Miracle-dz/UniFAR-FTUs huggingface dataset:
Cryptography with constant computational overhead

Current constructions of cryptographic primitives typically involve a large multiplicative computational overhead that grows with the desired level of security. We explore the possibility of implementing basic cryptographic primitives, such as encryption, authentication, signatures, and secure two-party computation, while incurring only a constant computational overhead compared to insecure implementations of the same tasks. Here we make the usual security requirement that the advantage of any polynomial-time attacker must be negligible in the input length. We obtain affirmative answers to this question for most central cryptographic primitives under plausible, albeit sometimes nonstandard, intractability assumptions. We start by showing that pairwise-independent hash functions can be computed by linear-size circuits, disproving a conjecture of Mansour, Nisan, and Tiwari (STOC 1990). This construction does not rely on any unproven assumptions and is of independent interest. Our hash functions can be used to construct message authentication schemes with constant overhead from any one-way function. Under an intractability assumption that generalizes a previous assumption of Alekhnovich (FOCS 2003), we get (public and private key) encryption schemes with constant overhead. Using an exponentially strong version of the previous assumption, we get signature schemes of similar complexity. Assuming the existence of pseudorandom generators in NC z with polynomial stretch together with the existence of an (arbitrary) oblivious transfer protocol, we get similar results for the seemingly very complex task of secure two-party computation. More concretely, we get general protocols for secure two-party computation in the semi-honest model in which the two parties can be implemented by circuits whose size is a constant multiple of the size s of the circuit to be evaluated. In the malicious model, we get protocols whose communication complexity is a constant multiple of s and whose computational complexity is slightly super-linear in s. For natural relaxations of security in the malicious model that are still meaningful in practice, we can also keep the computational complexity linear in s. These results extend to the case of a constant number of parties, where an arbitrary subset of the parties can be corrupted. Our protocols rely on non-black-box techniques, and suggest the intriguing possibility that the ultimate efficiency in this area of cryptography can be obtained via such techniques.
Polymer optical fiber sensing

Development of single-mode polymer optical fibres, polymer materials and polymer fibre Bragg gratings has provided new opportunities for optical communication and other related applications. In this paper we report on recent progress and development of polymer optical fibres and devices that would have a significant impact on fibre sensing applications. We also present some of our preliminary experimental work on polymer optical fibre sensing.
Cell attachment on ion implanted titanium surface

Of outmost importance for the successful use of an implant is a good adhesion of the surrounding tissue to the biomaterial. In addition to the surface composition of the implant, the surface topography also influences the properties of the adherent cells. In the present investigation, ion implanted and untreated surfaces were compared for cell adhesion and spreading. The surface topography of the surfaces were analyzed using AFM and the cell studies with SEM. The results of our present investigation is indicative of the fact that ion implanted titanium surface offer better cell binding affinity compared to untreated/polished surface.
Asymptotic path following and velocity control of port-Hamiltonian systems

This paper is devoted to path following control for port-Hamiltonian systems which have energy dissipation mechanism. The control law presented here is extension of an existing passive velocity field controller for fully actuated mechanical systems. The proposed method employs vector fields on co-tangent spaces instead of those on tangent spaces. Since port-Hamiltonian systems can describe a wider class of systems than conventional mechanical ones, the proposed method is applicable to various systems. Futhermore, we can control the velocity directly by this method while it is not possible with the conventional approach.
Augmentation of antidepressants with atypical antipsychotic medications for treatment-resistant major depressive disorder: a meta-analysis.

OBJECTIVE To examine the efficacy and overall tolerability of augmentation of standard antidepressants with atypical antipsychotic agents for treatment-resistant major depressive disorder. DATA SOURCES MEDLINE/PubMed, EMBASE, the Cochrane database, and program syllabi from major psychiatric meetings held since 2000 as well as a number of online clinical trial results registries were searched. Makers of atypical anti-psychotic agents who do not maintain an online clinical study results registry were contacted directly. STUDY SELECTION Double-blind, randomized, placebo-controlled clinical trials assessing adjunctive treatment of standard antidepressants with an atypical antipsychotic agent for treatment-resistant major depressive disorder were identified. DATA EXTRACTION Data were extracted with the use of a pre-coded form. DATA SYNTHESIS Data from 10 clinical trial reports involving a total of 1500 outpatients with treatment-resistant major depressive disorder were identified and combined using a random-effects model. Patients randomized to adjunctive treatment with an atypical antipsychotic agent were more likely to experience remission (risk ratio [RR] = 1.75, p < .0001) or clinical response (RR = 1.35, p = .001) than patients who received adjunctive placebo. Pooled remission and response rates for the 2 treatment groups were 47.4% vs. 22.3% and 57.2% vs. 35.4%, respectively. Although there was no difference in overall discontinuation rates (p = .929) or the rate of discontinuation due to inefficacy (p = .133) between the 2 treatment groups, the rate of discontinuation due to adverse events was lower among placebo-treated patients (RR = 3.38, p < .0001). CONCLUSIONS These results support the utility of augmenting standard antidepressants with atypical antipsychotic agents for treatment-resistant major depressive disorder. An obvious limitation of this work is the absence of data focusing on the use of aripiprazole and ziprasidone. Future short- as well as long-term studies comparing the efficacy, safety, and tolerability of this versus other adjunctive strategies are warranted.
New image retrieval paradigm: logical composition of region categories

We present a novel framework for intelligent search and retrieval by image content composition. Very different from the existing query-by-example paradigm, logical queries are expressed using categories of similar regions without any starting example region. The set of region category representatives constitutes the "photometric region thesaurus" of the image database. Logical composition of region categories expresses the presence and absence of certain types of regions in images to retrieve and allows to integrate visual semantics in the search. Resulting indexing and retrieval implementation turns out to be simple and very fast even on very complex query compositions and large image database. It was tested on a database of 9,995 images from the Corel Photostock.
Interface properties of bio-based composites of polylactic acid and bamboo fibers

Viel, Quentin, "Interface properties of bio-based composites of polylactic acid and bamboo fibers" (2013). Environmental impact plays an ever-increasing role in the industrial production of materials, and because of its importance, the scientific community is examining a wide variety of new materials that are more environmentally friendly. Bioplastics are characterized by the fact that the usual petrochemical resins (polypropylene, polyethylene etc.) are replaced by bio-sourced resins and the reinforcements (glass fibers, carbon fibers etc.) are replaced by natural fibers (bamboo, flax, cotton, etc.). Polylactic acid (PLA) is a biodegradable polymer that is increasingly used in biomedical applications and in packaging. Additionally, bamboo is a promising source of fibers that could be used as reinforcement. In fact, bamboos are grasses with rigid, woody stems, which grow extremely fast and profusely. By virtue of these properties, bamboo is a good candidate as a natural fiber source. Therefore, composites made of a PLA matrix which are reinforced by bamboo fibers may offer many potential advantages as a replacement for less biodegradable alternatives. The mechanical performance of polymer-based composites is often dominated by the interfacial properties between the fibers and matrix, especially with respect to mechanical failure. In this thesis, both untreated fibers and those modified with a NaOH treatment were examined. The shear strength at the interface between a bamboo fiber and the surrounding PLA matrix is quantified. A novel method for processing pull-out-test samples and the details of a test procedure are described. Electron and optical microscopy are both used to examine the failure mode and to quantify the geometry of the fiber-matrix interface. The value of the interfacial shear strength is reported, and its statistical variations are discussed. The results provide important information regarding the future design of natural composites. iv ACKNOWLEDGEMENTS First of all, I would like to thank Dr. Joseph Turner for having been highly concerned of my thesis and for having followed me throughout this year which was very fascinating for me. His patience helped me to realize this thesis in the best possible conditions and for this reason; I could adapted myself at the University of Lincoln quickly. I would like to thank highly Dr. Antonella Esposito, who has helped me many times in the creation of samples, the different presentation that I have made and for the interpretation of the data obtained; and all of these by videoconference (thank you). Prof. Jean-Marc Saiter was very important …
A Two-Dimensional Topic-Aspect Model for Discovering Multi-Faceted Topics

This paper presents the Topic-Aspect Model (TAM), a Bayesian mixture model which jointly discovers topics and aspects. We broadly define an aspect of a document as a characteristic that spans the document, such as an underlying theme or perspective. Unlike previous models which cluster words by topic or aspect, our model can generate token assignments in both of these dimensions, rather than assuming words come from only one of two orthogonal models. We present two applications of the model. First, we model a corpus of computational linguistics abstracts, and find that the scientific topics identified in the data tend to include both a computational aspect and a linguistic aspect. For example, the computational aspect of GRAMMAR emphasizes parsing, whereas the linguistic aspect focuses on formal languages. Secondly, we show that the model can capture different viewpoints on a variety of topics in a corpus of editorials about the Israeli-Palestinian conflict. We show both qualitative and quantitative improvements in TAM over two other state-of-the-art topic models.
Image-Guided Radiotherapy Using a Modified Industrial Micro-CT for Preclinical Applications

Purpose/Objective Although radiotherapy is a key component of cancer treatment, its implementation into pre-clinical in vivo models with relatively small target volumes is frequently omitted either due to technical complexity or expected side effects hampering long-term observational studies. We here demonstrate how an affordable industrial micro-CT can be converted into a small animal IGRT device at very low costs. We also demonstrate the proof of principle for the case of partial brain irradiation of mice carrying orthotopic glioblastoma implants. Methods/Materials A commercially available micro-CT originally designed for non-destructive material analysis was used. It consists of a CNC manipulator, a transmission X-ray tube (10–160 kV) and a flat-panel detector, which was used together with custom-made steel collimators (1–5 mm aperture size). For radiation field characterization, an ionization chamber, water-equivalent slab phantoms and radiochromic films were used. A treatment planning tool was implemented using a C++ application. For proof of principle, NOD/SCID/γc−/− mice were orthotopically implanted with U87MG high-grade glioma cells and irradiated using the novel setup. Results The overall symmetry of the radiation field at 150 kV was 1.04±0.02%. The flatness was 4.99±0.63% and the penumbra widths were between 0.14 mm and 0.51 mm. The full width at half maximum (FWHM) ranged from 1.97 to 9.99 mm depending on the collimator aperture size. The dose depth curve along the central axis followed a typical shape of keV photons. Dose rates measured were 10.7 mGy/s in 1 mm and 7.6 mGy/s in 5 mm depth (5 mm collimator aperture size). Treatment of mice with a single dose of 10 Gy was tolerated well and resulted in central tumor necrosis consistent with therapeutic efficacy. Conclusion A conventional industrial micro-CT can be easily modified to allow effective small animal IGRT even of critical target volumes such as the brain.
Accommodating the ecological fallacy in disease mapping in the absence of individual exposures

In health exposure modeling, in particular, disease mapping, the ecological fallacy arises because the relationship between aggregated disease incidence on areal units and average exposure on those units differs from the relationship between the event of individual incidence and the associated individual exposure. This article presents a novel modeling approach to address the ecological fallacy in the least informative data setting. We assume the known population at risk with an observed incidence for a collection of areal units and, separately, environmental exposure recorded during the period of incidence at a collection of monitoring stations. We do not assume any partial individual level information or random allocation of individuals to observed exposures. We specify a conceptual incidence surface over the study region as a function of an exposure surface resulting in a stochastic integral of the block average disease incidence. The true block level incidence is an unavailable Monte Carlo integration for this stochastic integral. We propose an alternative manageable Monte Carlo integration for the integral. Modeling in this setting is immediately hierarchical, and we fit our model within a Bayesian framework. To alleviate the resulting computational burden, we offer 2 strategies for efficient model fitting: one is through modularization, the other is through sparse or dimension‐reduced Gaussian processes. We illustrate the performance of our model with simulations based on a heat‐related mortality dataset in Ohio and then analyze associated real data.
Battery-free Visible Light Sensing

We present the design of the first Visible Light Sensing (VLS) system that consumes only tens of μWs of power to sense and communicate. Unlike most existing VLS systems, we require no modification to the existing light infrastructure since we use unmodulated light as a sensing medium. We achieve this by designing a novel mechanism that uses solar cells to achieve a sub-μW power consumption for sensing. Further, we devise an ultra-low power transmission mechanism that backscatters sensor readings and avoids the processing and computational overhead of existing sensor systems. Our initial results show the ability to detect and transmit hand gestures or presence of people up to distances of 330m at a peak power of μWs. Further, we demonstrate that our system can operate in diverse light conditions (100 lx to 80 klx) where existing VLS designs fail due to saturation of the transimpedance amplifier (TIA).
Nonlinear Price Incentives and Dynamic Brand Choice : B 2 B Purchasing Decisions with Quantity Discounts

I present an empirical framework to capture the dynamic decision-making process of an agent choosing between manufacturers that compete through quantity discounts. I apply the model to a rich data set provided by a multinational medical device manufacturer, in which I observe the daily ordering habits of doctors. Unique to this market, the doctor functions as a retailer and faces a cost-minimization problem based on his choice of prescriptions made during the day. Reducedform evidence suggests that doctors align their order sizes with the nonlinear incentives the focal manufacturer o ers. After estimation of the structural model, I nd the magnitude of the distortion. Conditional on one patient already receiving a product from the focal manufacturer, the doctor is 12 times more likely to prescribe a second product from that manufacturer. This increase in the prescription probability is aligned with the rst quantity threshold present in the focal rm's price schedule, and I nd a larger increase in prescription probability at the other quantity threshold. Next, I analyze di erent price schedules by adjusting the threshold levels and per-unit price discounts and nd one system that increases rm pro tability by 7% without changing the initial and nal tier per-unit price of the rm's products. The best single-price plan only increases pro tability by 3.5% in comparison. Also, I examine the pro tability implications of volume discounts in two di erent counterfactual scenarios; one in which 60% of the patients require a re ll of their previous prescription and the other with 0% re ll patients. I nd volume discounts provide the greatest pro tability gains over a single-tier pricing system in the setting with 60% re ll patients. In the other scenario, some of the optimal nonlinear price schedules actually result in less pro tability than a simple single-tier pricing system. Finally, I conclude with comments on the eld implementation of a new price schedule by the focal rm, which resulted in a 9% increase in revenue.
Hardware-software collaborative complexity reduction scheme for the emerging HEVC intra encoder

High Efficiency Video Coding (HEVC/H.265) is an emerging standard for video compression that provides almost double compression efficiency at the cost of major computational complexity increase as compared to current industry-standard Advanced Video Coding (AVC/H.264). This work proposes a collaborative hardware and software scheme for complexity reduction in an HEVC Intra encoding system, with run-time adaptivity. Our scheme leverages video content properties which drive the complexity management layer (software) to generate a highly probable coding configuration. The intra prediction size and direction are estimated for the prediction unit which provides reduced computational-complexity. At the hardware layer, specialized coprocessors with enhanced reusability are employed as accelerators. Additionally, depending upon the video properties, the software layer administers the energy management of the hardware coprocessors. Experimental results show that a complexity reduction of up to 60 % and the energy reduction up to 42 % are achieved.
RATES OF CEREBRAL GLUCOSE UTILIZATION IN RATS ANAESTHETIZED WITH PHENOBARBITONE

Abstract— 1 Intraperitoneal injection of phenobarbitone (250 mg/kg body wt.) into rats caused increased brain concentrations of glucose (100 per cent), glucose 6‐phosphate (16 per cent) and ATP (12 per cent) and decreased concentrations of lactate (33 per cent) and ADP (15 per cent). A 31 per cent decrease in glutamate content was not statistically significant. No significant change occurred in the cerebral contents of glycogen or creatine phosphate. 1 The rates of increase in the brain of specific activities, in the first few minutes after systemic injection of [U‐14C]glucose, of glucose, lactate, glutamate and glycogen were all halved by phenobarbitone. Calculated flux rates of 14C from glucose into metabolic intermediates and from lactate to glutamate were also decreased by 27–47 per cent; the effects on rate constants showed inconsistencies. The rate constants for conversion of glucose to lactate and to glutamate were decreased by 60–70 per cent, but that from lactate to glutamate was virtually unchanged. The rate constant for the flux from glucose to glycogen was reduced by 39 per cent, but the accumulation of glucose meant that the actual flux into glycogen increased by 20 per cent. 1 The results are interpreted in terms of an effect of the barbiturate not only on glucose transport, but also at an enzymic stage in glycolysis, possibly hexokinase or phosphofructokinase.
Multilingual Named Entity Recognition using Parallel Data and Metadata from Wikipedia

In this paper we propose a method to automatically label multi-lingual data with named entity tags. We build on prior work utilizing Wikipedia metadata and show how to effectively combine the weak annotations stemming from Wikipedia metadata with information obtained through English-foreign language parallel Wikipedia sentences. The combination is achieved using a novel semi-CRF model for foreign sentence tagging in the context of a parallel English sentence. The model outperforms both standard annotation projection methods and methods based solely on Wikipedia metadata.
EMG-based pattern recognition with kinematics information for hand gesture recognition

Predicting movement intention based on pattern recognition of biosignals are becoming increasingly important in many clinical and research applications. The main idea of these technologies is to use a human-in-the-loop system for controlling several hardware devices, in which the identification of the user intention is the most challenging aspect. Electromyography (EMG) provides biological signals that can be used in various applications including identifying neuromuscular diseases, control for prosthetic and assistive devices, human-machine interaction, etc. Decoding upper-limb gestures from EMG could help to develop human-computer interfaces that increase the quality of life of the disabled or aged people. Implementation of the EMG-based pattern recognition is not easy to be accomplished due to some difficulties, among them that EMG are time-varying and highly nonlinear. Kinematics information (i.e. position, velocity, acceleration) could provide valuable information in an EMG-based pattern recognition process to improve classification. This work describes a comparative study of two EMG-based pattern recognition algorithms aimed at decoding upper-limb gestures. Results show that algorithm using kinematics information and EMG data was better in classification of five movements at the upper-limb level that algorithm using only EMG data.
The Persistence of European Bond Fund Performance: Does Conditioning Information Matter?

In this paper we investigate if past performance can be used to predict future performance in the European bond fund market. Both unconditional and conditional measures of performance are considered. To our knowledge, this is the first study, which directly analyses the impact of conditioning information in assessing the persistence phenomenon in relation to bond funds. We find empirical evidence that indicates consistency of European bond performance. This evidence is particularly strong for the case of Spanish bond funds. Some evidence of persistence is also found for French and German bond funds. Additionally, it seems that the persistence is concentrated mainly in the poor performing funds. The results were similar whatever methodology, cross-sectional regression analysis or contingency tables, is used for assessing performance persistence. Our findings indicate that the evidence of performance persistence decreases when we consider conditional alphas, particularly for the multi-index model, which suggests that some of the persistence phenomenon is driven by time-varying betas.