Miracle-dz/UniFAR-FTUs huggingface dataset:
AC Scheduling Based on Thermodynamics of Indoor for On-Campus Small Data

This paper proposes a new day-ahead control scheme of an air conditioning (AC) based on thermodynamic model of indoor-temperature. The thermodynamic model of indoor-temperature can be achieved by modified first-order thermal dynamic equation. For the practical verification of proposed model, we implemented the home energy management system (HEMS) in the laboratory and used real experiment data sets. The proposed model can be represented by a state-space model of indoor-temperature and its parameters are obtained by least square algorithm. Through the proposed thermodynamic model, indoor-temperature can be predicted closely, and a behavior pattern of AC can also be achieved. This research involves the experimental verification of the proposed approach and communication architecture between the aggregator and a system user in a laboratory environment.
Multifractality in Foreign Currency Markets

Several empirical studies have shown the inadequacy of the standard Brownian motion (sBm) as a model of asset returns. To correct for this evidence some authors have conjectured that asset returns may be independently and identically Pareto-Levy stable (PLs) distributed, whereas others have asserted that asset returns may be identically - but not independently - fractional Brownian motion (fBm) distributed with Hurst exponents, in both cases, that differ from 0.5. In this article we empirically explore such non-standard assumptions for both spot and (nearby) futures returns for five foreign currencies: the British Pound, the Canadian Dollar, the German Mark, the Swiss Franc, and the Japanese Yen.
Optimal power distribution for decentralized electric energy network with electric vehicles

This paper proposes MIP (Mixed-Integer Programming)-based power distribution optimization method for decentralized energy network with electric vehicles (EVs). Decentralized energy network is a new grid systems toward independence from existing power grid, and renewable energy is main energy source for the decentralized energy network. EVs are expected to take an important role of future mobility and energy network. Because the latest EV usually include large battery for long cruising distance, now EVs can be regarded as “moving battery. ” Proposed method utilizes both battery in house and EV's battery to minimize total purchased energy and wasted energy. This method brings an opportunity to charge the surplus energy at house to EV's battery, and the total purchased energy may be reduced. Experimental results demonstrated the interconnection between the energy network with rich connectivity and EV reduced the purchased energy by more than half.
Interference management in wireless networks: Physical layer communication strategies, MAC layer interactions, and high layer messaging structures

Interference Management in Wireless Networks: Physical Layer Communication Strategies, MAC Layer Interactions, and High Layer Messaging Structures by Leonard H. Grokop Doctor of Philosophy in Computer Science University of California, Berkeley Professor David Tse, Chair Wireless communications research of previous decades has mostly focused on systems built from point to point channels. In such systems physical communication links are essentially interference free, and interference management is at most a peripheral issue. Whilst these approaches have obvious advantages in terms of simplicity of design and maintenance, they typically suffer from low spectral efficiencies. In this thesis we research a number of new approaches spanning a range of communication layers, aimed at improving spectrum management. In the first chapter the fully connected K-user interference channel is studied in a multipath environment with bandwidth W . We show that when each link consists of D physical paths, the total spectral efficiency can grow linearly with K. This result holds not merely in the limit of large transmit power P , but for any fixed P , and is therefore a stronger characterization than degrees of freedom. It is achieved via a form of interference alignment in the time domain. A caveat of this result is that W must grow with K, a phenomenon we refer to as bandwidth scaling. Our insight comes from examining channels with single path links (D = 1), which we refer to as line-of-sight (LOS) links. For such channels we build a time-indexed interference
Visual Arrestin Activity May Be Regulated by Self-association*

Visual arrestin is the protein responsible for rapid quenching of G-protein-coupled receptor signaling. Arrestin exists as a latent inhibitor which must be ‘activated’ upon contact with a phosphorylated receptor. X-ray crystal structures of visual arrestin exhibit a tetrameric arrangement wherein an asymmetric dimer with an extensive interface between conformationally different subunits is related to a second asymmetric dimer by a local two-fold rotation axis. To test the biological relevance of this molecular organization in solution, we carried out a sedimentation equilibrium analysis of arrestin at both crystallographic and physiological protein concentrations. While the tetrameric form can exist at the high concentrations used in crystallography experiments, we find that arrestin participates in a monomer/dimer equilibrium at concentrations more likely to be physiologically relevant. Solution interaction analysis of a proteolytically modified, constitutively active form of arrestin shows diminished dimerization. We propose that self-association of arrestin may provide a mechanism for regulation of arrestin activity by (i) ensuring an adequate supply for rapid quenching of the visual signal and (ii) limiting the availability of active monomeric species, thereby preventing inappropriate signal termination.
Load Balancing Routing for Wireless Mesh Networks: An Adaptive Partitioning Approach

In this paper, we propose a novel load balancing routing algorithm for wireless mesh networks (WMNs) with multiple gateways, i.e., sink routers. As most traffic occurring in WMNs is relayed to these gateways through wireless links in a multi-hop fashion, the sink routers are easily overloaded. In such a situation, when a user initiates a communication session and the corresponding route toward the sink router cannot provide the required level of services, the session is rejected. Our objective is to achieve load balancing routing that minimizes such rejections. To this end, we take an adaptive partitioning approach, which heuristically divides the entire network into partitions and applies load balancing to between partitions and within partitions. To cope with user mobility, partitions and routes are adaptively managed. Evaluation via simulations indicates up to 25% performance gains over existing schemes in rejected requests, while the overhead in route computation costs drops by up to 27%.
Musical Offset Detection of Pitched Instruments: The Case of Violin

Musical offset detection is an integral part of a music signal processing system that requires complete characterization of note events. However, unlike onset detection, off-set detection has seldom been the subject of an in-depth study in the music information retrieval community, possibly because of the ambiguity involved in the determination of offset times in music. This paper presents a preliminary study aiming at discussing ways to annotate and to evaluate offset times for pitched non-percussive instruments. More-over, we conduct a case study of offset detection in vio-lin recordings by evaluating a number of energy, spectral ﬂux, and pitch based methods using a new dataset covering 6 different violin playing techniques. The new dataset, which is going to be shared with the research community, consists of 63 violin recordings that are thoroughly annotated based on perceptual loudness and note transition. The offset detection methods, which are adapted from well-known methods for onset detection, are evaluated using an onset-aware method we propose for this task. Result shows that the accuracy of offset detection is highly dependent on the playing techniques involved. Moreover, pitch-based methods can better get rid of the soft-decaying behavior of offsets and achieve the best result among others.
An extension of fault-prone filtering using precise training and a dynamic threshold

Fault-prone module detection in source code is important for assurance of software quality. Most previous fault-prone detection approaches have been based on software metrics. Such approaches, however, have difficulties in collecting the metrics and in constructing mathematical models based on the metrics. To mitigate such difficulties, we have proposed a novel approach for detecting fault-prone modules using a spam-filtering technique, named Fault-Prone Filtering. In our approach, fault-prone modules are detected in such a way that the source code modules are considered as text files and are applied to the spam filter directly. In practice, we use the training only errors procedure and apply this procedure to fault-prone. Since no pre-training is required, this procedure can be applied to an actual development field immediately. This paper describes an extension of the training only errors procedures. We introduce a precise unit of training, "modified lines of code," instead of methods. In addition, we introduce the dynamic threshold for classification. The result of the experiment shows that our extension leads to twice the precision with about the same recall, and improves 15% on the best F1 measurement.
Exploiting Temporal Network Structures of Human Interaction to Effectively Immunize Populations

Decreasing the number of people who must be vaccinated to immunize a community against an infectious disease could both save resources and decrease outbreak sizes. A key to reaching such a lower threshold of immunization is to find and vaccinate people who, through their behavior, are more likely than average to become infected and to spread the disease further. Fortunately, the very behavior that makes these people important to vaccinate can help us to localize them. Earlier studies have shown that one can use previous contacts to find people that are central in static contact networks. However, real contact patterns are not static. In this paper, we investigate if there is additional information in the temporal contact structure for vaccination protocols to exploit. We answer this affirmative by proposing two immunization methods that exploit temporal correlations and showing that these methods outperform a benchmark static-network protocol in four empirical contact datasets under various epidemic scenarios. Both methods rely only on obtainable, local information, and can be implemented in practice. For the datasets directly related to contact patterns of potential disease spreading (of sexually-transmitted and nosocomial infections respectively), the most efficient protocol is to sample people at random and vaccinate their latest contacts. The network datasets are temporal, which enables us to make more realistic evaluations than earlier studies—we use only information about the past for the purpose of vaccination, and about the future to simulate disease outbreaks. Using analytically tractable models, we identify two temporal structures that explain how the protocols earn their efficiency in the empirical data. This paper is a first step towards real vaccination protocols that exploit temporal-network structure—future work is needed both to characterize the structure of real contact sequences and to devise immunization methods that exploit these.
Structure Activity Relationships in Alkylammonium C12-Gemini Surfactants Used as Dermal Permeation Enhancers

The purpose of this study was to determine the ability and the safety of a series of alkylammonium C12-gemini surfactants to act as permeation enhancers for three model drugs, namely lidocaine HCl, caffeine, and ketoprofen. In vitro permeation studies across dermatomed porcine skin were performed over 24 h, after pretreating the skin for 1 h with an enhancer solution 0.16 M dissolved in propylene glycol. The highest enhancement ratio (enhancement ratio (ER) = 5.1) was obtained using G12-6-12, resulting in a cumulative amount of permeated lidocaine HCl of 156.5 μg cm−2. The studies with caffeine and ketoprofen revealed that the most effective gemini surfactant was the one with the shorter spacer, G12-2-12. The use of the latter resulted in an ER of 2.4 and 2.2 in the passive permeation of caffeine and ketoprofen, respectively. However, Azone was found to be the most effective permeation enhancer for ketoprofen, attaining a total of 138.4 μg cm−2 permeated, 2.7-fold over controls. This work demonstrates that gemini surfactants are effective in terms of increasing the permeation of drugs, especially in the case of hydrophilic ionized compounds, that do not easily cross the stratum corneum. Skin integrity evaluation studies did not indicate the existence of relevant changes in the skin structure after the use of the permeation enhancers, while the cytotoxicity studies allowed establishing a relative cytotoxicity profile including this class of compounds, single chain surfactants, and Azone. A dependence of the toxicity to HEK and to HDF cell lines on the spacer length of the various gemini molecules was found.
Enhancement of soluble CD28 levels in the serum of Graves’ disease

Graves’ disease is an autoimmune disease of the thyroid gland mediated by T cells. CD28, a member of costimulatory molecules, plays a pivotal role in regulating T-cell responses. Plasma-soluble CD28 is one form of CD28 in peripheral blood. To investigate the concentrations of soluble CD28 in patients with Graves’ disease, we used a sensitive dual monoclonal antibody sandwich enzyme-linked immunosorbent assay (ELISA) to detect the soluble form of CD28. Our results suggested that mean concentrations of soluble CD28 in plasma of patients with Graves’ disease were 1.79 ±1.52 ng/ml, and levels of soluble CD28 in healthy subjects were only 0.83 ±1.35 ng/ml. Concentrations of soluble CD28 detected in patients with Graves’ disease were significantly higher than those of healthy subjects (p < 0.01). Moreover, there was a significant positive correlation between the concentrations of soluble CD28 in plasma and levels of FT3 (r = 0.663), FT4 (r = 0.624) and TRAb (r = 0.728) in serum, but a negative correlation was found between sCD28 levels and TSH (r = –0.726). Through in vitro experiments we observed that engagement of soluble CD28 protein and B7-1/B7-2 molecules expressed on dendritic cells could exert the secretion of cytokine IL-6, which may promote the production of autoantibody and aggravate Graves’ disease. Therefore, aberrant elevation of plasma-soluble CD28 in patients with Graves’ disease may reflect the dysregulation of immune system, and may serve as a useful biomarker in Graves’ disease diagnosis.
Testing for trustworthiness in scientific software

Two factors contribute to the difficulty of testing scientific software. One is the lack of testing oracles - a means of comparing software output to expected and correct results. The second is the large number of tests required when following any standard testing technique described in the software engineering literature. Due to the lack of oracles, scientists use judgment based on experience to assess trustworthiness, rather than correctness, of their software. This is an approach well established for assessing scientific models. However, the problem of assessing software is more complex, exacerbated by the problem of code faults. This highlights the need for effective and efficient testing for code faults in scientific software. Our current research suggests that a small number of well chosen tests may reveal a high percentage of code faults in scientific software and allow scientists to increase their trust.
Metal-Free ALS Variants of Dimeric Human Cu,Zn-Superoxide Dismutase Have Enhanced Populations of Monomeric Species

Amino acid replacements at dozens of positions in the dimeric protein human, Cu,Zn superoxide dismutase (SOD1) can cause amyotrophic lateral sclerosis (ALS). Although it has long been hypothesized that these mutations might enhance the populations of marginally-stable aggregation-prone species responsible for cellular toxicity, there has been little quantitative evidence to support this notion. Perturbations of the folding free energy landscapes of metal-free versions of five ALS-inducing variants, A4V, L38V, G93A, L106V and S134N SOD1, were determined with a global analysis of kinetic and thermodynamic folding data for dimeric and stable monomeric versions of these variants. Utilizing this global analysis approach, the perturbations on the global stability in response to mutation can be partitioned between the monomer folding and association steps, and the effects of mutation on the populations of the folded and unfolded monomeric states can be determined. The 2- to 10-fold increase in the population of the folded monomeric state for A4V, L38V and L106V and the 80- to 480-fold increase in the population of the unfolded monomeric states for all but S134N would dramatically increase their propensity for aggregation through high-order nucleation reactions. The wild-type-like populations of these states for the metal-binding region S134N variant suggest that even wild-type SOD1 may also be prone to aggregation in the absence of metals.
Economic Evaluation of a School-based Combined Program with a Targeted Pit and Fissure Sealant and Fluoride Mouth Rinse in Japan

Background: In Niigata prefecture, Japan, a system has been developed based on a school-based fluoride mouth rinse program as follows; students with caries susceptible teeth are screened in a school dental examination, and encouraged to receive sealant placement in local dental clinics. However, the cost-effectiveness of sealant application in the public health has been questioned. The aim of this study was to estimate of the cost-effectiveness and cost-benefit ratio for a school-based combined program with fluoride mouth rinse and targeted fissure sealant in children residing in non-fluoridated areas in Japan. Participants: The analysis was based on comparing an intervention group with two cohorts in the 8-year-old (n=66) and 11-year-old (n=58) participating in the combined program for four and seven years, respectively, with a control group of the same grades (n=43 and n=54 respectively). Methods: The study measured mean differences in number of decayed and filled teeth (DFT) between the study groups and a combined program cost per child during study periods. The cost-effectiveness ratio was expressed as an individual annual program cost per DFT averted. In the cost-benefit ratio the mean difference in treatment cost between groups (program benefit) was compared to program cost. Results: The mean reduced DFT differences between groups were 1.44 in 8-year-old and 3.17 in 11-year-old children. The cost-effectiveness ratio was ¥ 493 in the 8-year-old and ¥ 202 in the 11-year-old, respectively. The cost-benefit ratio was 1.84 in 8-year-old children and 2.42 in 11-year-old. Conclusion: This combined program indicated acceptable cost-effectiveness and cost –benefit ratio.
On the crystallinity of silicate dust in the interstellar medium

An accurate knowledge of the mineralogy (chemical composition and crystal structure) of the silicate dust in the interstellar medium (ISM) is crucial for understanding its origin in evolved stars, the physical and chemical processing in the ISM, and its subsequent incorporation into protostellar nebulae, protoplanetary discs and cometary nuclei where it is subjected to further processing. While an appreciable fraction of silicate dust in evolved stars, in protoplanetary discs around pre-main-sequence stars, in debris discs around main-sequence stars and in cometary nuclei is found to be in crystalline form, very recent infrared spectroscopic studies of the dust along the sightline toward the Galactic Centre source Sgr A* placed an upper limit of ∼1.1 per cent on the silicate crystalline fraction, well below the previous estimates of ∼5 or ∼60 per cent derived from the observed 10-μm absorption profile for the local ISM toward Cyg OB2 No. 12. Since the sightline toward Sgr A* contains molecular cloud materials as revealed by the detection of the 3.1- and 6.0-μm water ice absorption features, we argue that by taking into account the presence of ice mantles on silicate cores, the upper limit on the degree of silicate crystallinity in the ISM is increased to ∼3–5 per cent.
A hardware virtual machine for networked reconfiguration

Networked reconfiguration is an enabling technology for cost effective service deployment and maintenance. A hardware virtual machine to enable this networked reconfiguration is presented. An abstract FPGA model is the core of such a hardware virtual machine. Based on this abstract FPGA model, the traditional implementation flow of FPGA has been separated into two parts: the service provider's side and client's side. We show how to split the FPGA design flow to enable this networked reconfiguration and present first results in the efficiency of the byte files for a hardware virtual machine.
Rapid Clothing Retrieval via Deep Learning of Binary Codes and Hierarchical Search

This paper deals with the problem of clothing retrieval in a recommendation system. We develop a hierarchical deep search framework to tackle this problem. We use a pre-trained network model that has learned rich mid-level visual representations in module 1. Then, in module 2, we add a latent layer to the network and have neurons in this layer to learn hashes-like representations while fine-tuning it on the clothing dataset. Finally, module 3 achieves fast clothing retrieval using the learned hash codes and representations via a coarse-to-fine strategy. We use a large clothing dataset where 161,234 clothes images are collected and labeled. Experiments demonstrate the potential of our proposed framework for clothing retrieval in a large corpus.
The Intelligent Campus (iCampus): End-to-End Learning Lifecycle of a Knowledge Ecosystem

A new paradigm of thinking pertaining to a novel holistic intelligent campus (iCampus) environment is proposed, in this paper, in order to enrich and enhance, as well as to transform, the end-to-end learning lifecycle of a knowledge ecosystem. Analogous to the different functions of a biological brain, the central digital nervous system of the campus is comprised of various different interconnected functional intelligences. Each of these intelligent areas is set to perform its specified functional role in a dynamic and coherent inter- and intra-integrative manner within the environment itself. A generalized roadmap has also been devised to encapsulate the concept from within an existing or a new campus setting. Note that the nature of the iCampus proposition is inherently multi-disciplinary and has multi-applicability to other forms of intelligent environment. To capture part of the essence of the concept, some of the key challenges pertinent to the iCampus ecosystem have also been highlighted within the campus value proposition framework.