultados positivos, así como a una posible reducción de los resultados negativos. La evidencia empírica que respalda estas afirmaciones proviene principalmente de estudios con muestras estadounidenses. En el presente estudio, examinamos si la presencia de más activos de desarrollo se asocia con una menor participación en tres conductas de riesgo: embriaguez, violencia y delincuencia, entre 591 estudiantes noruegos (55% niñas), con una edad promedio de 16,70 (DT = 0,90). Nuestros resultados indicaron que si bien se observaron varias correlaciones significativas entre los activos del desarrollo y las conductas de riesgo, sólo dos activos internos (valores positivos y competencia Risk Behaviors among Young People: The Role of Developmental Assets
Drug Target Prediction Using Graph Representation Learning via Substructures Contrast

The prediction of drug–target interactions is always a key task in the field of drug redirection. However, traditional methods of predicting drug–target interactions are either mediocre or rely heavily on data stacking. In this work, we merged heterogeneous graph information and obtained effective node information and substructure information based on mutual information in graph embeddings. We then learned high quality representations for downstream tasks, and proposed an end–to–end auto–encoder model to complete the task of link prediction. Experimental results show that our method outperforms several state–of–art models. The model can achieve the area under the receiver operating characteristics (AUROC) curve of 0.959 and area under the precise recall curve (AUPR) of 0.848. We found that the mutual information between the substructure and graph–level representations contributes most to the mutual information index in a relatively sparse network. And the mutual information between the node–level and graph–level representations contributes most in a relatively dense network.
Functionalization of polylactic acid through direct melt polycondensation in the presence of tricarboxylic acid

The goal of the article was to describe the preparation of carboxyl-functionalized polylactic acid (PLA) through the method of direct melt copolycondensation of lactic and citric acid (CA). In addition, detailed study of copolycondensation process, its limitations and investigation of the reaction products properties are another issue this article deals with. The effect of tricarboxylic CA on the resulting properties of the functionalized lactic acid (LA) polycondesates was studied in a wide range of LA/CA molar ratios. The influence of CA on molecular weight, thermal and physicochemical properties, and chemical structure of the products was investigated, using viscometric measurements of the polymer solutions, gel permeation chromatography, 1H nuclear magnetic resonance spectroscopy, differential scanning calorimetry, acidity number determination, and Fourier-transform infrared and ultraviolet spectroscopy. The results show the significant effect of CA on the structure and physicochemical properties as well as high efficiency of functionalization. Furthermore, a branched structure was detected at low CA concentrations, while higher CA content leads to termination of the polycondensates chains by citryl units and a reduction in the molecular weight. Here, insights on the characterization methods of PLA-based materials are given by various experimental techniques. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011
Aligning the design of intermediary organisations with the ecosystem

ABSTRACT Intermediary organisations such as technology transfer organisations (TTOs) are an important mechanism of open ecosystem governance, as they support how ecosystem participants search for knowledge. While scholars have identified TTO activities to support knowledge search, little is known about how these activities relate to the structural dimensions of TTOs or ecosystem-level factors. We propose that ecosystem search scope and problem complexity are key ecosystem-level factors that influence how TTOs support knowledge search. We further argue that coupling, specialisation, centralisation, and formalisation are the key structural dimensions of TTOs. We combine these arguments to develop TTO designs that detail the interplay of the structural dimensions and activities of a TTO given varying ecosystem-level factors. Our paper contributes to research on the open governance of ecosystems, ecosystem structures, and the ecosystem structure–intermediary organisations relation.
Being a medical pathology expert in the COVID-19 pandemic

The aim of the study is to reveal the risk of COVID-19 among pathologists and to examine their views, concerns along with measures to be taken in dealing with COVID-19. The research was carried out in Turkey with online survey method, on 176 participants. According to the findings of the study, participants who served oneon-one to a COVID-19 patient was 47.16%. Number of participants assigned in the polyclinic and clinical processes of coronavirus patients; 63.6%. 24 participant (13.6%) stated that their frozen cases decreased. Substantially, there was a use of protective equipment (88.6%). Cytological specimens were seen to continue 93.7%. There was a competence of 88.6% in terms of protective equipment. It was determined that the anxiety levels of the participants did not change according to age groups, according to the hospital type, working pandemic outpatient clinic and gender variables (p> 0.05). As a result, medical pathologists actively continue their routine services during the pandemic process and also support their other colleagues by working actively in the COVID-19 outpatient clinic. As always, solidarity with our colleagues continues.
Moving Robot Accountability to the Cloud: Effects in Knowledge Representation Processes

—Future legal requirements will push for creating cognitive architectures and decision-making frameworks capable of offering human-interpretable information about their actions. Fulﬁlling these requirements will require a high computational cost. Thus, these systems have been moved from local scenarios to cloud environments where it is possible to exploit High Performance Computing features, but uploading these processes to the cloud would also impose unacceptable latencies for some robotics but suitable for auditing. This paper presents an empirical evaluation of knowledge manipulation and processing based on PDDL (Planning Domain Description Language) in four scenarios: local native, local container, mixed and cloud. The knowledge about the robot itself and its environment is a cornerstone in any cognitive architecture no matter where is the scenario. The knowledge representation enables in turn reasoning and the implementation of regular cognitive functions such as memory, attention, information processing, and reasoning on cognitive architecture. In this initial iteration, we can see the high-performance impact of partially moving knowledge manipulation to the cloud, particularly in mixed local/cloud scenarios.
Transactivation of the grp 78 Promoter by Malfolded Proteins , Glycosylation Block , and Calcium lonophore Is Mediated through a Proximal Region Containing a CCAAT Motif Which Interacts with CTF / NFI

The 78-kDa glucose-regulated protein (GRP78) is a major endoplasmic reticulum (ER) protein that can form stable associations with a variety of proteins retained in the ER because of underglycosylation or other conformational changes. In this study, we provide evidence at the transcriptional level that a conformationally abnormal protein, an altered herpes simplex virus type 1 envelope protein that is retained in the ER of a mammalian cell line, transactivates the grp78 promoter. In contrast, the normal viral envelope glycoprotein does not elevate grp78 promoter activity. Using a series of 5' deletions, linker-scanning, and internal deletion mutations spanning a 100-bp region from -179 to -80, we correlate the cis-acting regulatory elements mediating the activation of grp78 by malfolded proteins, glycosylation block, and the calcium ionophore A23187. We show that they all act through the same control elements, suggesting that they share a common signal. We report here that the highly conserved grp element, while important for basal level and induced grp78 expression, is functionally redundant. The single most important element, by linker-scanning analysis, is a 10-bp region that contains a CCAAT motif. It alone is not sufficient for promoter activity, but a 40-bp region (-129 to -90) that contains this motif is essential for mediating basal level and stress inducibility of the grp78 promoter. We show that the transcription factor CTF/NF-I is able to transactivate the grp78 promoter through interaction with this CCAAT motif.
Collaborative Translation in the Digital Age

This study investigates the learning experiences of student translators participating in collaborative translation with and without the use of translation technology through collaborative translation teaching and practical exercises. The effectiveness and efficiency of two types of collaboration (face-to-face and virtual) are surveyed in terms of students’ cooperation and communication, the effort they invest into translation exercises, the importance they attach to these exercises, and the effectiveness of translation technology in collaborative translation. We use questionnaires to obtain a comprehensive overview of the translation process of and feedback on collaborative translation from student translators. Face-to-face and virtual collaborative translations are performed in English–Chinese translation courses to compare the learning effectiveness of virtual and face-to-face collaboration, enhance our understanding of how collaborative translation facilitates reciprocity, and offer recommendations to enhance translation teaching. This study develops collaborative translation teaching methods and designs collaborative translation curricula. Exploring the core criteria of collaboration, effectiveness, and efficiency through the reports of student translators collaborating face-to-face and online will contribute to the establishment of a collaborative translation framework.
A study of data augmentation for increased ASR robustness against packet losses

Nowadays a large amount of companies record conversations, calls, sales or even meetings, in many cases to comply with the current legislation. Apart from the legal need, these recordings constitute an invaluable source of information about clients, call center operators, marketing campaigns, markets trends, etc. The current state of the art in Automatic Speech Recognition (ASR) allows to exploit this information in a very efﬁcient way. However, the recordings at these repositories tend to present very low quality because the audio is typically recorded in a highly compressed way to save storing space. Besides, since it is very common to use Voice over IP (VoIP) in these systems, it is usual to have short interruptions in the speech signal due to packet losses. Both effects, and particularly the last one, have an impact in ASR performance. This paper presents an extensive study of the inﬂuence of these effects and the effectiveness of different data augmentation strategies to increase the robustness of ASR systems in these circumstances, and in particular when packet losses degrade the speech signal.
WHICH MOTIVATIONS BOOST IDEA QUALITY? EXPLOR-ING THE IMPACT OF CUSTOMERS’ MOTIVES FOR PAR-TICIPATING IN VIRTUAL IDEAS COMMUNITIES ON IDE-ATION OUTCOME

For practice it is important to leverage ideas of high quality from Virtual Ideas Communities (VIC). Therefore, firms that run such VIC have a strong interest in understanding which factors impact customers’ ideation outcome. This research investigates the influence of customers’ motivation factors for developing ideas on the quality of their ideas. So far, empirical studies that provide evidence on this association are neglected, although these insights would be highly beneficial for firms in their role as operator of VIC. Knowing the factors that have a positive influence will provide valuable insights into how to design effective incentive strategies that attract corresponding customer motivations and, in turn, will lead to higher levels of idea quality. In this research-in-progress paper we build a theoretical model explaining which of customers‘ motives for developing ideas have a positive impact on their ideation outcome.
ILMPQ : An Intra-Layer Multi-Precision Deep Neural Network Quantization framework for FPGA

This work targets the commonly used FPGA (field-programmable gate array) devices as the hardware platform for DNN edge computing. We focus on DNN quantization as the main model compression technique. The novelty of this work is: We use a quantization method that supports multiple precisions along the intra-layer dimension, while the existing quantization methods apply multi-precision quantization along the inter-layer dimension. The intra-layer multi-precision method can uniform the hardware configurations for different layers to reduce computation overhead and at the same time preserve the model accuracy as the inter-layer approach. Our proposed ILMPQ DNN quantization framework achieves 70.73 Top1 accuracy in ResNet-18 on the ImageNet dataset. We also validate the proposed MSP framework on two FPGA devices i.e., Xilinx XC7Z020 and XC7Z045. We achieve 3.65x speedup in end-to-end inference time on the ImageNet, compared with the fixed-point quantization method.
Comparisons of Physical Properties of Intercalated and Exfoliated Clay/Epoxy Nanocomposites

Two types of intercalated and exfoliated silicate platelets were allowed to disperse in phenol-cured epoxy matrixes. The different dispersing forms of these silicate platelets in the composites may alter their hardness, transparency, thermal stability, and coefficient of thermal expansion (CTE). In particular, the presence of silicate platelets in the epoxy substantially enhances the hardness of the pristine epoxy from 2 to 6 H by loading only 0.5 wt % of the exfoliated platelets but only to 4 H hardness by loading the intercalated form (pristine 58 A d spacing). Analyses by X-ray diffraction, transmission electron microscopy (TEM), differential scanning calorimetry, thermal mechanics, and thermal gravimetry were performed to characterize these silicate-added epoxies. Physical properties including CTE and Tg were correlated with the silicate platelet dispersion in a matrix revealed by the TEM observations.
Do Cyborgs dream of Electric Limbs? Experiential Factors in Human-Computer Integration Design and Evaluation

While many systems have successfully demonstrated functional integration of humans and technology, little attention has been paid to how technologies might experientially integrate to feel as part of humans. Our aim is to shed light on the importance of experiential integration and provide researchers with a scientifically driven foundation for future designs and investigations. The workshop will consist of hands-on experiments with novel body-illusions, discussions on experiential integration, and instructor-guided sessions on psychological concepts related to the design and evaluation of experiential integration.
Social Support is Positively Correlated With College Adjustment in First-Year Students

When first-year students enter university, they experience many changes and challenges that require adjustment and adaptation. Previous studies have suggested that social support is one factor related to college adjustment. However, scientific support for the relationship between these variables in Indonesia is limited. This study aimed to investigate the relationship between social support and college adjustment in the Indonesian university context. We used the adapted version of the Student Adjustment to College Questionnaire (SACQ) and the Multidimensional Scale of Perceived Social Support (MSPSS) to measure college adjustment and social support in 281 first-year students enrolled in Universitas Indonesia. The social supports measured in this study include peer support and family support. Our analysis confirmed that social support was positively correlated with college adjustment (r = 0.468, p < 0.001, one-tailed). The results suggest that social networks, including family and peers, are important to students during their transition period from high school to higher education.
Test Data Compression Based on Variable-to-Variable Huffman Encoding With Codeword Reusability

—A new statistical test data compression method that is suitable for IP cores of an unknown structure with multiple scan chains is proposed in this paper. Huffman, which is a well-known ﬁxed-to-variable code, is used in this paper as a variable-to-variable code. The precomputed test set of a core is partitioned into variable-length blocks, which are, then, compressed by an efﬁcient Huffman-based encoding procedure with a limited number of codewords. To increase the compression ratio, the same codeword can be reused for encoding compatible blocks of different sizes. Further compression improvements can be achieved by using two very simple test set transformations. A simple and low-overhead decompression architecture is also proposed.
MRI studies of flow and dislocation of model NAPL in saturated and unsaturated sediments

In this article, we explore the possibilities of studying transport phenomena that involve non‐aqueous phase liquids (NAPL) by means of magnetic resonance imaging (MRI) with a paramagnetic contrast agent. We studied n‐octanol as a model NAPL, especially in alcohol flooding in a water‐saturated sediment, and flood‐drainage‐cycles in a temporally unsaturated sediment column. While the ‘natural’ relaxation time contrast between water and n‐octanol often allows a distinction of the two liquids in a quartz‐sand sediment, the use of Mn2+‐ions dissolved in the water phase as a ‘biphasic’ contrast agent allows much better discrimination between the different liquid phases and also considerably faster imaging. Using a 3D FLASH sequence, a NAPL‐saturated region can be visualized against a background of water‐saturated sediment in 11 s with a resolution of 1.9 × 1.9 × 3.2 mm3.
PSCC-Net: Progressive Spatio-Channel Correlation Network for Image Manipulation Detection and Localization

To defend against manipulation of image content, such as splicing, copy-move, and removal, we develop a Progressive Spatio-Channel Correlation Network (PSCC-Net) to detect and localize image manipulations. PSCC-Net processes the image in a two-path procedure: a top-down path that extracts local and global features and a bottom-up path that detects whether the input image is manipulated, and estimates its manipulation masks at multiple scales, where each mask is conditioned on the previous one. Different from the conventional encoder-decoder and no-pooling structures, PSCC-Net leverages features at different scales with dense cross-connections to produce manipulation masks in a coarse-to-fine fashion. Moreover, a Spatio-Channel Correlation Module (SCCM) captures both spatial and channel-wise correlations in the bottom-up path, which endows features with holistic cues, enabling the network to cope with a wide range of manipulation attacks. Thanks to the light-weight backbone and progressive mechanism, PSCC-Net can process $1,080\text{P}$ images at 50+FPS. Extensive experiments demonstrate the superiority of PSCC-Net over the state-of-the-art methods on both detection and localization. Codes and models are available at https://github.com/proteus1991/PSCC-Net.