Miracle-dz/UniFAR-FTUs huggingface dataset:
DStat: A Versatile, Open-Source Potentiostat for Electroanalysis and Integration

Most electroanalytical techniques require the precise control of the potentials in an electrochemical cell using a potentiostat. Commercial potentiostats function as “black boxes,” giving limited information about their circuitry and behaviour which can make development of new measurement techniques and integration with other instruments challenging. Recently, a number of lab-built potentiostats have emerged with various design goals including low manufacturing cost and field-portability, but notably lacking is an accessible potentiostat designed for general lab use, focusing on measurement quality combined with ease of use and versatility. To fill this gap, we introduce DStat (http://microfluidics.utoronto.ca/dstat), an open-source, general-purpose potentiostat for use alone or integrated with other instruments. DStat offers picoampere current measurement capabilities, a compact USB-powered design, and user-friendly cross-platform software. DStat is easy and inexpensive to build, may be modified freely, and achieves good performance at low current levels not accessible to other lab-built instruments. In head-to-head tests, DStat’s voltammetric measurements are much more sensitive than those of “CheapStat” (a popular open-source potentiostat described previously), and are comparable to those of a compact commercial “black box” potentiostat. Likewise, in head-to-head tests, DStat’s potentiometric precision is similar to that of a commercial pH meter. Most importantly, the versatility of DStat was demonstrated through integration with the open-source DropBot digital microfluidics platform. In sum, we propose that DStat is a valuable contribution to the “open source” movement in analytical science, which is allowing users to adapt their tools to their experiments rather than alter their experiments to be compatible with their tools.
RIG-I and TLR 3 are both required for maximum interferon induction by in fl uenza virus in human lung alveolar epithelial cells

Pattern recognition receptors, such as retinoic acid-inducible protein I (RIG-I), Toll-like receptors 3 and 7 (TLR3 and 7), and nucleotide-binding oligomerization domain containing protein 2 (NOD2), play important roles in the recognition of influenza A virus (IAV), but their role in interferon (IFN) induction is still unclear, particularly in human lung. We investigated IFN induction by IAV in the A549 cell line as well as in primary human alveolar epithelial cells (AEC). TLR3/7, NOD2, RIG-I, and IFN expression levels were measured by qRT-PCR and ELISA in cells infected with IAV PR8. We found that TLR7 and NOD2 were not involved in IFN induction by IAV in these cells. Neither RIG-I nor TLR3 siRNA alone completely blocked IFN induction. However, double knockdown of RIG-I and TLR3 completely inhibited IFN induction by influenza. Thus, signaling through both RIG-I and TLR3 is important for IFN induction by IAV in human lung AEC. & 2015 Elsevier Inc. All rights reserved.
Improve online boosting algorithm from self-learning cascade classifier

Online boosting algorithm has been used in many vision-related applications, such as object detection. However, in order to obtain good detection result, combining a large number of weak classifiers into a strong classifier is required. And those weak classifiers must be updated and improved online. So the training and detection speed will be reduced inevitably. This paper proposes a novel online boosting based learning method, called self-learning cascade classifier. Cascade decision strategy is integrated with the online boosting procedure. The resulting system contains enough number of weak classifiers while keeping computation cost low. The cascade structure is learned and updated online. And the structure complexity can be increased adaptively when detection task is more difficult. Moreover, most of new samples are labeled by tracking automatically. This can greatly reduce the effort by labeler. We present experimental results that demonstrate the efficient and high detection rate of the method.
Minimizing Building Electricity Costs in a Dynamic Power Market: Algorithms and Impact on Energy Conservation

Energy is a global concern and the electricity bills nowadays are leading to unprecedented costs. Electricity price is market-based and dynamic. In this paper, we investigate how to cut the electricity bills of commercial buildings in a dynamic power market. The building thermal systems (e.g., air-conditioning), which dominate electricity bills, has a special property of thermal storage, i.e., the energy will not immediately dissipate from thermal air/water. Intuitively, with storage, the energy can be "stored" in the thermal system, making it possible to purchase electricity in low price and use it at appropriate time. The building thermal supply and electricity purchasing surely depends on human activities that the building should support such as class and meeting schedules. To minimize electricity bills, we develop a holistic planning of electricity purchasing schedule with thermal storage management, and appropriate room assignment schedules for classes/meetings usage. The computing algorithms require inputs of physical modeling on energy consumption. We develop wireless sensing systems to collect fine-grained data which are used to assist the cross-disciplinary physical modeling. We conduct validation through real experiments. We formulate an optimization problem and show that it is NP-complete. Our primary focus is to minimize electricity bills, which matches the incentives of the commercial buildings. We show that this does not coincide with energy conservation. We further investigate the relationship of minimization of electricity bills and minimization of energy consumption. We develop algorithms for our problem and our evaluation shows that we can achieve a 40% cost reduction.
Design and Implementation of a Library Metadata Management Framework and its Application in Fuzzy Data Deduplication and Data Reconciliation with Authority Data

We describe the application of a generic workflow management system to the problem of metadata processing in the library domain. The requirements for such a framework and acting real-world forces are examined. The design of the framework is layed out and illustrated by means of two example workflows: fuzzy data deduplication and data reconciliation with authority data. Fuzzy data deduplication is the process of finding similar items in record collections that can not be matched by identifiers. Data reconciliation with authority data takes a data source and enhances the metadata of its records – mainly authors and subjects – with available normed data. Finally, the advantages and tradeoffs of the presented approach are discussed.
Development and Control of Articulated Mobile Robot for Climbing Steep Stairs

In this paper, we develop an articulated mobile robot that can climb stairs, and also move in narrow spaces and on 3-D terrain. This paper presents two control methods for this robot. The first is a 3-D steering method that is used to adapt the robot to the surrounding terrain. In this method, the robot relaxes its joints, allowing it to adapt to the terrain using its own weight, and then, resumes its motion employing the follow-the-leader method. The second control method is the semi-autonomous stair climbing method. In this method, the robot connects with the treads of the stairs using a body called a connecting part, and then shifts the connecting part from its head to its tail. The robot then uses the sensor information to shift the connecting part with appropriate timing. The robot can climb stairs using this method even if the stairs are steep, and the sizes of the riser and the tread of the stairs are unknown. Experiments are performed to demonstrate the effectiveness of the proposed methods and the developed robot.
Timing and Impact of Decisions to Adjust Disease‐Modifying Antirheumatic Drug Therapy for Rheumatoid Arthritis Patients With Active Disease

Guidelines recommend that rheumatoid arthritis (RA) patients with moderate‐to‐high disease activity (MHDAS) adjust disease‐modifying antirheumatic drug (DMARD) therapy at least every 3 months until reaching low disease activity or remission (LDAS). We examined how quickly RA patients with MHDAS adjust DMARD therapy in clinical practice, and whether those who adjust DMARDs within 90 days in response to MHDAS reach LDAS sooner.
Teacher assisted versus individual viewing of foreign language video: Relation to comprehension, self-efficacy, and engagement

As teachers' roles evolve in technology-enhanced language learning (TELL), choices of technological devices and instructional delivery and the degree of foreign language (FL) teacher facilitation within TELL activities are prominent. This investigation compared 53 beginning college French students' comprehension of FL video in a teacher-assisted viewing classroom environment (TAV) and an independent computer-based setting (IV) to examine the benefits of teacher mediation on students' comprehension of FL video and the relation to the types of questions asked, self-efficacy, and engagement. The results demonstrated that students performed equally well on comprehension measures in the TAV and IV conditions. With regard to self-efficacy, students felt significantly more confident in their ability to comprehend video in the TAV than in the IV condition. A relationship was found between self-efficacy and comprehension in the TAV, a relationship not present in the IV condition. Levels of engagement significantly predicted students' comprehension performance while working independently but were not a significant predictor of comprehension in the TAV condition. Implications of this study include (a) the need for increased exposure to self-directed learning tasks in beginning FL classrooms to improve self-efficacy toward independent TELL activities and (b) the need for student exploration during TAV tasks to improve engagement.
Visual/acoustic detection and localisation in embedded systems

The continuous miniaturisation of sensing and processing technologies is increasingly offering a variety of embedded platforms, enabling the accomplishment of a broad range of tasks using such systems. Motivated by these advances, this thesis investigates embedded detection and localisation solutions using vision and acoustic sensors. Focus is particularly placed on surveillance applications using sensor networks. Existing vision-based detection solutions for embedded systems suffer from the sensitivity to environmental conditions. In the literature, there seems to be no algorithm able to simultaneously tackle all the challenges inherent to real-world videos. Regarding the acoustic modality, many research works have investigated acoustic source localisation solutions in distributed sensor networks. Nevertheless, it is still a challenging task to develop an efficient algorithm that deals with the experimental issues, to approach the performance required by these systems and to perform the data processing in a distributed and robust manner. The movement of scene objects is generally accompanied with sound emissions with features that vary from an environment to another. Therefore, considering the combination of the visual and acoustic modalities would offer a significant opportunity for improving the detection and/or localisation using the described platforms. In the light of the described framework, we investigate in the first part of the thesis the use of a cost-effective visual based method that can deal robustly with the issue of motion detection in static, dynamic and moving background conditions. For motion detection in static and dynamic backgrounds, we present the development and the performance analysis of a spatio-temporal form of the Gaussian mixture model. On the other hand, the problem of motion detection in moving
Possible Synergistic Effects of Thymol and Nicotine against Crithidia bombi Parasitism in Bumble Bees

Floral nectar contains secondary compounds with antimicrobial properties that can affect not only plant-pollinator interactions, but also interactions between pollinators and their parasites. Although recent work has shown that consumption of plant secondary compounds can reduce pollinator parasite loads, little is known about the effects of dosage or compound combinations. We used the generalist pollinator Bombus impatiens and its obligate gut parasite Crithidia bombi to study the effects of nectar chemistry on host-parasite interactions. In two experiments we tested (1) whether the secondary compounds thymol and nicotine act synergistically to reduce parasitism, and (2) whether dietary thymol concentration affects parasite resistance. In both experiments, uninfected Bombus impatiens were inoculated with Crithidia and then fed particular diet treatments for 7 days, after which infection levels were assessed. In the synergism experiment, thymol and nicotine alone and in combination did not significantly affect parasite load or host mortality. However, the thymol-nicotine combination treatment reduced log-transformed parasite counts by 30% relative to the control group (P = 0.08). For the experiment in which we manipulated thymol concentration, we found no significant effect of any thymol concentration on Crithidia load, but moderate (2 ppm) thymol concentrations incurred a near-significant increase in mortality (P = 0.054). Our results tentatively suggest the value of a mixed diet for host immunity, yet contrast with research on the antimicrobial activity of dietary thymol and nicotine in vertebrate and other invertebrate systems. We suggest that future research evaluate genetic variation in Crithidia virulence, multi-strain competition, and Crithidia interactions with the gut microbe community that may mediate antimicrobial activities of secondary compounds.
Realistic simulation of ocean surface using wave spectra

We present a method to simulate ocean surfaces away from the coast, with correct statistical wave height and direction distributions. By using classical oceanographic parametric wave spectra, our results fit real world measurements, without depending on them. Since wave spectra are independent of the ocean model, Gerstner parametric equations and Fourier transform method can be used with them. Moreover, since they are simple to use and need very few parameters, they allow easy production of ocean surface animations usable in movies and games. We explain how to accurately sample them, to achieve oceanic waves in deep water according to given wind parameters, in a realistic way. 1
A pathway for low zinc homeostasis that is conserved in animals and acts in parallel to the pathway for high zinc homeostasis

Abstract The essential element zinc plays critical roles in biology. High zinc homeostasis mechanisms are beginning to be defined in animals, but low zinc homeostasis is poorly characterized. We investigated low zinc homeostasis in Caenorhabditis elegans because the genome encodes 14 evolutionarily conserved Zrt, Irt-like protein (ZIP) zinc transporter family members. Three C. elegans zipt genes were regulated in zinc-deficient conditions; these promoters contained an evolutionarily conserved motif that we named the low zinc activation (LZA) element that was both necessary and sufficient for activation of transcription in response to zinc deficiency. These results demonstrated that the LZA element is a critical part of the low zinc homeostasis pathway. Transcriptional regulation of the LZA element required the transcription factor ELT-2 and mediator complex member MDT-15. We investigated conservation in mammals by analyzing LZA element function in human cultured cells; the LZA element-mediated transcriptional activation in response to zinc deficiency in cells, suggesting a conserved pathway of low zinc homeostasis. We propose that the pathway for low zinc homeostasis, which includes the LZA element and ZIP transporters, acts in parallel to the pathway for high zinc homeostasis, which includes the HZA element, HIZR-1 transcription factor and cation diffusion facilitator transporters.
Rationale-Based Engineering of a Potent Long-Acting FGF21 Analog for the Treatment of Type 2 Diabetes

Fibroblast growth factor 21 (FGF21) is a promising drug candidate for the treatment of type 2 diabetes. However, the use of wild type native FGF21 is challenging due to several limitations. Among these are its short half-life, its susceptibility to in vivo proteolytic degradation and its propensity to in vitro aggregation. We here describe a rationale-based protein engineering approach to generate a potent long-acting FGF21 analog with improved resistance to proteolysis and aggregation. A recombinant Fc-FGF21 fusion protein was constructed by fusing the Fc domain of human IgG1 to the N-terminus of human mature FGF21 via a linker peptide. The Fc positioned at the N-terminus was determined to be superior to the C-terminus as the N-terminal Fc fusion retained the βKlotho binding affinity and the in vitro and in vivo potency similar to native FGF21. Two specific point mutations were introduced into FGF21. The leucine to arginine substitution at position 98 (L98R) suppressed FGF21 aggregation at high concentrations and elevated temperatures. The proline to glycine replacement at position 171 (P171G) eliminated a site-specific proteolytic cleavage of FGF21 identified in mice and cynomolgus monkeys. The derived Fc-FGF21(RG) molecule demonstrated a significantly improved circulating half-life while maintaining the in vitro activity similar to that of wild type protein. The half-life of Fc-FGF21(RG) was 11 h in mice and 30 h in monkeys as compared to 1-2 h for native FGF21 or Fc-FGF21 wild type. A single administration of Fc-FGF21(RG) in diabetic mice resulted in a sustained reduction in blood glucose levels and body weight gains up to 5-7 days, whereas the efficacy of FGF21 or Fc-FGF21 lasted only for 1 day. In summary, we engineered a potent and efficacious long-acting FGF21 analog with a favorable pharmaceutical property for potential clinical development.
Discussion on the Existing Deterministic Approaches for Evaluating the Voltage Deviation due to Distributed Generation

This paper investigates uncertainties in the existing deterministic approaches for evaluating steadystate voltage deviation due to distributed generation. Nowadays, deterministic approaches are widely adopted by the persons proposing the interconnection of distributed generation. However, the existing deterministic approaches overlook some operation conditions that may give rise to incorrect results and lead to wrong decisions in practical applications. In this paper, the interconnection rules for distributed generations and the existing deterministic approaches for evaluating steady-state voltage deviations are introduced first. Then, various factors effecting steady-state voltage deviation and the determination of maximum allowable DG capacity are discussed. Finally, the uncertainties of the existing deterministic approaches are discussed. It is intended for reference by utility engineers processing distributed generation interconnection applications. Key-Words: Distributed generation, Distribution system, Power flow analysis, Power quality, Voltage deviations, Wind power.
Study of Current Pulse Form for Optimization of Railguns Forces

Electromagnetic force on rails of railgun is the effective factor which impacts on input current pulse, rails and armature geometry, dimensions, and materials. This paper investigates how the stimulated current form affects the electromagnetic force on rails. A transient analysis with a finite-element method is discussed to simulate a 3-D railgun in this paper. In the first section, we consider the effect of flat-top length of stimulated current pulse on electromagnetic force distribution on rail and armature velocities. In the second section, we consider the effect of stimulated currents that have the same areas but have various amplitudes and flat-top lengths and at the last section, the flat-top length and amplitude of current are exactly the same, but the flat-top part replaces during time. Consequences are shown in several figures.
Anderson acceleration in the context of a Broyden-type approximation of the inverse Jacobian

Acceleration schemes can dramatically improve existing optimization procedures. In most of the work on these schemes, such as nonlinear Generalized Minimal Residual (N-GMRES), acceleration is based on minimizing the `2 norm of some target on subspaces of R. There are many numerical examples that show how accelerating general purpose and domain-specific optimizers with N-GMRES results in large improvements. We propose a natural modification to N-GMRES, which significantly improves the performance in a testing environment originally used to advocate N-GMRES. Our proposed approach, which we refer to as O-ACCEL (Objective Acceleration), is novel in that it minimizes an approximation to the objective function on subspaces of R. We prove that O-ACCEL reduces to the Full Orthogonalization Method for linear systems when the objective is quadratic, which differentiates our proposed approach from existing acceleration methods. Comparisons with L-BFGS and N-CG indicate the competitiveness of O-ACCEL. As it can be combined with domain-specific optimizers, it may also be beneficial in areas where L-BFGS or N-CG are not suitable.
A Nonconvex Proximal Splitting Algorithm under Moreau-Yosida Regularization

We tackle composite optimization problems whose objectives are (highly) nonconvex and nonsmooth. Classical nonconvex proximal splitting algorithms, such as nonconvex ADMM, suffer from a lack of convergence for such a problem class. In this work, we consider a Moreau-Yosida regularized variant of the original model and propose a novel multiblock primal-dual algorithm on the resulting lifted problem. We provide a complete convergence analysis of our algorithm, and identify respective optimality qualifications under which stationarity of the regularized problem is retrieved at convergence. Numerically, we demonstrate the relevance of our model and the efficiency of our algorithm on robust regression as well as joint variable selection and transductive learning.
Dual-polarized dual-frequency antenna module for a maritime phased array radar

A dual-polarized dual-frequency antenna module for a future commercial navigation radar is presented. The module is comprised of three X-band antenna columns as well as one S-Band antenna column. All antennas feature dual-polarization capability and are the basic antenna cell for a full phased array realization of the radar system.
Thermodynamic properties of anthophyllite and talc : Corrections and discussion of calorimetric data

Arithmetic errors in calculating heat capacity values (Krupka, 1984; Krupka et al., 1985a) for anthophyllite and several errors in the Hess cycles utilized to derive enthalpies of formation of anthophyllite and talc are identified, and revised values are reported. The corrected values are: for anthophyllite, ^Sns ,$ : 554.2 + 3 J/mol'K and A1Hln, : -12163 + 8kJ/mol.KforthecompositionMgurFeo,SirOrr(OH)ri andSlnr:534.5 + 3.5 J/mol'K, ArHorrr: -12070 a 8 kJ/mol and ArGln": -11343 + 8 kJlmol for the composition MgrSirOrr(OH)r; and for talc [MgrSioO,o(OH)r], \H9n": -5900 + 2 kJ/mol and ArG2nr: -5520 + 2 kJ/mol. Corrected heat capacity equations for anthophyllite are: for MgurFeorSirOrr(OH),