Miracle-dz/UniFAR-FTUs huggingface dataset:
Single-Path Bit Sharing for Automatic Loss-Aware Model Compression

Network pruning and quantization are proven to be effective ways for deep model compression. To obtain a highly compact model, most methods first perform network pruning and then conduct quantization based on the pruned model. However, this strategy may ignore that the pruning and quantization would affect each other and thus performing them separately may lead to sub-optimal performance. To address this, performing pruning and quantization jointly is essential. Nevertheless, how to make a trade-off between pruning and quantization is non-trivial. Moreover, existing compression methods often rely on some pre-defined compression configurations (i.e., pruning rates or bitwidths). Some attempts have been made to search for optimal configurations, which however may take unbearable optimization cost. To address these issues, we devise a simple yet effective method named Single-path Bit Sharing (SBS) for automatic loss-aware model compression. To this end, we consider the network pruning as a special case of quantization and provide a unified view for model pruning and quantization. We then introduce a single-path model to encode all candidate compression configurations, where a high bitwidth value will be decomposed into the sum of a lowest bitwidth value and a series of re-assignment offsets. Relying on the single-path model, we introduce learnable binary gates to encode the choice of configurations and learn the binary gates and model parameters jointly. More importantly, the configuration search problem can be transformed into a subset selection problem, which helps to significantly reduce the optimization difficulty and computation cost. In this way, the compression configurations of each layer and the trade-off between pruning and quantization can be automatically determined. Extensive experiments on CIFAR-100 and ImageNet show that SBS significantly reduces computation cost while achieving promising performance. For example, our SBS compressed MobileNetV2 achieves 22.6× Bit-Operation (BOP) reduction with only 0.1% drop in the Top-1 accuracy.
Political Hate Speech Detection and Lexicon Building: A Study in Taiwan

There is minimal restriction to users’ speech in cyberspace. The Internet provides a space in which people can freely present their speech, which puts a Utopian sense of freedom of speech into practice. However, the appearance of hate speech is a significant side effect of online freedom of speech. Some users use hate speech to attack others, which makes the attacked targets uncomfortable. The proliferation of hate speech poses serious challenges to cyber society. Users may hope that social media platforms and online communities promote anti-hate speech. However, hate speech detection is still a developing technology which requires system developers to create a method to detect unacceptable hate speech while maintaining the online freedom of speech environment. No effective detection approach has yet been proposed, although some literature has focused on it. The current study proposes an approach to build a political hate speech lexicon and train artificial intelligence classifiers to detect hate speech. Our academic and practical contributions include the collection of a Chinese hate speech dataset, creation of a Chinese hate speech lexicon, and the development of both a deep learning-based and a lexicon-based approach to detect Chinese hate speech. Although we focus on Chinese hate speech detection, our proposed hate speech detection system and hate speech lexicon development approach can also be used for other languages.
Studies of networking algorithms in wireless sensor networks

In traditional wireless sensor networks (WSNs), sensors po wered by battery are largely deployed in a field to observe certain physical phenomena, such as temperature, noise and many more. The purpose of WSN is to be able to sense from environmen t and detect events for a long time. By improving the network lifetime, WSNs are able to det ect events longer. This agrees with the nature of WSNs, which is sense-to-detect events thr ough long operations (hopefully) of batteries. However, limited battery capacity and low eve nt detection probability have always been imposing serious challenges and constraints to networ k applications, stimulating the developments of various new technologies. Existing works on m axi izing lifetime include networking clustering technologies which let most sensors com municate with the nearby cluster head (CH) rather than the remote base station; and energy-ha vesting (EH) sensors which allow battery recharging by collecting energy from surrounding e vironment, etc. Existing works on maximizing event detection probability study the case of de terministic and known sensors deployment, where sensors transmit their local observations or decisions over perfectly known channels to a Gateway, which collects the observations and f uses them in order to perform event detection. In this thesis, we propose a centralized approach to finding t he optimal locations for cluster heads and energy harvesting nodes, where we consider nodes p w red by ambient energy harvesting as dedicated relay nodes for cluster heads, and prop ose joint clustering and relay node placement algorithms for network lifetime maximization. I addition, we also propose a distributed EH-CH matching algorithm with given locations for CHs and EHs. To achieve good EH-CH matching in a distributed manner, we borrow ideas adop ted in virtual-output-queued (VOQ) networks to develop a simple matching scheme. For the p roblem of event detection, we develop the first reported solution for wireless sensor ne twork under random deployment. We consider the practical case where the spatial distributi on of the sensors follows a Finite
Potential Wadge Classes

Let $\bf\Gamma$ be a Borel class, or a Wadge class of Borel sets, and $2\! \leq\! d\! \leq\! \omega$ be a cardinal. A Borel subset $B$ of ${\mathbb R}^d$ is potentially in $\bf\Gamma$ if there is a finer Polish topology on $\mathbb R$ such that $B$ is in $\bf\Gamma$ when ${\mathbb R}^d$ is equipped with the new product topology. The author provides a way to recognize the sets potentially in $\bf\Gamma$ and applies this to the classes of graphs (oriented or not), quasi-orders and partial orders.
Design patterns for robot swarms

Demand for autonomous multi-robot systems, where robots can cooperate with each other without human intervention, is set to grow rapidly in the next decade. Today, technologies such as self-driving cars and fleets of robotic assistants in hospitals and warehouses are being developed and used. In the future, robot swarms could be deployed in retrieval, reconnaissance and construction missions. Distributed collective systems have desirable properties, such as low cost of individual robots, robustness, fault tolerance and scalability. One of the main challenges in swarm robotics is that "bottom-up" approach to behaviour design is required. While the swarm performance is specified on the collective level of the swarm, robot designers need to program control algorithms of individual robots, while taking into account complex robot-robot interactions that allow emergence of collective intelligence. In order to be able to develop such systems, we need a methodology that aligns bottom-up design decisions with top-down design specifications. In this thesis, a novel approach to understanding and designing robot swarms that perform foraging and task allocation is proposed. Based on thousands of different simulation experiments, the Information-Cost-Reward framework is formulated, that relates the way in which a swarm obtains and uses information, to its ability to use that information in order to obtain reward efficiently. Secondly, based on the information-based understanding of swarm performance, design patterns for robot swarms are formalised. The design patterns are modular aspects of robot behaviour that define when and how information should be obtained, exchanged or updated by robots, given particular swarm mission characteristics. Multiple design patterns can be unambiguously combined together in order to create a suitable robot control strategy. The design patterns specify robot behaviour in a newly developed Behaviour-Data Relations Modeling Language, where relationships between robot behaviour and data stored in and outside of robots are explicitly defined. This allows the design patterns to define behaviour of robots that cooperate and share information.
NARRATE: A Normal Assisted Free-View Portrait Stylizer

In this work, we propose NARRATE, a novel pipeline that enables simultaneously editing portrait lighting and perspective in a photorealistic manner. As a hybrid neural-physical face model, NARRATE leverages complementary benefits of geometry-aware generative approaches and normal-assisted physical face models. In a nutshell, NARRATE first inverts the input portrait to a coarse geometry and employs neural rendering to generate images resembling the input, as well as producing convincing pose changes. However, inversion step introduces mismatch, bringing low-quality images with less facial details. As such, we further estimate portrait normal to enhance the coarse geometry, creating a high-fidelity physical face model. In particular, we fuse the neural and physical renderings to compensate for the imperfect inversion, resulting in both realistic and view-consistent novel perspective images. In relighting stage, previous works focus on single view portrait relighting but ignoring consistency between different perspectives as well, leading unstable and inconsistent lighting effects for view changes. We extend Total Relighting to fix this problem by unifying its multi-view input normal maps with the physical face model. NARRATE conducts relighting with consistent normal maps, imposing cross-view constraints and exhibiting stable and coherent illumination effects. We experimentally demonstrate that NARRATE achieves more photorealistic, reliable results over prior works. We further bridge NARRATE with animation and style transfer tools, supporting pose change, light change, facial animation, and style transfer, either separately or in combination, all at a photographic quality. We showcase vivid free-view facial animations as well as 3D-aware relightable stylization, which help facilitate various AR/VR applications like virtual cinematography, 3D video conferencing, and post-production.
SOME FIXED POINT THEOREMS FOR CONDENSING MULTIFONCTIONS IN LOCALLY CONVEX SPACES

Let G be a nonempty subset of a locally convex space E such that cl(C) is convex and quasi-complete, and /: cl(G)—► E a continuous condensing multifunction. In this paper, several fixed point theorems are established if / satisfies some conditions on the boundary of G. The results herein extend some theorems of Reich [9] and generalize some of the well-known fixed point theorems. The classical Tychonoff's fixed point theorem [l0] has been extended to multifunctions by Browder [3l, Fan [4], Glicksberg [5], Himmelberg [7] and several others. In a recent paper [9j, Reich has proved some interesting fixed point theorems for condensing multifunctions and has given extensions of some of the results contained in [3] and [4.1. In this paper, we prove several fixed point theorems for condensing multifunctions in a locally convex space. The main result of this paper (Theorem 2) is motivated by Reich [9] and extends a result in [9l. The results herein also generalize some wellknown results (see [2], [8]). 1. Let X and Y be topological spaces. A multifunction /: X —» Y is a point to set function such that for each x £ X, f(x) is a nonempty subset of V. The multifunction /: X —> Y is (a) upper semicontinuous (u. s. c.) iff for each closed subset B of V, the set /" (ß) = i*: /(*) n B 4 0\ is a closed subset of X, (b) lower semicontinuous (l.s.c.)iff for each open subset U C Y, the set /~ (U) is an open subset of X, (c) continuous iff it is both u.s.c. and l.s. c, (d) point-compact (closed, convex) iff for each * £ X, /(*) is a compact (closed, convex) subset of Y. It follows immediately from the above that a multifunction f: X —» V is u.s.c. iff for each * £ X and open U C Y with /(*) Ç U, there is an open VCX such that * £ V and f(v) = \J{f(z): z £ V\ C U. It is l.s. c. iff for each open set U C Y and each * £ X with /(*) Ci ¡J 4 0, there exists an Received by the editors February 16, 1974. AMS (MOS) subject classifications (1970). Primary 47H10, 54H20.
Detection of Tropical Diseases Caused by Mosquitoes Using CRISPR-Based Biosensors

Tropical diseases (TDs) are among the leading cause of mortality and fatality globally. The emergence and reemergence of TDs continue to challenge healthcare system. Several tropical diseases such as yellow fever, tuberculosis, cholera, Ebola, HIV, rotavirus, dengue, and malaria outbreaks have led to endemics and epidemics around the world, resulting in millions of deaths. The increase in climate change, migration and urbanization, overcrowding, and other factors continue to increase the spread of TDs. More cases of TDs are recorded as a result of substandard health care systems and lack of access to clean water and food. Early diagnosis of these diseases is crucial for treatment and control. Despite the advancement and development of numerous diagnosis assays, the healthcare system is still hindered by many challenges which include low sensitivity, specificity, the need of trained pathologists, the use of chemicals and a lack of point of care (POC) diagnostic. In order to address these issues, scientists have adopted the use of CRISPR/Cas systems which are gene editing technologies that mimic bacterial immune pathways. Recent advances in CRISPR-based biotechnology have significantly expanded the development of biomolecular sensors for diagnosing diseases and understanding cellular signaling pathways. The CRISPR/Cas strategy plays an excellent role in the field of biosensors. The latest developments are evolving with the specific use of CRISPR, which aims for a fast and accurate sensor system. Thus, the aim of this review is to provide concise knowledge on TDs associated with mosquitoes in terms of pathology and epidemiology as well as background knowledge on CRISPR in prokaryotes and eukaryotes. Moreover, the study overviews the application of the CRISPR/Cas system for detection of TDs associated with mosquitoes.
Factors affecting the integration of auditory and visual information in speech: The level effect

The “McGurk effect” is a phenomenon in which an illusory syllable is perceived when discrepant auditory and visual information are combined. For example, an illusory /da/ is perceived when an auditory syllable /ba/ is paired with a video display of a talker saying /ga/. In a series of studies reported here, it was found that the level of the auditory signal substantially affects the illusion. Moreover, this effect of auditory level works in a direction that is counterintuitive. One might have postulated that as the level of the auditory signal is increased, making the auditory signal more pronounced, the illusion would decrease. These results indicate just the opposite. As the level of the auditory signal goes up, rather than it outweighing the visual signal and thereby decreasing the illusion, the effect is to increase the number of illusory responses. Paired were the same auditory syllable /ba/ at three levels, soft (45 dB SPL), moderate (58 dB SPL), and loud (66 dB SPL), with a video display of /ga/. Significant increases in illusory /da/ responses occurred as the auditory signal increased from soft to moderate and again from moderate to loud. The work thus shows that auditory level is an important determinant in the perception of the illusion. The paradox of the situation is that as the auditory signal increases in strength, the resulting percept becomes less veridical rather than more so. [Work supported by NIH. ]
Seminormal forms for the Temperley-Lieb algebra

Let ${\mathbb{TL}_n^{\! \mathbb Q}} $ be the rational Temperley-Lieb algebra, with loop parameter $ 2 $. In the first part of the paper we study the seminormal idempotents $ E_{ \mathfrak{t}} $ for ${\mathbb{TL}_n^{\! \mathbb Q}}$ for $ \mathfrak{t} $ running over two-column standard tableaux. Our main result is here a concrete combinatorial construction of $ E_{\mathfrak{t}} $ using Jones-Wenzl idempotents $ {\mathbf{JW}_{\! k}} $ for ${\mathbb{TL}_k^{\! \mathbb Q}}$ where $ k \le n $. In the second part of the paper we consider the Temperley-Lieb algebra ${\mathbb{TL}_n^{\! {\mathbb F}_p}}$ over the finite field $ {\mathbb F}_p$, where $ p>2$. The KLR-approach to ${\mathbb{TL}_n^{\! {\mathbb F}_p}}$ gives rise to an action of a symmetric group $ \mathfrak{S}_m$ on ${\mathbb{TL}_n^{\! {\mathbb F}_p}}$, for some $ m<n $. We show that the $ E_{ \mathfrak{t}} $'s from the first part of the paper are simultaneous eigenvectors for the associated Jucys-Murphy elements for $ \mathfrak{S}_m$. This leads to a KLR-interpretation of the $p$-Jones-Wenzl idempotent $ ^{p}\! {\mathbf{JW}_{\! n}} $ for ${\mathbb{TL}_n^{\! {\mathbb F}_p}}$, that was introduced recently by Burull, Libedinsky and Sentinelli.
Assessment of Personal Values for Data-Driven Human Resource Management

Business organizations have introduced data analytics to human resource management (HRM) to predict employee behavior in recent years. This practice is called HR analytics, and uses the various properties of employees, including their personal values, as inputs. Personal values are conceptualized as stable personal traits that represent the relevant employee. Previous studies in the area have shown that the personal values of employees influence their attitudes and behaviors as well as the performance of their group. Assessing these values is thus important in HRM. Although most previous studies have measured personal values based on self-reported questionnaires, this method encounters many problems, such as the social desirability bias. Accordingly, more recent studies have proposed alternative methods that apply machine learning algorithms to linguistic or visual data. This study reviews research on personal values by focusing on the methods used to measure them, and discusses the usefulness of and the challenges to the measurement of personal values. We also discuss future directions of research on the assessment of personal values.
Measuring Probabilities which Violate "Reality" in a Bell Inequality Experiment

B. L. Higgins, 2 M. S. Palsson, G. Y. Xiang, 3 H. M. Wiseman, and G. J. Pryde Centre for Quantum Dynamics and Centre for Quantum Computation and Communication Technology, Griffith University, Brisbane 4111, Australia Institute for Quantum Computing, University of Waterloo, Waterloo, ON N2L 3G1, Canada Key Laboratory of Quantum Information, University of Science and Technology of China, Hefei 230026, China
Information Efficiency and Firm-Specific Return Variation

Reasoning that private firm-specific information causes firm-specific return variation that drives down market-model R2s, [Morck et al., 2000, The Information Content of Stock Markets: Why do Emerging Markets have Synchronous Stock Price Movements? Journal of Financial Economics, 58, 215–260] begin a large body of research which interprets R2 as an inverse measure of price informativeness. Low-R2s or "synchronicity," as it is called in this literature, signal that prices more efficiently incorporate private firm-specific information, and high R2s indicate less. For this to be true, we would expect that low-R2 stocks have characteristics that facilitate private informed trade, i.e., lower information costs and fewer impediments to arbitrage. However, in this paper we document the opposite: Low-R2 stocks are small, young, and followed by few analysts, and have high bid-ask spreads, high price impact, greater short-sale constraints and are infrequently traded. In fact, microstructure measures suggest that private-information events are less likely for low-R2 stocks than high, and that differences in R2 are driven as much by firm-specific volatility on days without private news as by firm-specific volatility on days with private news. These results call into question prior research using R2 to measure the information content of stock prices.
Structure and metamorphism in the Mount Washington area, New Hampshire

The Mt. Washington area of New Hampshire contains the highest peaks in the northern Appalachian Mountains. The metamorphic rocks belong to four stratigraphic units: the Ordovician (? ) Ammonoosuc volcanics, chiefly fine-grained biotite gneiss; the Ordovician (? ) Partridge formation, largely gneiss derived from shale; the Silurian Fitch formation, consisting of lime-silicate granulite and schist; the Devonian Littleton formation, mostly quartzite and schist. The oldest intrusive rocks are quartz monzonites and granites belonging to the Devonian (? ) Oliverian and New Hampshire series. Granite, syenite, tuff, and breccia belong to the Mississippian (? ) White Mountains magma series. The chemical composition of some of the minerals differs with the formation. Pyroxene and amphibole in the Fitch formation are magnesia-rich and iron-poor, whereas in the Ammonoosuc volcanics the reverse is true. Oligoclase characterizes the Partridge formation, Littleton formation, and Bickford granite; andesine is typical in the Ammonoosuc volcanics; and bytownite is common in the Fitch formation. Biotite and muscovite are relatively uniform, except for magnesia-rich biotite in the Fitch formation. The Mt. Washington area is on the southeast flank of a large dome, the center of which is occupied by the intrusive Oliverian magma series. The folds in the Presidential Range trend north and northeast. The major folds are en echelon , and upon them are superimposed many minor folds. Schistosity, due to platy minerals, parallels the bedding. Fracture cleavage is essentially parallel to the axial planes of the minor folds. The Pine Mountain fault is the largest of several normal faults. Metamorphism is high-grade (katazonal). Original shales are now andalusite schist, coarse rough pseudo-andalusite schist, fine grained pseudo-andalusite schist, and staurolite schist. Contrasting metamorphic history explains the various types. Metamorphism was syntectonic, and the coarser schists show three major stages in the paragenesis. Many rocks, particularly paraschists, suffered no significant chemical change. Potash was introduced into some of the coarser schists. Many of the gneisses are derived from shale by metamorphic differentiation, and less than 1 per cent of soda, lime, and potash has been introduced. Four or five per cent of soda, lime, and potash has been added to shale to form the lighter colored gneisses.
Tertiary Volcanic and Tectonic Evolution of the Ayas-Güdül-Celtikci Region, Turkey

Volcanic activity in the Ayas-Gudul-Celtikci region began by Oligocene (? )-early Miocene time and persisted until the end of early Pliocene time. It commenced with andesitic breccias and lavas at the base of the series and evolved through the deposition of ignimbritic and laharic volcanic material toward intermediate levels of the succession. Caldera formation followed this period of volcanic activity. Ephemeral lakes covering the region caused the subaqueous extrusion of the latest lavas during this period of activity. Afterward, limnic and fluvial sedimentation Occurred in the region during a period of volcanic quiescence. This mid-late Miocene deposition was followed by new basaltic activity. The volcanism was controlled by conjugate fault sets, N45W and N15E, representing pure-shear stress in a N20W direction, from the late Oligocene to the end of the early Pliocene. Normal dip-slip faults having a N55E trend were created by local N25W tension, presumably because of the North Anatolian fault, after ea.