Miracle-dz/UniFAR-FTUs huggingface dataset:
Supplementary Materials: Implicit Class-Conditioned Domain Alignment for Unsupervised Domain Adaptation

For simplicity, we drop the multiple 1 mb in the following analysis as it does not affect the result of optimization. Theorem 2 (The decomposition of d̂H∆H(BS ,BT )). Let H be a hypothesis space and Y be the label space of the classification task where BS , BT are minibatches drawn from US , UT , respectively, and YS , YT are the label set of BS , BT . We define three disjoint sets on the label space: the shared labels YC := YS ∩ YT , and the domain-specific labels YS := YS − YC , and YT := YT − YC . We also define the following disjoint sets on the input space where B S := {x ∈ BS | y ∈ YC}, B S := {x ∈ BS | y / ∈ YC}, B T := {x ∈ BT | y ∈ YC}, B T := {x ∈ BT | y / ∈ YC}. The empirical d̂H∆H(BS ,BT ) divergence can be decomposed into class aligned divergence and class-misaligned divergence:
THE RELATIONSHIP BETWEEN CRUDE OIL PRICES, EUR/USD EXCHANGE RATE AND GOLD PRICES

This study aims to analyze and measure the nature of the relationship between crude oil price, EUR/USD exchange rate, and Gold price by using monthly data from January 1999 to October 2019. The result of data analysis using Auto-Regressive Distributed Lag (ARDL) shows that there exists a co-integration relationship between the price of crude oil in U.S. dollars per barrel (C.O.), and the interpreting variables in this study, represented in the Euro Dollar Exchange Rate (E.R.) and the Gold Price in U.S. dollars per ounce (G.P.). The relationship that happened only in a short-term one. Granger causality test result shows one-way causal relationship from the Euro/ Dollar towards oil prices; that is, the variation in the exchange rate causes changes in oil prices. Also a unidirectional causal relationship has been found between the gold price and crude oil price. The relationship between the study variables is positive.
Robot Pets for Everyone: The Untapped Potential for Domestic Social Robots

— While research has demonstrated the potential for social robots as companions in care homes, for targeted specialized therapies (e.g., children on the autism spectrum) or uses in clinical practice (e.g., to increase comfort or reduce pain), social robotic pets for the general public have not yet even been minimally successful. Despite ongoing laboratory success of social robots for shaping mood, building rapport and creating empathy, this has not translated to actual robot pets supporting people in their homes. In this paper, we highlight this untapped potential for domestic robots to discuss some of the underlying issues behind acceptance, describe a simple agenda to design novel domestic robots, and present our initial plans to understand social robot acceptance and promote them to be domestic companions as pets.
Annotating discussions centred on an unseen artefact using an extended version of the ICAP framework

The annotation guidelines presented in this document were developed to inform the labelling of student discussion forum messages using an extended version of the ICAP framework (Chi and Wylie, 2014), particularly in the context of an artefact, such as a video presentation, that is not available to the annotators. The extended ICAP framework has been used to label messages from MOOC discussion forums and annotated textbooks (Wang et al., 2016b; Yogev et al., 2018). The guidelines in that earlier work were adapted here to allow the framework labels to be applied to a discussion where each message thread is a response to a video presentation that is not available to the annotators (Farrow et al., 2020). The ICAP framework defines cognitive engagement based on observable behaviours. It looks at individual learning activities and how they relate to students’ cognitive engagement with the learning materials. Four modes of cognitive engagement are identified, and the framework predicts that higher modes will be correlated with greater learning gains. In descending order, these modes are Interactive, Constructive, Active, and Passive. Each mode represents a qualitatively different kind of growth in knowledge, not simply a bigger or smaller change. Nevertheless, each mode subsumes the modes below it (Figure 1). Off-task behaviours do not constitute any sort of cognitive engagement. The lowest mode in the framework, Passive engagement, corresponds to the least taxing on-task activities; for example, watching a video or reading a discussion forum post. Active engagement covers activities that demand the student’s attention, such as taking verbatim notes or reworking previous content. To qualify as Constructive engagement, novel output must be generated; for example, summary notes that link together concepts, or a list of relevant external resources. Interactive engagement requires interaction with a partner, and both partners must be engaged constructively. Off-task behaviours do not constitute cognitive engagement at all. Prior work has demonstrated the feasibility of applying a modified version of the ICAP framework to MOOC discussion forums (Wang et al., 2016b) and to student comments on an annotated electronic course text (Yogev et al., 2018). In common with Yogev et al. (2018), this work looks at the case where the discussion centres around a pre-existing artefact. In the earlier work, that artefact was an electronic course text. Participants highlighted sections of
MINDMIX: Mapping brain activity to congruent audio mixing features

Brain-computer interfacing (BCI) offers novel methods to facilitate participation in audio engineering, providing access for individuals who might otherwise be unable to take part (either due to lack of training, or physical disability). This paper describes the development of a BCI system for conscious, or ‘active’, control of parameters on an audio mixer by generation of synchronous MIDI Machine Control messages. The mapping between neurophysiological cues and audio parameter must be intuitive for a neophyte audience (i.e., one without prior training or the physical skills developed by professional audio engineers when working with tactile interfaces). The prototype is dubbed MINDMIX (a portmanteau of ‘mind’ and ‘mixer’), combining discrete and many-to-many mappings of audio mixer parameters and BCI control signals measured via Electronecephalograph (EEG). In future, specific evaluation of discrete mappings would be useful for iterative system design.
Neural-network Method for Determining Text Author’s Sentiment to an Aspect Specified by the Named Entity

This study presents the approach to aspect-based sentiment analysis where a named entity of a certain category is considered as an aspect. Such task formulation is a novelty and opens up the opportunity to determine writers’ attitudes to organizations and people considered in texts. This task required a dataset of Russian-language sentences where sentiment with respect to certain named entities would be labeled, which we collected using a crowdsourcing platform. Sentiment determination is based on a deep neural network with attention mechanism and ELMo language model for word vector representation. The proposed model is validated on available data on a similar task. The resulting performance (by the f1-micro metric) on the collected dataset is 0.72, which is the new state of the art for the Russian language.
Robust Unsupervised Cleaning of Underwater Bathymetric Point Cloud Data

This paper presents a novel unified one-stage unsupervised learning framework for point cloud cleaning of noisy partial data from underwater side-scan sonars. By combining a swath-based point cloud tensor representation, an adaptive multi-scale feature encoder, and a generative Bayesian framework, the proposed method provides robust sonar point cloud denoising, completion, and outlier removal simultaneously. The condensed swath-based tensor representation preserves the point cloud associated with the underlying three-dimensional geometry by utilizing spatial and temporal correlation of sonar data. The adaptive multi-scale feature encoder identifies noisy partial tensor data without handcrafted feature labeling by utilizing CANDECOMP/PARAFAC tensor factorization. Each local embedded outlier feature under various scales is aggregated into a global context by a generative Bayesian framework. The model is automatically inferred by a variational Bayesian, without parameter tuning and model pre-training. Extensive experiments on large scale synthetic and real data demonstrate robustness against environmental perturbation. The proposed algorithm compares favourably with existing methods.
Cross-dataset Color Constancy Revisited Using Sensor-to-Sensor Transfer

Color constancy is required for camera captured images and therefore all digital camera imaging pipelines include an Auto White Balance (AWB) algorithm. An intrinsic problem of AWB is that it is sensor speciﬁc and therefore developers need to repeatedly collect new in-house datasets to adjust their methods for new sensors. In literature, the best learning-based methods achieve state-of-the-art performance with clear margin on all available datasets, but performance signiﬁcantly degrades in cross-dataset experiments due to the aforementioned reason. In this work, we introduce a sensor-to-sensor transfer model that can be used to map datasets with known cameras to any other known camera. The only requirement is that spectral characterizations of the camera models are available. In our experiments, we demonstrate improvements in cross-dataset settings using the proposed sensor-to-sensor transfer model. In addition, for the ﬁrst time we are able to analyze the characteristics of existing datasets in the common standard observer space and our analysis reveals that certain datasets contain images which are not suitable for color constancy. We introduce a uniﬁed cross-dataset color constancy benchmark dataset, compare two state-of-the-art learning-based AWB methods and show superior performance of the proposed sensor-to-sensor model.
Competitive Procurement with Ex Post Moral Hazard1

Unlike standard auctions, we show that competitive procurement may optimally limit competition or use ineffi cient allocation rules that award the project to a less effi cient firm with positive probability. Procurement projects often involve ex post moral hazard after the competitive process is over. A procurement mechanism must combine an incentive scheme with the auction to guard against firms bidding low to win the contract and then cutting back on effort. While competition helps reduce the rent of effi cient firms, it exacerbates the problem due to moral hazard. If allocative effi ciency is a requirement, limiting the number of participants may be optimal. Alternatively, the same incentives can be optimally provided using ineffi cient allocation rules. 1We thank Pat Bajari, Dirk Bergemann, Roberto Burguet, Yeon-Koo Che, Hae Yun Choung, Jacques Crémer, Dong-Jae Eun, Andrew Foster, Marina Halac, Do-Shin Jeon, George Mailath, Claudio Mezzetti, Preston McAfee, Alessandro Pavan, Patrick Rey, David Sappington, Guofu Tan, Xu Tan, Jean Tirole, Richard Van Weelden and John Wooders for many helpful comments. The paper benefitted greatly from detailed comments by Mark Armstrong and two anonymous referees. Chakraborty acknolowdges financial support from Singapore MOE research grants numbers R-122-000-254-115 and R-122-000-283-115 and generous hospitality from Department of Economics, University of Washington.
Indicative conditionals and learning from testimony

Our beliefs change with learning, and much of what we learn comes from the testimony of other people. How much our beliefs change may depend on how many people are the sources of a given piece of information, and how reliable their expertise makes them. It is not clear, however, what exactly the effects of reliability or number of speakers will be when the testimony has the form of an indicative conditional. Here, we test the hypothesis that learning a conditional amounts to increasing the degree to which the antecedent of that conditional is relevant for its consequent. Furthermore, we investigate whether this is affected by number of speakers and by their expertise.
Anchor Calibration for Real-Time-Measurement Localization Systems

This article investigates the effect of additional calibration modules (CMs) in a 3-D real-time localization system during the calibration of the anchor position. A quick calibration is desirable for new anchors that are positionally undetermined in the working coordinate system. Three localization methods were tested for the anchor calibration: multidimensional scaling, semidefinite programming, and iterative trilateration. First, the accuracy of the anchor localization was studied by simulating a change in the number of additional CMs and their positions. Second, tests on a real system with ultrawideband modules were performed to validate the improvements in the anchor calibration when using the additional CMs. The experimental results revealed an improvement in the anchor localization for all three methods, where the average positional error was improved by 0.01 m in the first scenario and 0.30 m in the second scenario. The MDS method had the best absolute performance, with an average positional error that was as much as two times less in comparison with the other two methods. This investigation demonstrates that the positional error can be successfully reduced by using additional CMs. The calibration of anchor positions in the working coordinate system using additional CMs resulted in a 3-D error of less than 0.32 m.
Redshifting of cosmological black bodies in BSBM varying-alpha theories

We analyse the behaviour of black-body radiation in theories of electromagnetism which allow the electron charge and the fine structure constant to vary in space and time. We show that such theories can be expressed as relativistic generalizations of a conventional dielectric. By making the appropriate definition of the vector potential and associated gauge transformations, we can identify the equivalent of the electric and displacement fields, E and D, as well as the magnetic B and H fields. We study the impact of such dielectrics on the propagation of light in the so-called “BSBM” theory. We examine the form of simple cosmological solutions and conclude that no changes are created to the standard cosmological evolution of the temperature and energy-density of black-body radiation. Nonetheless the matter evolution changes and the behaviour of the entropy per baryon is modified, and the ratios of different dark matter components may be changed too.
Technological Capability: Does it Matter for Bahrain?

The study aims at determining the impact of the technological capability on the economic growth of Kingdom of Bahrain during the period (2005-2014). The study methodology is based on the econometric analytical approach to estimate the parameters’ values and the trends of the economic relationship between the study variables by employing the cointegration and Granger causality techniques. The study found that there is a positive long run relationship between the technological capability and economic growth. Granger causality test reveals that the technological capability Granger causes the economic growth in Bahrain. This means the technological capability could accelerate the economic growth in the long run. The study result is consistent with the new growth theory and various empirical studies in different countries. The study recommends that government and policy makers in Bahrain should pay careful attention to all of the factors that provide incentives for technological creation such as R&D, the education system, entrepreneurship and the tolerance for diversity, macroeconomic expectations and openness to trade.
The functional role of mitochondria in neural progenitor cells

Neurodevelopment is a complex process that requires the precise spatiotemporal control of cellular differentiation. As cells differentiate, they undergo metabolic changes that make them increasingly reliant on their mitochondria for energy production. Beyond playing a central role in the bioenergetic support of newborn neurons, functional changes in mitochondria regulate the processes of cellular differentiation. Importantly, mitochondrial function extends beyond energy production. Mitochondria in neural stem cells play an essential role in both producing intermediates for biosynthesis and regulating calcium levels. In this thesis, I review the functional role of mitochondria in stem cell fate decisions, differentiation, and proliferation during neurodevelopment. Due to the challenges of directly measuring mitochondrial activity ​in vivo​ , I outline how genetically encoded fluorescent probes can be used to indirectly evaluate mitochondrial function. Beyond my review of this field, I engineered three genetically encoded fluorescent probes that can be used to measure both cytosolic and mitochondrial calcium activity in radial glial cells in ​Xenopus laevis. ​ Preliminary imaging indicates the promising potential for these plasmids in the measurement of calcium activity and, by proxy, mitochondrial activity in differentiating stem cells.
How Do FDIs Affect Performance at Home?: Activity-level Analysis for Japanese Electronics Firms

This paper investigates the impacts of FDIs on home productivity by using firms’ activity-level data for Japanese electronics firms, instead of firm-level data in past literature. The Vertical FDI (VFDI) firms’ change in their main activity at home between pre-investing and post-investing makes the comparison of productivity between them qualitatively difficult because such a change implies the change of firms’ home production function per se. The use of activity-level data enables us to avoid influence of the activity change in the evaluation of VFDI’s impacts. Our empirical results are consistent with theoretical predictions: Horizontal FDI of an activity does not necessarily have positive significant impacts on productivity in domestic activities same with the invested activity. On the other hand, the VFDI of an activity enhances the productivity significantly in domestic activities with input-output relationship with the invested activity.
Approximate Logic Synthesis: A Survey

Approximate computing is an emerging paradigm that, by relaxing the requirement for full accuracy, offers benefits in terms of design area and power consumption. This paradigm is particularly attractive in applications where the underlying computation has inherent resilience to small errors. Such applications are abundant in many domains, including machine learning, computer vision, and signal processing. In circuit design, a major challenge is the capability to synthesize the approximate circuits automatically without manually relying on the expertise of designers. In this work, we review methods devised to synthesize approximate circuits, given their exact functionality and an approximability threshold. We summarize strategies for evaluating the error that circuit simplification can induce on the output, which guides synthesis techniques in choosing the circuit transformations that lead to the largest benefit for a given amount of induced error. We then review circuit simplification methods that operate at the gate or Boolean level, including those that leverage classical Boolean synthesis techniques to realize the approximations. We also summarize strategies that take high-level descriptions, such as C or behavioral Verilog, and synthesize approximate circuits from these descriptions.
Contracting Institutions and Product Quality 1

For many goods, quality improvements involve the use of more sophisticated, higher quality inputs. The production of these sophisticated inputs requires greater collaboration between suppliers and final good producers, with suppliers developing relationship-specific inputs, and final good producers customizing their production processes to incorporate them. In countries with poor legal institutions, the relationship-specific investments needed to achieve strong collaboration, and by extension more sophisticated inputs and higher quality outputs, will arguably be hard to achieve. As the incomplete contracts literature suggests, doubts over contract enforcement will render the return on relationship-specific investments less certain, rendering both suppliers and final good producers less willing to undertake the customization necessary to improve quality. Employing a difference-in-difference methodology on highly disaggregated US import data for 1995, this paper studies the impact of legal institutions on product quality. It finds that poor contracting institutions substantially impede a country’s ability to produce high quality final goods: in industries where the potential use of customizable inputs is extensive, countries with weaker contract enforcement regimes produce lower quality final goods. JEL classification: F14; O17; D23; O11
Doxorubicin Induced Histomorphometric Changes in the Kidney of Albino Rats and Protective Role of Nigella Sativa

Objective: Doxorubicin is presently a leading antineoplastic drug with promising efficacy. This study was designed to investigate the histological effects of doxorubicin toxicity on rat kidneys and how much protection is provided by Nigella Sativa. Materials & Methods: A randomized controlled trial conducted on thirty adult male wistar rats divided randomly into three equal groups. Group A served as a control. Group B was injected with weekly intraperitoneal injections of doxorubicin at a dose of 3mg/kg b.w. Group C rats received doxorubicin along with nigella sativa at a dose of 1000mg/kg b.w. orally daily. At the end of these interventions, animals were sacrificed and kidneys were removed for the purpose of histological staining. Renal glomerular and tubules related histopathological parameters were assessed qualitatively as mild, moderate & severe. Renal glomerular diameter was digitally measured by microscope. Ethical approval was taken from Ethical Committee, Jinnah Postgraduate Medical Centre (JPMC), Karachi. All the parameters were statistically analyzed. Results: Group B rats’ renal tissue was adversely affected by the drug showing marked necrosis of tubules and the glomeruli along with interstitial cells’ infiltration. Glomerular diameter was also significantly decreased in group B as compared to group A. These histological features in group C rats’ renal tissue were milder and glomerular diameter was close to that of group A. Conclusion: According to our study doxorubicin treatment proved noxious for the renal tissue, both tubules and glomeruli, while nigella sativa significantly competed against these pathological alterations.
The Relationship Between Tendency to Substance Abuse and Resilience and Academic Procrastination in Secondary School Students

* Corresponding Author: Saeed Toulabi, PhD. Address: Department of Educational Psychology, Faculty of psychology, Kharazmi University, Tehran, Iran. Tel: +98 (912) 5840062 E-mail: saeedtoulabi@yahoo.com 1. Department of Counselling, Faculty of Psychology, Kharazmi University, Tehran, Iran. 2. Department of Educational Psychology, Faculty of psychology, Kharazmi University, Tehran, Iran. Sedigheh Ahmadi1 , *Saeed Toulabi2 , Hossein Ilanloo1