Miracle-dz/UniFAR-FTUs huggingface dataset:
Secure and energy-efficient multicast routing in smart grids

A smart grid is a power system that uses information and communication technology to operate, monitor, and control data flows between the power generating source and the end user. It aims at high efficiency, reliability, and sustainability of the electricity supply process that is provided by the utility centre and is distributed from generation stations to clients. To this end, energy-efficient multicast communication is an important requirement to serve a group of residents in a neighbourhood. However, the multicast routing introduces new challenges in terms of secure operation of the smart grid and user privacy. In this paper, after having analysed the security threats for multicast-enabled smart grids, we propose a novel multicast routing protocol that is both sufficiently secure and energy efficient.We also evaluate the performance of the proposed protocol by means of computer simulations, in terms of its energy-efficient operation.
Extraction of Inter-Aural Time Differences Using a Spiking Neuron Network Model of the Medial Superior Olive

The mammalian auditory system is able to extract temporal and spectral features from sound signals at the two ears. One important cue for localization of low-frequency sound sources in the horizontal plane are inter-aural time differences (ITDs) which are first analyzed in the medial superior olive (MSO) in the brainstem. Neural recordings of ITD tuning curves at various stages along the auditory pathway suggest that ITDs in the mammalian brainstem are not represented in form of a Jeffress-type place code. An alternative is the hemispheric opponent-channel code, according to which ITDs are encoded as the difference in the responses of the MSO nuclei in the two hemispheres. In this study, we present a physiologically-plausible, spiking neuron network model of the mammalian MSO circuit and apply two different methods of extracting ITDs from arbitrary sound signals. The network model is driven by a functional model of the auditory periphery and physiological models of the cochlear nucleus and the MSO. Using a linear opponent-channel decoder, we show that the network is able to detect changes in ITD with a precision down to 10 μs and that the sensitivity of the decoder depends on the slope of the ITD-rate functions. A second approach uses an artificial neuronal network to predict ITDs directly from the spiking output of the MSO and ANF model. Using this predictor, we show that the MSO-network is able to reliably encode static and time-dependent ITDs over a large frequency range, also for complex signals like speech.
Evaluation of Thai speech intelligibility based on noise reduction techniques for cochlear implants

Speech intelligibility improvement in noisy environments for cochlear implant (CI) users is a difficult task which has encountered numerous challenges, such as differences between languages. Most studies have been carried out using the English language. The objective of the study was to evaluate Thai speech intelligibility based on noise reduction (NR) algorithms as a pre-processing approach in CIs. Two NR algorithms, namely multi-band spectral subtraction (MBSS) and Weiner filter (WF) algorithms, were chosen. Monosyllabic and bisyllabic Thai words were corrupted by different noises (speech-shaped noise and babble noise) at SNRs of 0, 5, and 10 dB. Then, the noisy speech was enhanced using NR algorithms. The enhanced speech was fed into a n-of-m coding strategy to synthesize vocoded speech. The vocoded speech was evaluated by ten normal-hearing (NH) listeners. The experimental results showed that intelligibility performance was slightly improved for the MBSS algorithm and considerably improved for the WF algorithm in some conditions. The intelligibility performance of bisyllabic words was significantly more improved than that of monosyllabic words in all conditions.
Covalent Immobilization of (-)-Riboflavin on Polymer Functionalized Silica Particles: Application in the Photocatalytic E→Z Isomerization of Polarized Alkenes.

The covalent immobilization of the biomimetic, photo-organocatalyst (-)-riboflavin on silica micro- and nanoparticles via atom transfer radical polymerization (ATRP) is disclosed. Given the effectiveness of (-)-riboflavin as a versatile, environmentally benign photocatalyst, an immobilization strategy based on acrylate-linker modification of the catalyst core and controlled polymerization on initiator pre-functionalized silica particles has been developed. Validation of this approach is demonstrated in the E→Z isomerization of a benchmark cinnamonitrile (Z/E up to 88:12) with 0.97 mol % catalyst loading. Characterization of the immobilized photocatalyst supports covalent embedding of the catalyst in the polymeric brushes on the silica particle surface.
Recognition of Group Mobility Level and Group Structure with Mobile Devices

Monitoring group mobility and structure is crucial for understanding group activities and social relations. In this paper, we develop algorithms for fine-grained mobility classification and structure recognition of social groups utilizing mobile devices. First, we present a method that recognizes four levels of group mobility, including stationary, strolling, walking, and running. Second, using multiple types of mobile sensors, a novel relative position relationship estimation algorithm is developed to understand different moving group structures. We have conducted real-life experiments in which 12 volunteers moved in different small groups either in an office building or a shopping mall with various speeds and structures. Experimental results show that our approach achieves an accuracy of 99.5 percent in group mobility level classification and about 80 percent in group structure recognition.
Hepatocyte Heparan Sulfate Is Required for Adeno-Associated Virus 2 but Dispensable for Adenovirus 5 Liver Transduction In Vivo

ABSTRACT Adeno-associated virus 2 (AAV2) and adenovirus 5 (Ad5) are promising gene therapy vectors. Both display liver tropism and are currently thought to enter hepatocytes in vivo through cell surface heparan sulfate proteoglycans (HSPGs). To test directly this hypothesis, we created mice that lack Ext1, an enzyme required for heparan sulfate biosynthesis, in hepatocytes. Ext1 HEP mutant mice exhibit an 8-fold reduction of heparan sulfate in primary hepatocytes and a 5-fold reduction of heparan sulfate in whole liver tissue. Conditional hepatocyte Ext1 gene deletion greatly reduced AAV2 liver transduction following intravenous injection. Ad5 transduction requires blood coagulation factor X (FX); FX binds to the Ad5 capsid hexon protein and bridges the virus to HSPGs on the cell surface. Ad5.FX transduction was abrogated in primary hepatocytes from Ext1 HEP mice. However, in contrast to the case with AAV2, Ad5 transduction was not significantly reduced in the livers of Ext1 HEP mice. FX remained essential for Ad5 transduction in vivo in Ext1 HEP mice. We conclude that while AAV2 requires HSPGs for entry into mouse hepatocytes, HSPGs are dispensable for Ad5 hepatocyte transduction in vivo. This study reopens the question of how adenovirus enters cells in vivo. IMPORTANCE Our understanding of how viruses enter cells, and how they can be used as therapeutic vectors to manage disease, begins with identification of the cell surface receptors to which viruses bind and which mediate viral entry. Both adeno-associated virus 2 and adenovirus 5 are currently thought to enter hepatocytes in vivo through heparan sulfate proteoglycans (HSPGs). However, direct evidence for these conclusions is lacking. Experiments presented herein, in which hepatic heparan sulfate synthesis was genetically abolished, demonstrated that HSPGs are not likely to function as hepatocyte Ad5 receptors in vivo. The data also demonstrate that HSPGs are required for hepatocyte transduction by AAV2. These results reopen the question of the identity of the Ad5 receptor in vivo and emphasize the necessity of demonstrating the nature of the receptor by genetic means, both for understanding Ad5 entry into cells in vivo and for optimization of Ad5 vectors as therapeutic agents.
Towards Human-Like Conversational Search Systems

Voice search is currently widely available on the majority of mobile devices via use of Virtual Personal Assistants. However, despite its general availability, the use of voice interaction remains sporadic and is limited to basic search tasks such as checking weather updates and looking up answers to factual queries. Present-day voice search systems struggle to use relevant contextual information to maintain conversational state, and lack conversational initiative needed to clarify user's intent, which hampers their usability and prevents users from engaging in more complex interaction activities. This research investigates the potential of a hypothesised interactive information retrieval system with human-like conversational abilities. To this end, we propose a series of usability studies that involve a working prototype of a conversational system that uses real time speech synthesis. The proposed experiments seek to provide empirical evidence that enabling a voice search system with human-like conversational abilities can lead to increased likelihood of its adoption.
People detection based on appearance and motion models

The main contribution of this paper is a new people detection algorithm based on motion information. The algorithm builds a people motion model based on the Implicit Shape Model (ISM) Framework and the MoSIFT descriptor. We also propose a detection system that integrates appearance, motion and tracking information. Experimental results over sequences extracted from the TRECVID dataset show that our new people motion detector produces results comparable to the state of the art and that the proposed multimodal fusion system improves the obtained results combining the three information sources.
Macrophage Targeted Nanoparticles for Antiretroviral (ARV) Delivery.

Objective To reduce the amount of the antiretroviral (ARV) nevirapine necessary to achieve therapeutic concentrations using macrophage targeted nanoparticles. Methods Core-shell nanoparticles were prepared from FDA approved, biodegradable and biocompatible polymers, with poly(lactic-co-glycolic) acid (PLGA) as the core and chitosan (CS) as the shell using a water/oil/water method. Nevirapine was encapsulated in the core of the nanoparticles. β-glucan (GLU) was adsorbed to the surface of the nanoparticle. Macrophage uptake and intracellular nevirapine concentrations were determined by fluorescence imaging and ultra-performance liquid chromatography/mass spectroscopy (UPLC-MS). Optical imaging was employed to characterize the biodistribution of nanoparticles following intravenous injection in CD-1 mice. Results We synthesized spherical shaped 190 nm GLU-CS-PLGA nanoparticles that provide controlled release of nevirapine. In THP-1 macrophage the uptake of PLGA and CS- PLGA nanoparticles was less compared to targeted GLU-CS-PLGA nanoparticles. THP-1 macrophage were dosed with free nevirapine (10 μg/well) and GLU-CS- PLGA nanoparticles containing 1/10 the concentration of free nevirapine (1 μg nevirapine/well). The intracellular concentration of nevirapine was the same for both nanoparticles and free nevirapine at 2 and 24 hrs. No significant change in THP-1 macrophage viability was observed in the presence of nanoparticles relative to the control. Ex vivo imaging demonstrates that nanoparticles are predominantly found in the liver and kidney and at 24 hr there is still a large amount of nanoparticles in the body. Conclusion These data demonstrate that the total dose of nevirapine delivered by GLU-CS-PLGA nanoparticles can be greatly reduced, to limit side effects, while still providing maximal ARV activity in a known cellular reservoir.
APPLICATION OF AN IMPROVED MODEL FOR THE IDENTIFICATION OF MATERIAL PARAMETERS

Elastic material constants of thick plates can be identified by combining a range of measured natural frequencies with an accurate numerical model for the theoretical predictions. To deal with thick plates, a model that takes transverse shear effects into account is necessary. Since modeling errors affect the estimates in a systematic way, an accurate numerical model is of primary importance. Compared to a model used previously, an improved, more accurate plain model is studied here for the purpose of identification. This new advanced model is used to assess the systematic errors in the identification associated with the previous model It is shown that due to the errors in the previous model, the transverse shear moduli were overestimated, whereas the in-plane parameters were practically unaffected. The new model is implemented in the identification procedure whereby systematic errors have been significantly reduced. Experimental results are presented that support the theoretical investigations. Parameter.
Image super-resolution based on dictionary learning and anchored neighborhood regression with mutual incoherence

In this paper, we employ unified mutual coherence between the dictionary atoms and atoms/samples when learning the dictionary and sampling anchored neighborhoods respectively for image super-resolution (SR) application algorithm. On one hand, an incoherence promoting term in dictionary learning for SR is introduced to encourage dictionary atoms, associated to different anchored regressors, to be as independent as possible, while still allowing for different regressors to share same samples. On the other hand, a unified form with mutual coherence between dictionary atoms and training samples is proposed when we group neighborhoods of samples centered on each atom and find the nearest neighbors for input samples in image super-resolution. Extensive experimental results on commonly used datasets demonstrate that our method outperforms state-of-the-art methods by obtaining compelling results with improved quality, such as sharper edges, finer textures and higher structural similarity.
Development and Preclinical Validation of a Cysteine Knottin Peptide Targeting Integrin αvβ6 for Near-infrared Fluorescent-guided Surgery in Pancreatic Cancer

Purpose: Intraoperative near-infrared fluorescence (NIRF) imaging could help stratification for the proper primary treatment for patients with pancreatic ductal adenocarcinoma (PDAC), and achieve complete resection, as it allows visualization of cancer in real time. Integrin αvβ6, a target specific for PDAC, is present in >90% of patients, and is able to differentiate between pancreatitis and PDAC. A clinically translatable αvβ6-targeting NIRF agent was developed, based on a previously developed cysteine knottin peptide for PET imaging, R01-MG, and validated in preclinical mouse models. Experimental Design: The applicability of the agent was tested for cell and tissue binding characteristics using cell-based plate assays, subcutaneous, and orthotopic pancreatic models, and a transgenic mouse model of PDAC development (Pdx1-Cretg/+;KRasLSL G12D/+;Ink4a/Arf−/−). IRDye800CW was conjugated to R01-MG in a 1:1 ratio. R01-MG-IRDye800, was compared with a control peptide and IRDye800 alone. Results: In subcutaneous tumor models, a significantly higher tumor-to-background ratio (TBR) was seen in BxPC-3 tumors (2.5 ± 0.1) compared with MiaPaCa-2 (1.2 ± 0.1; P < 0.001), and to the control peptide (1.6 ± 0.4; P < 0.005). In an orthotopic tumor model, tumor-specific uptake of R01-MG-IRDye800 was shown compared with IRDye800 alone (TBR 2.7 vs. 0.86). The fluorescent signal in tumors of transgenic mice was significantly higher, TBR of 3.6 ± 0.94, compared with the normal pancreas of wild-type controls, TBR of 1.0 ± 0.17 (P < 0.001). Conclusions: R01-MG-IRDye800 shows specific targeting to αvβ6, and holds promise as a diagnostic and therapeutic tool to recognize PDAC for fluorescence-guided surgery. This agent can help improve the stratification of patients for a potentially curative, margin-negative resection. Clin Cancer Res; 24(7); 1667–76. ©2018 AACR.
Topic model and similarity calculation of text on spark

Since the 21st century, with the popularization and development of the Internet, the volume of text data on the Internet has been increasing rapidly. To extract the theme of people, need from text content, at the same time in order to solve problems such as excessive dimension of vector in model and dependence of word frequency, David M. Blei put forward a helpful and efficient method based on topic model, which also known as implicit Dirichlet distribution (Latent Dirichlet Allocation). The LDA model uses the Gibbs sampling method to estimate the parameters of the document-topic, topic-word distribution pattern, and express the text content as the probability model of the subject model to calculate the similarity of the document. In this paper, Spark as a LDA algorithm to run the computing platform, the use of Spark parallel computing advantages of a large number of text corpus processing, and on the basis of LDA proposed a document similarity calculation method.
Regional Assessment of Human Fecal Contamination in Southern California Coastal Drainages

Host-associated genetic markers that allow for fecal source identification have been used extensively as a diagnostic tool to determine fecal sources within watersheds, but have not been used in routine monitoring to prioritize remediation actions among watersheds. Here, we present a regional assessment of human marker prevalence among drainages that discharge to the U.S. southern California coast. Approximately 50 samples were analyzed for the HF183 human marker from each of 22 southern California coastal drainages under summer dry weather conditions, and another 50 samples were targeted from each of 23 drainages during wet weather. The HF183 marker was ubiquitous, detected in all but two sites in dry weather and at all sites during wet weather. However, there was considerable difference in the extent of human fecal contamination among sites. Similar site ranking was produced regardless of whether the assessment was based on frequency of HF183 detection or site average HF183 concentration. However, site ranking differed greatly between dry and wet weather. Site ranking also differed greatly when based on enterococci, which do not distinguish between pollution sources, vs. HF183, which distinguishes higher risk human fecal sources from other sources, indicating the additional value of the human-associated marker as a routine monitoring tool.
Representing and decoding rank order codes using polychronization in a network of spiking neurons

The introduction of axonal delays in networks of spiking neurons has enhanced the representational capabilities of neural networks, whilst also providing more biological realism. Approaches in neural coding such as rank order coding and polychronization have exploited the precise timing of action potential observed in real neurons. In a rank order code information is coded in the order of firing of a pool of neurons; on the other hand with polychronization it is the time of arrival of different spikes at the postsynaptic neuron which triggers different post-synaptic responses, with the axonal delays compensating for different timings in the afferents. In this paper we propose a model in which rank order coding is used to represent an arbitrary symbol, and a polychronous layer is used to decode, represent and recall that symbol. To prove that the polychronous layer is able to do this a detector neuron is trained with a supervised learning strategy and associated with a single code. According to this premise the detector neuron only fires on the appearance of the associated code, even in the presence of noise. Tests prove that rank order coding and polychronization can be coupled to code and decode information such as intensity or significance using timing information in spiking neural networks in an effective way.
A functional 19-base pair deletion polymorphism of dihydrofolate reductase (DHFR) and risk of breast cancer in multivitamin users.

BACKGROUND Dihydrofolate reductase (DHFR) converts dihydrofolate (DHF) into tetrahydrofolate (THF) and plays an essential role in cell metabolism and cellular growth. Folic acid from multivitamins needs to be reduced by DHFR before it participates in cellular reactions. OBJECTIVES We examined the relation of a 19-base pair (bp) deletion polymorphism of the DHFR gene with the risk of breast cancer by using data from the Long Island Breast Cancer Study Project, a population-based case-control study. We also investigated the transcriptional effect of this deletion polymorphism. DESIGN Dietary data and habitual use of multivitamins were assessed from a modified Block food-frequency questionnaire (FFQ). Genotypes of DHFR were ascertained from 1062 case subjects and 1099 control subjects by allele-specific polymerase chain reaction. Unconditional logistic regression was used to estimate odds ratios (ORs) and 95% CIs. RESULT Although the DHFR 19-bp deletion polymorphism was not associated with overall breast cancer risk, we observed a borderline significant additive interaction (P = 0.06) between the DHFR genotype and multivitamin use. The -19-bp allele was associated with greater breast cancer risk in multivitamin users (51.2% of the study population) with an OR of 1.26 (95% CI: 0.96, 1.66) and 1.52 (95% CI: 1.08, 2.13) for the +/- and -/- genotypes, respectively (P for trend = 0.02) than in multivatimin nonusers. A dose-dependent relation (P for trend < 0.001) between DHFR expression and the deletion genotype was observed. Compared with the subjects with the 19-bp +/+ genotype, subjects with the -/- genotype had 4.8-fold DHFR mRNA levels. CONCLUSIONS The DHFR 19-bp deletion polymorphism affects the transcription of DHFR gene in humans. Multivitamin supplements may place a subgroup of women (ie, those with the -19-bp allele) at elevated risk of developing breast cancer.
A System-on-Chip Crystal-Less Wireless Sub-GHz Transmitter

This paper presents a fully integrated system-on-chip wireless transmitter that has no need for an external quartz crystal frequency reference. Instead, a nontrimmable $LC$ oscillator (LCO) is implemented, operating at a fixed frequency of roughly 3.2 GHz. This LCO serves as the accurate frequency reference of the transmitter and is used to derive a frequency in the sub-GHz range for wireless applications via a fractional phase-locked loop. The digital functionality required for the frequency generation and thus for the wireless operation is performed by an 8-b microcontroller. The calibration data as well as the application specific firmware are stored in an integrated EEPROM. An initial frequency accuracy of ±52 ppm over a temperature of −20 °C to 85 °C is achieved using only two temperature insertions for the calibration. The device covers a continuous frequency range of 10–960 MHz and provides an ASK and GFSK operation. A low harmonic power amplifier was implemented to overcome design issues due to injection modulation effects. The chip is implemented in a 130 nm standard CMOS process and constitutes a new approach for a fully integrated wireless sub-GHz transmitter that is competitive to state-of-the-art quartz crystal-based transmitters as well as to already existing crystal-less architectures.