Miracle-dz/UniFAR-FTUs huggingface dataset:
Author's Personal Copy Theoretical Computer Science a Computational Proof of Complexity of Some Restricted Counting Problems Author's Personal Copy Author's Personal Copy

In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: a b s t r a c t We explore a computational approach to proving the intractability of certain counting problems. These problems can be described in various ways, and they include concrete problems such as counting the number of vertex covers or independent sets for 3-regular graphs. The high level principle of our approach is algebraic, which provides sufficient conditions for interpolation to succeed. Another algebraic component is holographic reductions. We then analyze in detail polynomial maps on R 2 induced by some combinatorial constructions. These maps define sufficiently complicated dynamics of R 2 that we can only analyze them computationally. In this paper we use both numerical computation (as intuitive guidance) and symbolic computation (as proof theoretic verification) to derive that a certain collection of combinatorial constructions, in myriad combinations, fulfills the algebraic requirements of proving #P-hardness. The final result is a dichotomy theorem for a class of counting problems. This includes a class of generic holant problems with an arbitrary real valued edge signature over (2, 3)-regular undirected graphs. In particular, it includes all partition functions with 0–1 vertex assignments and an arbitrary real valued edge function over all 3-regular undirected graphs. In this paper we study some counting problems which can be described in the following way. We are given a graph G = (V , E). At each vertex v ∈ V there is a function f v , and at each edge e ∈ E there is a function g e. We also call these functions f v and g e signatures. These functions take 0–1 inputs and output real values in R. Now consider all 0–1 assignments σ at each end of every edge e = (x, y), i.e., a value σ (e, x) and σ (e, y). The counting problem is to compute ∑ σ ∏ v f v (σ | v) ∏ e g e (σ | e), where the sum is over all 0–1 assignments σ , of products of function evaluations over all v ∈ V and e ∈ E. Here σ | v denotes the values assigned locally by σ at v, i.e., the ends of all edges …
Title: Factors Affecting Intra-island Genetic Connectivity and Diversity of an Abundant and Running Title: Landscape Genetics of Xantusia Riversiana

1 widespread island endemic, the San Clemente Island night lizard. ABSTRACT 17 Habitat fragmentation and loss are fundamental conservation concerns. Because protected 18 areas are often " habitat islands " isolated by human development, studies of physical islands 19 which document genetic patterns associated with natural versus anthropogenic fragmentation may 20 provide insight into the management of anthropogenic habitat islands. The San Clemente Island 21 night lizard, Xantusia riversiana reticulata, is a highly abundant endemic to two California 22 Channel Islands (San Clemente and Santa Barbara Islands), each with a history of anthropogenic 23. CC-BY-NC-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not. 2 disturbance, and was recently delisted from the Endangered Species Act. We genotyped 917 24 individuals at 23 microsatellite loci to estimate genetic divergence between collection sites and 25 identify natural and anthropogenic landscape features correlated with genetic divergence for X. r. 26 reticulata throughout its range. Genepool delineation resulted in each well-sampled collection 27 site acting as a distinct population, pairwise Fst values were small but significant, and 28 STRUCTURE detected 2 populations on San Clemente Island and 4 populations on Santa Barbara 29 Island. Active sand dunes on San Clemente Island acted as a barrier whereas cholla phase 30 maritime desert scrub, secondary roadways, and canyons > 500ft in length acted as resistant 31 surfaces. Resistant surfaces on Santa Barbara Island were woolly seablite, crystalline iceplant, 32 barren ground, and herbaceous vegetation. Conductance models included California boxthorn and 33 prickly pear cactus on both islands with additional minor features unique to each island. We 34 recommend the application of conductance and resistance models within " habitat islands " to 35 better inform management for species persistence when the intervening habitat between reserves 36 cannot be improved.
Recommendation : A Ranking Approach to Address the Ubiquitous Click Sparsity Problem

We study the problem of personalized advertisement recommendation (PAR), which consist of a user visiting a system (website) and the system displaying one of K ads to the user. The system uses an internal ad recommendation policy to map the user’s profile (context) to one of the ads. The user either clicks or ignores the ad and correspondingly, the system updates its recommendation policy. PAR problem is usually tackled by scalable contextual bandit algorithms, where the policies are generally based on classifiers. A practical problem in PAR is extreme click sparsity, due to very few users actually clicking on ads. We systematically study the drawback of using contextual bandit algorithms based on classifier-based policies, in face of extreme click sparsity. We then suggest an alternate policy, based on rankers, learnt by optimizing the Area Under the Curve (AUC) ranking loss, which can significantly alleviate the problem of click sparsity. We conduct extensive experiments on public datasets, as well as three industry proprietary datasets, to illustrate the improvement in click-through-rate (CTR) obtained by using the ranker-based policy over classifier-based policies.
International Students’ Perceptions and Experiences of British Drinking Cultures

While the increased scale and importance of international students to the UK Higher Education sector is now well established, little is known about the ways in which students from non-UK countries experience and interact with the heavy drinking culture that predominates on and near many British universities. Drawing on qualitative interviews, this article analyses the perceptions, attitudes, and experiences of British drinking cultures held by international students studying on postgraduate courses at a UK university. Students report prior awareness of alcohol consumption being important to British culture and recount both positive and negative experiences of witnessing and, for many, participating in drinking alcohol. Students make ready comparisons with the drinking habits and attitudes of their own culture. Further still, many made a distinction between the public house, or ‘pub’, as a welcoming and friendly social space, and bars and nightclubs, where a far greater risk of exposure to violence and harassment was perceived. The article provides theoretical insights to support future and more wide-ranging research into mobile drinking cultures and also suggests practical implications to inform stakeholders with interests in the welfare of international students in the UK in relation to the provision of effective and proactive policies which address the impact of British drinking cultures on international student integration and well-being.
SLocX: Predicting Subcellular Localization of Arabidopsis Proteins Leveraging Gene Expression Data

Despite the growing volume of experimentally validated knowledge about the subcellular localization of plant proteins, a well performing in silico prediction tool is still a necessity. Existing tools, which employ information derived from protein sequence alone, offer limited accuracy and/or rely on full sequence availability. We explored whether gene expression profiling data can be harnessed to enhance prediction performance. To achieve this, we trained several support vector machines to predict the subcellular localization of Arabidopsis thaliana proteins using sequence derived information, expression behavior, or a combination of these data and compared their predictive performance through a cross-validation test. We show that gene expression carries information about the subcellular localization not available in sequence information, yielding dramatic benefits for plastid localization prediction, and some notable improvements for other compartments such as the mitochondrion, the Golgi, and the plasma membrane. Based on these results, we constructed a novel subcellular localization prediction engine, SLocX, combining gene expression profiling data with protein sequence-based information. We then validated the results of this engine using an independent test set of annotated proteins and a transient expression of GFP fusion proteins. Here, we present the prediction framework and a website of predicted localizations for Arabidopsis. The relatively good accuracy of our prediction engine, even in cases where only partial protein sequence is available (e.g., in sequences lacking the N-terminal region), offers a promising opportunity for similar application to non-sequenced or poorly annotated plant species. Although the prediction scope of our method is currently limited by the availability of expression information on the ATH1 array, we believe that the advances in measuring gene expression technology will make our method applicable for all Arabidopsis proteins.
A Novel Caching Mechanism for P2P Video-on-Demand Systems

Providing scalable video services in a peer-to-peer (P2P) environment is challenging. In this paper we formulize the QoS (quality-of-service)-aware replication problem for P2P video-on-demand (VoD)systems, the goal of which is to satisfy access time deadlines for all nodes while maximize the probability of the successful block requests. A novel caching mechanism was proposed to achieve the goal, which includes a prefetching algorithm and a cache replacement algorithm. In particular, emergency level De and contribution degree Dc of blocks were defined, and were used in both algorithms to decide which block should be requested or removed. Simulation results show that our mechanism is effective in suppressing the playback delay and reducing the workload of server with a media stream of the desired quality comparing to another existing approach.
Scheduling aperiodic and sporadic tasks in hard real-time systems

The stringent timing constraints as well as the functional correctness are essential requirements of hard real-time systems. In such systems, scheduling plays a very important role in satisfying these constraints. The priority based scheduling schemes have been used commonly due to the simplicity of the scheduling algorithm. However, in the presence of task interdependencies and complex timing constraints, such scheduling schemes may not be appropriate due to the lack of an e cient mechanism to schedule them and to carry out the schedulability analysis. In contrast, the time based scheduling scheme may be used to schedule a set of tasks with greater degree of schedulability achieved at a cost of higher complexity of o -line scheduling. One of the drawbacks of currently available scheduling schemes, however, is known to be their in exibility in dynamic environments where dynamic processes exist, such as aperiodic and sporadic processes. We develop and analyze scheduling schemes which e ciently provide the exibility required in real-time systems for scheduling processes arriving dynamically. This enables static hard periodic processes and dynamic processes(aperiodic or sporadic) to be jointly scheduled. This work is supported in part by ONR and ARPA under contract N66001-95-C-8619 to the Computer Science Department at the University of Maryland. The views, opinions, and/or ndings contained in this report are those of the author(s) and should not be interpreted as representing the o cial policies, either expressed or implied, of the Advanced Research Projects Agency, ONR or the U.S. Government.
Eurospeech 2001 -scandinavia 6\vwhp'hvfulswlrq

With this work we evaluate the Philips continuous speech recognition system on the standardized AURORA noisy digit string recognition task. A variety of noise robust algorithms, ranging from spectral subtraction during the feature extraction stage, to adaptation techniques in the HMM-decoding stage, are applied and their effects are presented. Detailed experimental results show the contribution of the single approaches to the overall system performance. By thoroughly combining the best performing of the standard algorithms, we achieve in the weighted average performance figure, as defined over the six basic AURORA tasks, a total performance of 92.42% word accuracy. ,QWURGXFWLRQ Still, speech recognition under adverse noisy conditions is a challenging research topic even for small vocabulary tasks. Especially non-stationary and noise conditions, which were not seen in the training material for the HMM based recognizers, have been identified as the major reasons for degraded performance. A huge variety of algorithms has been presented over the years to enhance the robustness of the automatic speech recognition against additive as well as convolutional noise. The approaches range from mere pre-processing algorithms, suppressing noise in front of the ASR system, over noise robust feature extraction schemes, towards measures inside the core HMM system like compensation and adaptation algorithms. With the AURORA 2.0 database introduced recently [1], a framework is available to compare different algorithms and systems on a common basis. One evaluation strategy on this database is, to keep the recognition engine fixed to a pre-defined HTK reference setup [1], and thus to benchmark different pre-processing and feature extraction methods only. Another strategy, and we are following this strategy with this paper, is, to evaluate an entire ASR system in its whole processing chain from the signal acquisition stage up to the back-end HMM recognizer. Aiming at improved overall performance on this database, we examine noise robust algorithms and strategies at several stages, from noise subtraction in the input signal to HMM-adaptation during recognition. Experimental evaluations describe the gain in performance achieved with each measure individually as well as in their interplay to finally configure an optimized system. The paper is organized as follows: The next chapter sketches the properties of the Philips continuous ASR system and its basic setup for the AURORA digits task. Chapter 3 presents the algorithms examined in order to achieve noise robust behavior, before, in chapter 4, detailed experimental results are given. A discussion of the improvements achieved and an …
Evidence of enhanced star formation efficiency in luminous and ultraluminous infrared galaxies

We present new observations made with the IRAM 30 m telescope of the J = 1−0 and 3–2 lines of HCN and HCO + used to probe the dense molecular gas content in a sample of 17 local luminous and ultraluminous infrared galaxies (LIRGs and ULIRGs). These observations have allowed us to derive an updated version of the power law describing the correlation between the FIR luminosity (LFIR )a nd the HCN(1−0) luminosity (L �−0) ) of local and high-redshift galaxies. We present the first clear observational evidence that the star formation efficiency of the dense gas (SFEdense), measured as the LFIR/L �−0) ratio, is significantly higher in LIRGs and ULIRGs than in normal galaxies, a result that has also been found recently in high-redshift galaxies. This may imply a statistically significant turn upward in the Kennicutt-Schmidt law derived for the dense gas at LFIR ≥ 10 11 L� . We used a one-phase large velocity gradient (LVG) radiative transfer code to fit the three independent line ratios derived from our observations. The results of this analysis indicate that the [HCN]/[HCO + ] abundance ratios could be up to one order of magnitude higher than normal in a significant number
Oxidative stress modulates vascular smooth muscle cell phenotype via CTGF in thoracic aortic aneurysm.

AIMS Dissection and rupture of the ascending aorta are life-threatening conditions resulting in 80% mortality. Ascending aortic replacement in patients presenting with thoracic aortic aneurysm (TAA) is determined by metric measurement. However, a significant number of dissections occur outside of the parameters suggested by the current guidelines. We investigate the correlation among altered haemodynamic condition, oxidative stress, and vascular smooth muscle cell (VSMC) phenotype in controlling tissue homoeostasis. METHODS AND RESULTS We demonstrate using finite element analysis (FEA) based on computed tomography geometries that TAA patients have higher wall stress in the ascending aorta than non-dilated patients. We also show that altered haemodynamic conditions are associated with increased levels of reactive oxygen species (ROS), direct regulators of the VSMC phenotype in the microregional area of the ascending aorta. Using in vitro and ex vivo studies on human tissues, we show that ROS accumulation correlates with media layer degeneration and increased connective tissue growth factor (CTGF) expression, which modulate the synthetic VSMC phenotype. Results were validated by a murine model of TAA (C57BL/6J) based on Angiotensin II infusion showing that medial thickening and luminal expansion of the proximal aorta is associated with the VSMC synthetic phenotype as seen in human specimens. CONCLUSIONS Increased peak wall stress correlates with change in VSMC towards a synthetic phenotype mediated by ROS accumulation via CTGF. Understanding the molecular mechanisms that regulate VSMC towards a synthetic phenotype could unveil new regulatory pathways of aortic homoeostasis and impact the risk-stratification tool for patients at risk of aortic dissection and rupture.
HIP JOINT RECONSTRUCTION AND MOTION VISUALIZATION USING MRI AND OPTICAL MOTION CAPTURE

Patients’ anatomical models are increasingly used for both preoperative planning and postoperative guides. The joints motion visualization opens a new level of understanding and can be a valuable diagnosis tool. We propose here to use optical motion capture to simulate internal motions. The ability to image the articulation dynamically and non-invasively in vivo opens the way to the efficient and accurate design of patient-specific musculoskeletal functional models. The long term of our current project in CO-ME is to improve the success rate of orthopaedic surgeries by providing a new set of tools for anatomical and functional simulation of the full leg. This will help orthopaedists in diagnosing pathologies and in surgical planning.
Use-Centric Information Representation for Creative Knowledge Work

This paper presents an approach that supports creative knowledge work by re-presenting information that the user has previously used. The Phantasmic Shadows system uses a set of presently used information pieces as a way to imply the user’s current interest. The system then sorts previously viewed information pieces in the order of the computed relevance to the user’s current interest, and presents the highly ordered pieces in an unobtrusive manner as a peripheral display on the desktop.
Rich context modeling for high quality HMM-based TTS

This paper presents a rich context modeling approach to high quality HMM-based speech synthesis. We first analyze the over-smoothing problem in conventional decision tree tyingbased HMM, and then propose to model the training speech tokens with rich context models. Special training procedure is adopted for reliable estimation of the rich context model parameters. In synthesis, a search algorithm following a contextbased pre-selection is performed to determine the optimal rich context model sequence which generates natural and crisp output speech. Experimental results show that spectral envelopes synthesized by the rich context models are with crisper formant structures and evolve with richer details than those obtained by the conventional models. The speech quality improvement is also perceived by listeners in a subjective preference test, in which 76% of the sentences synthesized using rich context modeling are preferred. Index Terms: HMM-based TTS, rich context modeling
YPAP: The Yoking-Proofs Based Authentication Protocol for Wearable Devices in Wireless Communications

Along with the development of wireless communications, wearable devices are becoming popular for monitoring user data to provide intelligent service support. It makes that the wearable devices confront severe security issues compared with the traditional short-range communications. Due to limitations of computation capabilities and communication resources, it brings more challenges to design security schemes for the wearable devices. In this work, a yoking-proofs based authentication protocol (YPAP) is proposed for the wearable devices during secure wireless communications. In the YPAP, lightweight cryptographic operators are applied to realize authentication between a smart phone and two wearable devices, and yoking-proofs are established for the remote cloud server to perform simultaneous identification during a session. Meanwhile, Rubin logic based security formal analysis is performed to prove that the YPAP has theoretical design correctness. It indicates that the proposed protocol is flexible for ubiquitous wearable device applications.
Amplify-and-forward with partial relay selection

This letter offers a statistical analysis of the basic two-hop Amplify-and-Forward link, where the relay node is selected based on instantaneous and partial knowledge of the channel. In contrast with previously reported work, where relay selection requires global knowledge (2 hops) of the relaying link, the problem considered is interesting in practical ad-hoc systems, where only neighboring (1 hop) channel information is available to the nodes. The probability density function of the received signal-to-noise ratio for the considered relaying link is approximated in closed form, and an asymptotic exponential expression is proposed to simplify performance estimation.
Recognition of expression variant faces from one sample image per enrolled subject

Despite remarkable progress on face recognition, little attention has been given to robustly recognize expression variant faces from a single sample image per person. One way to deal with the recognition of faces under above conditions is by using local statistical approaches which appear to be more robust against variations in facial expression. In this paper, we propose a new weighted matching method based on our recent work of AWPPZMA to recognize expression variant faces when only one exemplar image per enrolled subject is available. The proposed weighting method gives more significance to those parts of the face with facial expression variations that change less compared to neutral face image and less significance to those parts that change more. In this contribution, we use the difference between local area in the input face and its corresponding local area in the neutral face image as a measure of observable structure changes. The encouraging experimental results demonstrate that the proposed method provides a new solution to the problem of robustly recognizing expression variant faces in single model databases.