Miracle-dz/UniFAR-FTUs huggingface dataset:
Do Political Liberals Need the Truth

In this thesis, I defend John Rawls’s assertion that political liberalism does not use the concept of truth. I respond to objections from Joshua Cohen and David Estlund. I argue that Cohen fails to show that public reason needs a minimalist conception of truth, since individuals with a range of conceptions of moral truth can meet the requirements of public reason. I dispute Estlund’s argument that the liberal principle of legitimacy is merely insular. Estlund assumes that the claim that the liberal principle of legitimacy is reasonable is no different than the claim that the principle is acceptable to reasonable persons. I argue that this assumption is incorrect, and that therefore the liberal principle of legitimacy is justifiable on the grounds that it is reasonable. I argue that political liberals need not worry that doing without the concept of truth will undermine the semantic coherence or objectivity of political liberalism. INDEX WORDS: John Rawls, Political liberalism, Truth, David Estlund, Joshua Cohen, Public reason DO POLITICAL LIBERALS NEED THE TRUTH?
Antidepressant and Neurocognitive Effects of Isoflurane Anesthesia versus Electroconvulsive Therapy in Refractory Depression

Background Many patients have serious depression that is nonresponsive to medications, but refuse electroconvulsive therapy (ECT). Early research suggested that isoflurane anesthesia may be an effective alternative to ECT. Subsequent studies altered drug, dose or number of treatments, and failed to replicate this success, halting research on isoflurane's antidepressant effects for a decade. Our aim was to re-examine whether isoflurane has antidepressant effects comparable to ECT, with less adverse effects on cognition. Method Patients with medication-refractory depression received an average of 10 treatments of bifrontal ECT (n = 20) or isoflurane (n = 8) over 3 weeks. Depression severity (Hamilton Rating Scale for Depression-24) and neurocognitive responses (anterograde and retrograde memory, processing speed and verbal fluency) were assessed at Pretreatment, Post all treatments and 4-week Follow-up. Results Both treatments produced significant reductions in depression scores at Post-treatment and 4-week Follow-up; however, ECT had modestly better antidepressant effect at follow-up in severity-matched patients. Immediately Post-treatment, ECT (but not isoflurane) patients showed declines in memory, fluency, and processing speed. At Follow-up, only autobiographical memory remained below Pretreatment level for ECT patients, but isoflurane patients had greater test-retest neurocognitive score improvement. Conclusions Our data reconfirm that isoflurane has an antidepressant effect approaching ECT with less adverse neurocognitive effects, and reinforce the need for a larger clinical trial.
Implementation of Image Descriptor Based on SURF and DCD

Image retrieval is one of the most exciting and fastest growing research areas in the field of multimedia technology. In this paper, we present and implement an image descriptor that extracts the feature of image using combination of SURF (Speed Up Robust Feature) and DCD (Dominant Color Descriptor) scheme. To evaluate the performance of implemented algorithm, we assess the performance of simulation in terms of average precision on two image database commonly used. The result shows that the proposed approach obtain an enough results which are applicable to mobile environments.
Lost in Space: Geolocation in Event Data

Improving geolocation accuracy in text data has long been a goal of automated text processing. We depart from the conventional method and introduce a two-stage supervised machine-learning algorithm that evaluates each location mention to be either correct or incorrect. We extract contextual information from texts, i.e., N-gram patterns for location words, mention frequency, and the context of sentences containing location words. We then estimate model parameters using a training data set and use this model to predict whether a location word in the test data set accurately represents the location of an event. We demonstrate these steps by constructing customized geolocation event data at the subnational level using news articles collected from around the world. The results show that the proposed algorithm outperforms existing geocoders even in a case added post hoc to test the generality of the developed algorithm.
Ultrasound image despeckling using singular value decomposition

The contrast and resolutions of ultrasound images may be degraded by a form of signal dependent noise known as speckle. Speckle pattern is multiplicative in nature and it depends on the structure of the object to be imaged and methods used for image acquisition. Despeckling is necessary to improve the human as well as machine interpretation of ultrasound images and hence it is used as a preprocessing step for many ultrasound image processing tasks such as segmentation and registration. This article proposes an effective despeckling technique based on Singular Value Decomposition on varying sized subdivisions. Quadtree representation along with higher order statistics is used to generate varying sized subimages. The performance is also compared with similar approach based on Principal Component Analysis.
Fibrinogen and Fibronectin Binding Activity and Immunogenic Nature of Choline Binding Protein M

Background: Choline-binding proteins (CBPs) are a group of surface-exposed proteins, which play crucial and physiological roles in Streptococcus pneumoniae. The novel member of CBPs, choline-binding protein M (CbpM) may have binding activity to plasma proteins. This study aimed to clone and express CbpM and demonstrate its interaction with plasma proteins and patients’ sera. Methods: The total length of cbpM gene was cloned in pET21a vector and expressed in BL21 expression host. Verification of recombinant protein was evaluated by Western blot using anti-His tag monoclonal antibody. Binding ability of the recombinant protein to plasma proteins and the interaction with patients’ sera were assessed by Western blot and ELISA methods. Results: The cbpM gene was successfully cloned into pET21a and expressed in BL21 host. Binding activity to fibronectin and fibrinogen and antibody reaction of CbpM to patients’ sera was demonstrated by Western blot and ELISA methods, respectively. Conclusion: CbpM is one of the pneumococcal surface-exposed proteins, which mediates pneumococcal binding to fibronectin and fibrinogen proteins.
Study on Venture Investment Model Base on Signaling Game

This paper present a new method and model to analysis the venture investment decision based on the signaling game. We analyze and describe the venture investment decision making of two-period using mathematics models under the uncertainty to establish our option value model of venture investment. We analyze the asymmetric information between venture enterprises and venture investment corporations. Boil down the game between venture enterprises and venture investment corporations to signaling game under the incompleteness information. Get a solution of combination perfect Bayesian equilibrium.
RESEARCH OF ADAPTIVE PROGRAM DESIGN ALGORITHM BASED ON AGENT

The current computer program is artificially design ed to execute the process, which has the weakness o f passivity, rigidity and lack of flexibility. This p aper proposes a method of program design based on reinforcement learning mechanism, and realizes the corresponding algorithm. According to the environment and requirements, the agent can choose executive process independently and arrive at the optimal result by learning, realize the layered cal ls. Using this method, the executing program is dec isionmaking, has a way to realize the adaption, and redu ces the dependence on designer. The result shows th at the method can achieve satisfactory execution effic i ncy.
Discovery of a 136 Millisecond Radio and X-ray Pulsar in Snr G54.1+0.3

We report the discovery of a pulsar with period P = 136 ms and dispersion measure 308 cm −3 pc in a deep observation of the supernova remnant (SNR) G54.1+0.3 with t he Arecibo radio telescope. Timing measurements of the new pulsar, J1930+1852, reveal a characteristic age o f P/2Ṗ = 2900 yr and spin-down luminositẏ E = 1.2×1037erg s−1. We have subsequently searched archival ASCA X-ray data of this SNR, and detect pulsations with a consistent period. These findings ensure that PSR J193 0+ 852 is the pulsar that powers the “Crab-like” SNR G54.1+0.3. Together with existing Chandra observations of the SNR, we derive an X-ray pulsed fraction (2–10 keV) of≈ 27%. We also find that the cooling efficiency of the pulsar wind nebula (PWN) is intermediate between those of the Vela and Crab PWNe: LX (2–10keV)∼ 0. 002Ė. PSR J1930+1852 is a very weak radio source, with period-averaged flux density at 1180 MHz of 60 μJy. For a distance of 5 kpc, its luminosity, ∼ 1 mJy kpc2, is among the lowest for known young pulsars. Subject headings: ISM: individual (G54.1+0.3) — pulsars: individual (PSR J19 30+1852) — supernova remnants
Improved Approach to Global Localization based on Odometry Error Modeling for Mobile Robots

It is often the odometry accumulative error without bound after long-range movement that decreases the precision of global localization for wheeled mobile robots. Therefore, an efficient a pproach to odometry error modeling is proposed regarding gentle drive type mobile robots. The approximate functional expressions, between process input of odometry and non-systematic error as well as systematic error, are derived based on odometry error propagation law. Further, the odometry error model is applied to the global localization to compensate the accumulative error during long-time navigation. In addition, Because a lot of candidate poses of robots are generated in the process of monocular visual localization, particle swarm optimization is applied to acquire the optimal pose for mobile robots during global localization. The experiments denote that in spite of sacrificing a little computation time, the proposed method decreases odometry accumulative errors, and improves the global localization precision during autonomous navigation efficiently.
Robust Multi-Focus Image Fusion Using Multi-Task Sparse Representation and Spatial Context

We present a novel fusion method based on a multi-task robust sparse representation (MRSR) model and spatial context information to address the fusion of multi-focus gray-level images with misregistration. First, we present a robust sparse representation (RSR) model by replacing the conventional least-squared reconstruction error by a sparse reconstruction error. We then propose a multi-task version of the RSR model, viz., the MRSR model. The latter is then applied to multi-focus image fusion by employing the detailed information regarding each image patch and its spatial neighbors to collaboratively determine both the focused and defocused regions in the input images. To achieve this, we formulate the problem of extracting details from multiple image patches as a joint multi-task sparsity pursuit based on the MRSR model. Experimental results demonstrate that the suggested algorithm is competitive with the current state-of-the-art and superior to some approaches that use traditional sparse representation methods when input images are misregistered.
Human activity recognition in smart homes based on passive RFID localization

Modern societies are facing an important ageing of their population leading to arising economical and sociological challenges such as the pressure on health support services for semi-autonomous persons. Smart home technology is considered by many researchers as a promising potential solution to help supporting the needs of elders. It aims to provide cognitive assistance by taking decisions, such as giving hints, suggestions and reminders, with different kinds of effectors (light, sound, screen, etc.) to a resident suffering from cognitive deficits in order to foster their autonomy. To implement such technology, the first challenge we need to overcome is the recognition of the ongoing inhabitant activity of daily living (ADL). Moreover, to assist him correctly, we also need to be able to detect the cognitive errors he performs. Therefore, we present in this paper a new affordable activity recognition system, based on passive RFID technology, able to detect errors related to cognitive impairment in morning routines. The entire system relies on an innovative model of elliptical trilateration with several filters, and on an ingenious representation of activities with spatial zones. This system has been implemented and deployed in a real smart home prototype. We also present the promising results of a first experiment conducted on this new activity recognition system with real cases scenarios about morning routines.
A new built in self test pattern generator for low power dissipation and high fault coverage

The Built in Self Test (BIST) scheme proposed here is a combination of two test pattern generators. One is Low Transition Random Test Pattern Generator (LT-RTPG) and the other is Arithmetic based 3-weighted Random Test pattern Generator (A-3WRTPG). The LT-RTPG aims at detection of easy to detect faults which are prone to pseudo random patterns and reduction of power consumption during BIST activity. The LT-RTPG uses Bit-Swapping Linear Feedback Shift Register (BS-LFSR) for generation of pseudo random sequences. The BS-LFSR focuses on reducing the transitions in generated test pattern and there by reduces the power consumption during BIST activity. The A-3WRTPG aims at detection of pattern resistant faults that are left undetected by LT-RTPG and thereby increases the detection of fault probability. The A-3WRTPG uses flip flops and adders for carrying out arithmetic operations and modified form of weighted algorithm to achieve complete fault coverage. The weighted sets computed by A-3WRTPG comprising three weights, namely 0, 1, and 0.5 have been successfully utilized so far for test pattern generation, as a result in both low testing time and low consumed power. The proposed BIST can significantly reduce switching activity during BIST while achieving 100% fault coverage for all ISCAS'89 benchmark circuits.
Understanding the Privacy Design Space for Personal Connected Objects

Privacy is a major obstacle preventing the growth of the Internet of Things (IoT). As more connected objects become integrated in daily lives, ensuring that people feel comfortable with IoT's impact on their privacy becomes increasingly important. To date the understanding of users' perception regarding privacy risks in the connected object space is limited. In this paper we aim to shed lights on this issue through a qualitative study of in-depth interview with 16 people. Our results show that users are primarily concerned with the "Data Ownership" (i.e., who owns the data), when interacting with connected objects. Our findings suggest the need for an intuitive tool that can minimise the cognitive distance between users' mental model and the functionalities offered by connected objects. As a result we provide guidelines to design this kind of tool.
A remotely controlled Bluetooth enabled environment

Ad-hoc networks using Bluetooth enabled devices have piqued the interest of the networking community. Network developers are looking into different means of remotely controlling the devices comprising such networks, so as to have the flexibility to change various device parameters without actually being present near them. We present a method of remotely controlling devices in a Bluetooth enabled environment in the home or office from any part of the world via the Internet. A Web page applet programmed in Java can be accessed from any Java-enabled browser connected to the Internet and is used to control parameters of remote Bluetooth devices. It is also used to display the current state of the Bluetooth devices. A novel application of using Bluetooth devices for remote control is that a passive electronic device can be given processing power simply by connecting a Bluetooth chip to it. Any passive device in the Bluetooth enabled scatternet can have processed data send to it by the program resident in the Web server. The paper addresses issues related to internetworking such networks to form scatternets and presents a scatternet formation algorithm to solve the problem of connecting all the Bluetooth enabled devices in any home or office environment.
Children's Transfer of Spatial Learning from Virtual Reality to Real Environments

Spatial abilities in children have been shown to be related to activity in the environment, particularly to walking and other forms of active locomotion. The objective of this study is to investigate whether virtual reality (VR) can assist children in transferring spatial learning to a real environment. Children (six and seven-yr-old participants) were asked to find ten objects hidden around a room and to try not to visit the same location more than once. Examination of the percentage of correct choices and the visit of first error showed improvement as a result of training. There were initial differences between children trained on the computer compared to those trained in the real environment. However, after three practice trials, children with the VR training were comparable to children trained in the real space. The implications for utilizing a VR environment for enhancing spatial abilities for children with mobility difficulties is discussed.
A new family of matrix converters

A new family of matrix converters is introduced, that employs relatively simple voltage-clamped buses and can generate multilevel voltage waveforms of arbitrary magnitude and frequency. The basic configuration includes a nine-switch matrix that uses four-quadrant switch cells. Each four-quadrant switch cell resembles a full-bridge inverter and can assume three voltage levels during conduction. Semiconductor devices in a switch cell are clamped to a known constant DC voltage of a capacitor. Control of the input and output voltage waveforms of the proposed converter can be achieved through space vector modulation. Simulation results show how the converter can operate with any input and output voltages, currents, frequencies, and power factors while maintaining constant DC voltages across all switch cell capacitors.
Novel Activities of Select NSAID R-Enantiomers against Rac1 and Cdc42 GTPases

Rho family GTPases (including Rac, Rho and Cdc42) collectively control cell proliferation, adhesion and migration and are of interest as functional therapeutic targets in numerous epithelial cancers. Based on high throughput screening of the Prestwick Chemical Library® and cheminformatics we identified the R-enantiomers of two approved drugs (naproxen and ketorolac) as inhibitors of Rac1 and Cdc42. The corresponding S-enantiomers are considered the active component in racemic drug formulations, acting as non-steroidal anti-inflammatory drugs (NSAIDs) with selective activity against cyclooxygenases. Here, we show that the S-enantiomers of naproxen and ketorolac are inactive against the GTPases. Additionally, more than twenty other NSAIDs lacked inhibitory action against the GTPases, establishing the selectivity of the two identified NSAIDs. R-naproxen was first identified as a lead compound and tested in parallel with its S-enantiomer and the non-chiral 6-methoxy-naphthalene acetic acid (active metabolite of nabumetone, another NSAID) as a structural series. Cheminformatics-based substructure analyses—using the rotationally constrained carboxylate in R-naproxen—led to identification of racemic [R/S] ketorolac as a suitable FDA-approved candidate. Cell based measurement of GTPase activity (in animal and human cell lines) demonstrated that the R-enantiomers specifically inhibit epidermal growth factor stimulated Rac1 and Cdc42 activation. The GTPase inhibitory effects of the R-enantiomers in cells largely mimic those of established Rac1 (NSC23766) and Cdc42 (CID2950007/ML141) specific inhibitors. Docking predicts that rotational constraints position the carboxylate moieties of the R-enantiomers to preferentially coordinate the magnesium ion, thereby destabilizing nucleotide binding to Rac1 and Cdc42. The S-enantiomers can be docked but are less favorably positioned in proximity to the magnesium. R-naproxen and R-ketorolac have potential for rapid translation and efficacy in the treatment of several epithelial cancer types on account of established human toxicity profiles and novel activities against Rho-family GTPases.
A Multi-Population Consensus Genetic Map Reveals Inconsistent Marker Order among Maps Likely Attributed to Structural Variations in the Apple Genome

Genetic maps serve as frameworks for determining the genetic architecture of quantitative traits, assessing structure of a genome, as well as aid in pursuing association mapping and comparative genetic studies. In this study, a dense genetic map was constructed using a high-throughput 1,536 EST-derived SNP GoldenGate genotyping platform and a global consensus map established by combining the new genetic map with four existing reliable genetic maps of apple. The consensus map identified markers with both major and minor conflicts in positioning across all five maps. These major inconsistencies among marker positions were attributed either to structural variations within the apple genome, or among mapping populations, or genotyping technical errors. These also highlighted problems in assembly and anchorage of the reference draft apple genome sequence in regions with known segmental duplications. Markers common across all five apple genetic maps resulted in successful positioning of 2875 markers, consisting of 2033 SNPs and 843 SSRs as well as other specific markers, on the global consensus map. These markers were distributed across all 17 linkage groups, with an average of 169±33 marker per linkage group and with an average distance of 0.70±0.14 cM between markers. The total length of the consensus map was 1991.38 cM with an average length of 117.14±24.43 cM per linkage group. A total of 569 SNPs were mapped onto the genetic map, consisting of 140 recombinant individuals, from our recently developed apple Oligonucleotide pool assays (OPA). The new functional SNPs, along with the dense consensus genetic map, will be useful for high resolution QTL mapping of important traits in apple and for pursuing comparative genetic studies in Rosaceae.
Learning and Experience in the Labor Market

This paper models the role of the labor market in the transmission and acquisition of skills and knowledge, based on the hypothesis that indivduals learn from their working experiences. The problem is cast in terms of an implicit market for learning opportunities that is dual to the market for jobs. Optimum choices in this setting have implications for the evolution of earnings and occupational patterns over the workers' lifetimes and provide the basis for a theory of occupational mobility. Several implications of the model, including those for occupational discrimination against minorities, are also discussed.
Characterization of Curved Creases and Rulings: Design and Analysis of Lens Tessellations

We describe a general family of curved-crease folding tessellations consisting of a repeating "lens" motif formed by two convex curved arcs. The third author invented the first such design in 1992, when he made both a sketch of the crease pattern and a vinyl model (pictured below). Curve fitting suggests that this initial design used circular arcs. We show that in fact the curve can be chosen to be any smooth convex curve without inflection point. We identify the ruling configuration through qualitative properties that a curved folding satisfies, and prove that the folded form exists with no additional creases, through the use of differential geometry.