Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploiting Causal Independence in Bayesian Network Inference

A new method is proposed for exploiting causal independencies in exact Bayesian network inference. A Bayesian network can be viewed as representing a factorization of a joint probability into the multiplication of a set of conditional probabilities. We present a notion of causal independence that enables one to further factorize the conditional probabilities into a combination of even smaller factors and consequently obtain a finer-grain factorization of the joint probability. The new formulation of causal independence lets us specify the conditional probability of a variable given its parents in terms of an associative and commutative operator, such as "or", "sum" or "max", on the contribution of each parent. We start with a simple algorithm VE for Bayesian network inference that, given evidence and a query variable, uses the factorization to find the posterior distribution of the query. We show how this algorithm can be extended to exploit causal independence. Empirical studies, based on the CPCS networks for medical diagnosis, show that this method is more efficient than previous methods and allows for inference in larger networks than previous algorithms.
Low SNR Capacity of Fading Channels -- MIMO and multipath

Discrete-time noncoherent Rayleigh fading multiple-input multiple-output (MIMO) channels are consi dered, with no channel state information at either the transmitter or the receiver. The fading is assumed to be correlated in time and independent from antenna to antenna. Peak and average transmit power constraints are imposed, either on the sum ov er antennas, or on each individual antenna. In both cases, an up per bound and an asymptotic lower bound, as the signal-to-noise ratio approaches zero, on the channel capacity are presente d. The capacity asymptote is identified under the sum power constraints. For the individual power constraints, bounds on the capacity asymptote are presented and shown to be tight under certain conditions. These results are applied to a SIS O channel with multipath fading. For such a channel, the multiple transmission paths play the role of multiple transmit antennas. Upper and lower bounds on the low SNR capacity asymptote are presented and shown to coincide under certain condition s.
Mapping Asian anthropogenic emissions of non-methane volatile organic compounds to multiple chemical mechanisms

Abstract. An accurate speciation mapping of non-methane volatile organic compounds (NMVOC) emissions has an important impact on the performance of chemical transport models (CTMs) in simulating ozone mixing ratios and secondary organic aerosols. Taking the INTEX-B Asian NMVOC emission inventory as the case, we developed an improved speciation framework to generate model-ready anthropogenic NMVOC emissions for various gas-phase chemical mechanisms commonly used in CTMs in this work, by using an explicit assignment approach and updated NMVOC profiles. NMVOC profiles were selected and aggregated from a wide range of new measurements and the SPECIATE database v.4. 2. To reduce potential uncertainty from individual measurements, composite profiles were developed by grouping and averaging source profiles from the same category. The fractions of oxygenated volatile organic compounds (OVOC) were corrected during the compositing process for those profiles which used improper sampling and analyzing methods. Emissions of individual species were then lumped into species in different chemical mechanisms used in CTMs by applying mechanism-dependent species mapping tables, which overcomes the weakness of inaccurate mapping in previous studies. Emission estimates for individual NMVOC species differ between one and three orders of magnitude for some species when different sets of profiles are used, indicating that source profile is the most important source of uncertainties of individual species emissions. However, those differences are diminished in lumped species as a result of the lumping in the chemical mechanisms. Gridded emissions for eight chemical mechanisms at 30 min × 30 min resolution as well as the auxiliary data are available at http://mic.greenresource. cn/intex-b2006 . The framework proposed in this work can be also used to develop speciated NMVOC emissions for other regions.
Charged hydrophilic polymer brushes and their relevance for understanding marine biofouling

Abstract The resistance of charged polymers to biofouling was investigated by subjecting cationic (PDMAEMA), anionic (PSPMA), neutral (PHEMA-co-PEG10MA), and zwitterionic (PSBMA) brushes to assays testing protein adsorption; attachment of the marine bacterium Cobetia marina; settlement and adhesion strength of zoospores of the green alga Ulva linza; settlement of barnacle (Balanus amphitrite and B. improvisus) cypris larvae; and field immersion tests. Several results go beyond the expected dependence on direct electrostatic attraction; PSPMA showed good resistance towards attachment of C. marina, low settlement and adhesion of U. linza zoospores, and significantly lower biofouling than on PHEMA-co-PEG10MA or PSBMA after a field test for one week. PDMAEMA showed potential as a contact-active anti-algal coating due to its capacity to damage attached spores. However, after field testing for eight weeks, there were no significant differences in biofouling coverage among the surfaces. While charged polymers are unsuitable as antifouling coatings in the natural environment, they provide valuable insights into fouling processes, and are relevant for studies due to charging of nominally neutral surfaces.
Discriminated Belief Propagation

Near optimal decoding of good error control codes is generally a difficult task. However, for a certain type of (sufficiently) good codes an efficient decoding algorithm with near optimal performance exists. These codes are defined via a combination of constituent codes with low complexity trellis representations. Their decoding algorithm is an instance of (loopy) belief propagation and is based on an iterative transfer of constituent beliefs. The beliefs are thereby given by the symbol probabilities computed in the constituent trellises. Even though weak constituent codes are employed close to optimal performance is obtained, i.e., the encoder/decoder pair (almost) achieves the information theoretic capacity. However, (loopy) belief propagation only performs well for a rather specific set of codes, which limits its applicability. In this paper a generalisation of iterative decoding is presented. It is proposed to transfer more values than just the constituent beliefs. This is achieved by the transfer of beliefs obtained by independently investigating parts of the code space. This leads to the concept of discriminators, which are used to improve the decoder resolution within certain areas and defines discriminated symbol beliefs. It is shown that these beliefs approximate the overall symbol probabilities. This leads to an iteration rule that (below channel capacity) typically only admits the solution of the overall decoding problem. Via a Gauss approximation a low complexity version of this algorithm is derived. Moreover, the approach may then be applied to a wide range of channel maps without significant complexity increase.
IgE-mediated allergen presentation via Fc epsilon RI on antigen-presenting cells.

In atopic individuals, cutaneous antigen-presenting cells (APC), i.e. Langerhans' cells (LC) and dermal dendritic cells (DDC), frequently display anti-IgE reactivity. While earlier observations suggested that this phenomenon results from the binding of (complexed) IgE to the low affinity IgE receptor (Fc epsilonRII/CD23), recent evidence exists that LC and DDC, as well as peripheral blood dendritic cells and monocytes from atopic individuals, can bind monomeric IgE via the high-affinity receptor for IgE (Fc epsilonRI). We have now found that Fc epsilonRI, both quantitatively and qualitatively, is the pivotal serum IgE-binding structure on APC of atopic individuals, that Fc epsilonRI on APC functions as allergen-focusing molecule and that allergens are more efficiently taken up, processed and presented to T cells following targeting to APC via Fc epsilonRI compared to allergen binding to APC in the conventional manner. In vivo, Fc epsilonRI-IgE-dependent allergen presentation may critically lower atopic individuals' threshold to mount allergen-specific T cell responses. This would result in the perpetuation of allergen-specific IgE production (type I reactions) and perhaps even in the occurrence of T-cell-mediated delayed-type hypersensitivity reactions in allergen-exposed tissues.
A Method for Open-Vocabulary Speech-Driven Text Retrieval

While recent retrieval techniques do not limit the number of index terms, out-of-vocabulary (OOV) words are crucial in speech recognition. Aiming at retrieving information with spoken queries, we fill the gap between speech recognition and text retrieval in terms of the vocabulary size. Given a spoken query, we generate a transcription and detect OOV words through speech recognition. We then correspond detected OOV words to terms indexed in a target collection to complete the transcription, and search the collection for documents relevant to the completed transcription. We show the effectiveness of our method by way of experiments.
Near ML detection using Dijkstra’s algorithm with bounded list size over MIMO channels

We propose Dijkstrapsilas algorithm with bounded list size after QR decomposition for decreasing the computational complexity of near maximum-likelihood (ML) detection of signals over multiple-input-multiple-output (MIMO) channels. After that, we compare the performances of proposed algorithm, QR decomposition M-algorithm (QRM-MLD), and its improvement. When the list size is set to achieve the almost same symbol error rate (SER) as the QRM-MLD, the proposed algorithm has smaller average computational complexity.
Efficient messages broadcasting within vehicular safety applications

Advancements in communications technologies are spurring a revolution within the United States transportation network. Short-range dedicated radio allows vehicles to communicate with each other within VANET. Up to date, tremendous efforts from government, academia and industry have made progress in designing and implementing several vehicular safety applications. Therefore, significant efforts have been made in designing lower-layer communication protocols for VANET. Also, Connected Vehicles (CV) concept is moving rapidly from the experimental phase into real-world deployments. Nevertheless, since all vehicles in range are shown as destination nodes, safety applications in VANET critically need an optimized way for effectively transmitting information to surrounding vehicles. To respond to this need, we propose in this paper a new Request-To-Receive (RTR) approach as a crucial step in the Basic Safety Messages (BSM) transmission process among vehicles incubating multiple safety applications. A new Data Element is proposed to be added to the basic safety messages data dictionary. Simulation results showed that RTR reduces the average number of transmitted Data Element when compared to the current situation.
Using the Common Sense Model of Self-Regulation to Review the Effects of Self-Monitoring of Blood Glucose on Glycemic Control for Non–Insulin-Treated Adults With Type 2 Diabetes

Purpose This systematic review examined the relationship between self-monitoring of blood glucose (SMBG) and glycemic control in patients with type 2 diabetes. The Common Sense Model of Self-Regulation (CSM) served as a theoretical framework for examining how, when (mediators), and for whom (moderators) SMBG improved glycemic control. Data Sources Five databases were searched: Medline, PsychInfo, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, and Cumulative Index to Nursing & Allied Health Literature. Study Selection Included studies had cross-sectional, longitudinal, or randomized controlled trial designs; were published between 2007 and 2011; and included patients with type 2 diabetes at least some of whom were not taking insulin; 1318 studies were screened, 119 were reviewed in detail, and 26 were included. Data Extraction Data were collected on the relationship between SMBG and glycemic control, study design, mediators, moderators, participant characteristics, the CSM, and limitations. Data Synthesis Twenty-six studies met criteria for inclusion: 11 cross-sectional, 4 longitudinal, and 11 randomized controlled trials. The results of the cross-sectional studies were inconclusive. Results from the longitudinal studies and randomized control trials suggested that SMBG may improve glycemic control. The few studies investigating mediators or moderators reported mixed results. Few studies effectively measured the CSM. Conclusion Data suggested that SMBG may help improve glycemic control. Future trials must be designed to test hypotheses and improve our understanding of when, how, and for whom SMBG can enhance glycemic control. Rigorously controlled repetitions of current 2-arm trials will yield little new knowledge of theoretical or practical value.
Relating Turing’s Formula and Zipf’s Law

An asymptote is derived from Turing's local reestimation formula for population frequencies, and a local reestimation formula is derived from Zipf's law for the asymptotic behavior of population frequencies. The two are shown to be qualitatively different asymptotically, but nevertheless to be instances of a common class of reestimation-formula-asymptote pairs, in which they constitute the upper and lower bounds of the convergence region of the cumulative of the frequency function, as rank tends to infinity. The results demonstrate that Turing's formula is qualitatively different from the various extensions to Zipf's law, and suggest that it smooths the frequency estimates towards a geometric distribution.
Learning and discrimination through STDP in a top-down modulated associative memory

This article underlines the learning and discrimination ca- pabilities of a model of associative memory based on artificial networks of spiking neurons. Inspired from neuropsychology and neurobiology, the model implements top-down modulations, as in neocortical layer V pyra- midal neurons, with a learning rule based on synaptic plasticity (STDP), for performing a multimodal association learning task. A temporal cor- relation method of analysis proves the ability of the model to associate specific activity patterns to different samples of stimulation. Even in the absence of initial learning and with continuously varying weights, the ac- tivity patterns become stable enough for discrimination.
Capacity of a Class of Modulo-Sum Relay Channels

This paper characterizes the capacity of a class of modular additive noise relay channels, in which the relay observes a corrupted version of the noise and has a separate channel to the destination. The capacity is shown to be strictly below the cut-set bound in general and achievable using a quantize-and-forward strategy at the relay. This result confirms a previous conjecture on the capacity of channels with rate-limited side information at the receiver for this particular class of modulo-sum channels. This paper also considers a more general setting in which the relay is capable of conveying noncausal rate-limited side information about the noise to both the transmitter and the receiver. The capacity is characterized for the case where the channel is binary symmetric with a crossover probability 1/2. In this case, the rates available for conveying side information to the transmitter and to the receiver can be traded with each other arbitrarily-the capacity is a function of the sum of the two rates.
Discrete differential geometry of triangle tiles and algebra of closed trajectories

This paper proposes a new mathematical framework that can be applied to biological problems such as analysis of the structures of proteins and protein complexes. In particular, it gives a new method for encoding the three-dimensional structure of a protein into a binary sequence, where proteins are approximated by a folded tetrahedron sequence. It also gives a new algebraic framework for describing molecular complexes and their interactions. For simplicity, we shall explain the framework in the case of two-dimensional objects. Then, the binary code of a plane curve is obtained as the ``second derivative'' of the curve and ``fusion and fission'' of closed trajectories is described algebraically.
Optimal Power Allocation for Distributed Detection Over MIMO Channels in Wireless Sensor Networks

In distributed detection systems with wireless sensor networks, the communication between sensors and a fusion center is not perfect due to interference and limited transmitter power at the sensors to combat noise at the fusion center's receiver. The problem of optimizing detection performance with such imperfect communication brings a new challenge to distributed detection. In this paper, sensors are assumed to have independent but nonidentically distributed observations, and a multiple-input/multiple-output (MIMO) channel model is included to account for imperfect communication between the sensors and the fusion center. The J-divergence between the distributions of the detection statistic under different hypotheses is used as a performance criterion in order to provide a tractable analysis. Optimization of performance with individual and total transmitter power constraints on the sensors is studied, and the corresponding power allocation scheme strikes a tradeoff between two factors, the communication channel quality and the local decision quality. For the case with orthogonal channels, under certain conditions, the power allocation can be solved by a weighted water-filling al.gorithm. Simulations show that the proposed power allocation in certain cases only consumes as little as 25% of the total power used by an equal power allocation scheme while achieving the same performance.
A Locating-First Approach for Scalable Overlay Multicast

Recent proposals in multicast overlay networks have demonstrated the importance of exploiting underlying network topology data to construct efficient overlays. While they avoid virtual coordinates embedding and fixed landmarks measurements, these topology-aware proposals often rely on incremental and periodic refinements to improve each node's position in the delivery tree. We claim that there are barriers for the scalability of existing overlay multicast protocols. In fact, periodical refinement and control processes induce additional overhead and high communication cost. On the other hand, users attending a video conferencing session or an event broadcast expect an acceptable quality as soon as they join the multicast session. It is then important to overcome an efficiency problem from which almost all current overlay multicast proposals suffer. This problem is the long convergence time to reach a stabilized quality state in the overlay delivery tree. We propose a novel overlay multicast tree construction scheme, called LCC : Locate, Cluster and Conquer, designed to address the aforementioned scalability and efficiency issues. The scheme consists in two phases: a selective locating phase and an overlay construction phase. Using partial knowledge of location-information for participating nodes, the selective locating phase algorithm consists in locating the closest existing set of nodes (cluster) in the overlay for a newcomer. It allows then to avoid initially randomly-connected structures without using virtual coordinates system embedding nor fixed landmarks measurements. Then, on the basis of this locating process, the overlay construction phase consists in building and managing a topology-aware clustered hierarchical overlay.
Outage Probability of Cooperative Relay Networks in eta-µ, kappa-µ and Mixed Fading Channels

Outage performance of cooperative relay networks using opportunistic decode-and-forward (DF) relaying in η-μ, κ-μ and mixed η-μ and κ-μ fading channels is analyzed. In DF relaying, a relay is allowed to forward the message from source only if the message is correctly decoded. The destination node combines both the direct signals from the source and the indirect signals from the relays using maximal-ratio diversity combining technique. In our analysis, exact closed-form expressions for the outage probability are obtained in η-μ, κ-μ and mixed η-μ and κ-μ fading channels, respectively. Numerical examples are provided to show the effect of number of relays, transmission rate and fading parameters on the outage probability. Numerical results are verified with Monte Carlo simulations.
CRMP4 Inhibits Bone Formation by Negatively Regulating BMP and RhoA Signaling

We identified the neuroprotein collapsing response mediator protein‐4 (CRMP4) as a noncanonical osteogenic factor that regulates the differentiation of mouse bone marrow skeletal stem cells (bone marrow stromal stem cells [mBMSCs]) into osteoblastic cells. CRMP4 is the only member of the CRMP1–CRMP5 family to be expressed by mBMSCs and in osteoprogenitors of both adult mouse and human bones. In vitro gain‐of‐function and loss‐of‐function of CRMP4 in murine stromal cells revealed its inhibitory effect on osteoblast differentiation. In addition, Crmp4‐deficient mice (Crmp4–/–) displayed a 40% increase in bone mass, increased mineral apposition rate, and bone formation rate, compared to wild‐type controls. Increased bone mass in Crmp4–/– mice was associated with enhanced BMP2 signaling and BMP2‐induced osteoblast differentiation in Crmp4–/– osteoblasts (OBs). Furthermore, Crmp4–/– OBs exhibited enhanced activation of RhoA/focal adhesion kinase (FAK) signaling that led to cytoskeletal changes with increased cell spreading. In addition, Crmp4–/– OBs exhibited increased cell proliferation that was mediated via inhibiting cyclin‐dependent kinase inhibitor 1B, p27Kip1 and upregulating cyclin D1 expression which are targets of RhoA signaling pathway. Our findings identify CRMP4 as a novel negative regulator of osteoblast differentiation. © 2016 American Society for Bone and Mineral Research.
Tumor necrosis factor alpha inhibits wound healing in the rat.

This work was undertaken to study the effects of tumor necrosis factor-alpha (TNF-alpha/cachectin) on developing granulation tissue in rats. Cylindrical hollow sponge implants were used as an inductive matrix for the growth of granulation tissue. In the two test groups the implants were injected daily for 4 days with a solution containing either 50 or 200 ng of TNF-alpha, while the implants of the control group were treated correspondingly with phosphate-buffered saline solution only. Analyses of granulation tissue and would fluid in the sponge implants were carried out 7, 14 and 21 days after implantation. In histological specimens the ingrowth rate of granulation tissue into the sponge was significantly lower after 7 days in the group treated with 200 ng of TNF-alpha. No such an effect was observed after 14 or 21 days. After 7 days, the mean amounts of nucleic acids reflecting cellularity in the granulation tissue decreased dose-dependently, but nonsignificantly, in the groups treated with TNF-alpha. Simultaneously, the accumulation of collagen hydroxyproline of the sponge was significantly lower in the group treated with 200 ng of TNF-alpha than in the controls (-30%, one-way analysis of variance). This effect was not observed after 14 or 21 days. No significant differences were detected in the amounts of nitrogen, hexosamines and uronic acids between the groups, reflecting unchanged accumulation of glycosaminoglycans in the developing granulation tissue. (ABSTRACT TRUNCATED AT 250 WORDS)