Performance evaluation of an architecture for the characterisation of photo-devices: design,fabrication and test on a CMOS technology

In this report, the performance of a particular pixel's architecture is evaluated. It consists mainly of an optical sensor coupled to an amplifier. The circuit contains photoreceptors such as phototransistors and photodiodes. The circuit integrates two main blocks: (a) the pixel architecture, containing four p-channel transistors and a photoreceptor, and (b) a current source for biasing the signal conditioning amplifier. The generated photocurrent is integrated through the gate capacitance of the input p-channel MOS transistor, then converted to voltage and amplified. Both input transistor and current source are implemented as a voltage amplifier having variable gain (between 10dB and 32dB). Considering characterisation purposes, this last fact is relevant since it gives a degree of freedom to the measurement of different kinds of photo-devices and is not limited to either a single operating point of the circuit or one kind and size of photo-sensor. The gain of the amplifier can be adjusted with an external DC power supply that also sets the DC quiescent point of the circuit. Design of the row-select transistor's aspect ratio used in the matrix array is critical for the pixel's amplifier performance. Based on circuit design data such as capacitance magnitude, time and voltage integration, and amplifier gain, characterisation of all the architecture can be readily carried out and evaluated. For the specific technology used in this work, the spectral response of photo-sensors reveals performance differences between phototransistors and photodiodes. Good approximation between simulation and measurement was obtained.     

Optimization of Nonlinear Transmission Lines for Harmonic Generation: The Role of the Capacitance-Voltage Characteristic and the Area Effect

In this paper, nonlinear transmission lines (NLTLs) periodically loaded with symmetric voltage dependent capacitances are investigated by means of computer simulation. Specifically, we have studied the role that the C-V characteristic plays on the performance of NLTLs as frequency multipliers. The main conclusion of the work is that the area under the C(V) curve is a key parameter for the optimization of conversion efficiency. This result is interpreted on the basis of soliton like propagation in NLTLs.     

Detection of Channel Variations to Improve Channel Estimation Methods

In current digital communication systems, channel information is typically acquired by supervised approaches that use pilot symbols included in the transmit frames. Given that pilot symbols do not convey user data, they penalize throughput spectral efficiency, and transmit energy consumption of the system. Unsupervised channel estimation algorithms could be used to mitigate the aforementioned drawbacks although they present higher computational complexity than that offered by supervised ones. This paper proposes a simple decision method suitable for slowly varying channels to determine whether the channel has suffered a significant variation, which requires to estimate the matrix of the recently changed channel. Otherwise, a previous estimate is used to recover the transmitted symbols. The main advantage of this method is that the decision criterion is only based on information acquired during the time frame synchronization, which is carried out at the receiver. We show that the proposed criterion provides a considerable improvement of computational complexity for both supervised and unsupervised methods, without incurring in a penalization in terms of symbol error ratio. Specifically, we consider systems that make use of the popular Alamouti code. Performance evaluation is accomplished by means of simulated channels as well as making use of indoor wireless channels measured using a testbed.     

Teamwork assessment in the educational web of data: A learning analytics approach towards ISO 10018

The Web of Data is an emerging research field that contributes to make better decisions because it gathers, combines and analyses different data sources available worldwide. Educational data is an interesting domain because it deals with the quality of the education itself and educational institutions which are common goals for every country. This paper is devoted to present how this idea has been used to improve a learning analytics tool. By means of this tool, teachers can perform teamwork competence assessment of a group of students taking into account how the individuals acquire the essential components of such competence. In this sense, authors use the Comprehensive Training Model of the Teamwork Competence in Engineering Domain (CTMTC) method to gather competence evidences and improve the system with a learning analytics tool to support the process. This tool is able to transform competence evidences and stores them in a competence ontology built upon ISO 10018 concepts. The final result is the production of educational results for the web of data.     

An adaptive hybrid MOOC model: Disrupting the MOOC concept in higher education

In the 18th century, the educational model underwent a disruptive change driven by the transition from an agricultural to an industrial society. In the 21st century, the change from the industrial society to a knowledge society has been consolidated, but it has not involved a disruption in the learning context. Some elements, many based on technologies, can be considered disruptive, but they have not had sufficient effect to produce a change in the model that has predominated for 300 years. In 2008, teachers began to offer training outside the walls of the university, with a totally disruptive and chaotic model compared to the traditional one; this was supported by open, informal, cooperative, connectivist, autonomous and self-guided training. Massive open online courses (MOOCs) began with cMOOCs, and most universities join the initiative, but they abandoned this disruption, ultimately offering the same courses they always had with free access for anyone, resulting in the second generation of MOOCs (xMOOCs). These MOOCs responded to a new social demand, but their characteristics and context make a formative disruption – which has not yet emerged – necessary. This paper analyses the elements of the two generations of MOOCs in order to propose a new model that does not require sophisticated technological solutions and recovers the initial disruptive sense of MOOCs, so called ahMOOC. It also presents a case study that integrates the social advantages of cMOOCs, the organisational benefits of xMOOCs and the personalisation of the learning, which is essential due to the heterogeneity of the participants. The results and the participant viewpoints emerging from the case study confirm the feasibility of the model, the improvement of the results of current MOOCs and the need – demanded by the participants – to consider diversity, all of which should be accomplished in a disruptive way.     

New Drug‐Structure‐Directing Agent Concept: Inherent Pharmacological Activity Combined with Templating Solid and Hollow‐Shell Mesostructured Silica Nanoparticles

One of the major challenges in medicine is the delivery and control of drug release over time. Current approaches take advantage of mesostructured silica nanoparticles (MSNs) as carriers but suffer several problems including complex synthesis that requires sequential steps for (1) removal of surfactants and (2) functionalization of MSNs to allow upload of the drugs. Here, a novel solution is presented to these restrictions: the design of drug‐structure‐directing agents (DSDAs) with dual inherent pharmacological activity and ability to direct the formation of solid and hollow‐shell MSNs. Pharmacologically active DSDAs obtained by amidation of drugs with fatty acids are allowed to form micelles, around which the inorganic species self‐assembled to form MSNs. Since the DSDAs direct the formation of MSNs, the steps to remove surfactants, functionalization, and drug upload are not required. The MSNs thus prepared provide sustained release of the drug over more than six months, as well as rapid cellular internalization by both physiological and tumoral human colon cells without affecting cell viability. Moreover, the gradual intracellular release of both, the active drug and lipid moiety with potential nutraceutical properties is proved. MSN particles designed with this approach are promising vehicles for controlled and sustained intra‐or extracellular drug‐delivery.     

Using AVAL-1D to simulate avalanches in the eastern Pyrenees

The two friction parameters used in the numerical avalanche dynamics program AVAL-1D, were calibrated empirically with data from observed avalanches in the Swiss Alps. The implementation of the model with these friction parameters in other regions with different characteristics can lead to considerable uncertainty if a previous calibration is not performed. However, direct calibration for a specific avalanche path is often not possible since the data available are insufficient. Therefore, we back-calculated twelve well-documented avalanche events from the Catalan Pyrenees to calibrate the friction coefficients to be used in this mountain range. The result of the study reveals that there is a good fit between recorded and simulated avalanche events using the friction parameters originally calibrated for the Swiss Alps, despite the difference in snow climate between these two mountain ranges.     

Use of time history speckle pattern and pulsed photoacoustic techniques to detect the self-accommodating transformation in a Cu–Al–Ni shape memory alloy

Continuous and pulsed electromagnetic radiation was used to detect the self-accommodation mechanism on a polycrystalline Cu–13.83 wt.%Al–2.34 wt.%Ni shape memory alloy. Rectangular samples of this alloy were mechanically polished to observe the austenite and martensite phases. The samples were cooled in liquid nitrogen prior to the experiments to obtain the martensite phase. Using a dynamic speckle technique with a continuous wave laser we obtained the time history of the speckle pattern image and monitored the surface changes caused by the self-accommodation mechanism during the inverse (martensitic to austenitic) transformation. Using a photoacoustic technique based on a pulsed laser source it was also possible to detect the self-accommodation phenomena in a bulk sample. For comparison purposes, we used differential scanning calorimetry (DSC) to detect the critical temperatures of transformation and use these as reference to evaluate the performance of the optical and photoacoustical techniques. In all cases, the same range of temperature was obtained during the inverse transformation. From these results, we conclude that time history speckle pattern (THSP) and pulsed photoacoustic are complementary techniques; they are non-destructive and useful to detect surface and bulk martensitic transformation induced by a temperature change.     

Self-organized Ce(1-x)Gd(x)O(2-y) nanowire networks with very fast coarsening driven by attractive elastic interactions

Assembling arrays of ordered nanowires is a key objective for many of their potential applications. However, a lack of understanding and control of the nanowires' growth mechanisms limits their thorough development. In this work, an appealing new path towards self-organized epitaxial nanowire networks produced by high-throughput solution methods is reported. Two requisites are identified to generate the nanowires: a thermodynamic driving force for an unrestricted elongated equilibrium island shape, and a very fast effective coarsening rate. These requirements are met in anisotropically strained Ce(1-x)Gd(x)O(2-y) nanowires with the (011) orientation grown on the (001) surface of LaAlO(3) substrates. Nanowires with aspect ratios above ≈100 oriented along two mutually orthogonal axes are obtained leading to labyrinthine networks. A very fast effective nanowire growth rate (≈60 nm min(-1)) for ex-situ thermally annealed nanostructures derives from simultaneous kinetic processes occurring in a branched network. Ostwald ripening and anisotropic dynamic coalescence, both promoted by strain-driven attractive nanowire interaction, and rapid recrystallization, enabled by fast atomic diffusion associated with a high concentration of oxygen vacancies, contribute to such an effective growth rate. This bottom-up approach to self-organized nanowire growth has a wide potential for many materials and functionalities.