Hidden sector effects on double Higgs production near threshold at the LHC

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Determination of fluquinconazole, pyrimethanil, and clofentezine residues in fruits by liquid chromatography with ultraviolet detection

A simple method was developed for the determination of fluquinconazole, pyrimethanil, and clofentezine in whole fruit; peel; and pulp of mango, apple, and papaya. These compounds were extracted from fruit samples with a mixture of ethyl acetate-n-hexane (1 + 1, v/v). An aliquot (2 mL) of the extract was evaporated to near dryness under a stream of nitrogen, and the residue was dissolved with 2 mL methanol. The analysis was performed by means of liquid chromatography with ultraviolet detection at 254 nm using a gradient solvent system. The method was validated with fortified fruit samples at concentration levels of 0.05, 0.10, 0.20, and 0.50 mg/kg. Average recoveries (4-8 replicates) ranged from 80 to 95% with relative standard deviations between 3.5 and 12.7%. Detection limits ranged from 0.03 to 0.05 mg/kg for fruit pulp and 0.03 mg/kg for whole fruit. The quantitation limits ranged from 0.05 to 0.10 mg/kg for fruit pulp and 0.05 mg/kg for whole fruit. The analytical method was applied to fruit samples obtained from local markets.

Optimization of algorithm to identification of duplicate tuples through similarity phonetic based on multithreading

Aiming to ensure greater reliability and consistency of data stored in the database, the data cleaning stage is set early in the process of Knowledge Discovery in Databases (KDD) and is responsible for eliminating problems and adjust the data for the later stages, especially for the stage of data mining. Such problems occur in the instance level and schema, namely, missing values, null values, duplicate tuples, values outside the domain, among others. Several algorithms were developed to perform the cleaning step in databases, some of them were developed specifically to work with the phonetics of words, since a word can be written in different ways. Within this perspective, this work presents as original contribution an optimization of algorithm for the detection of duplicate tuples in databases through phonetic based on multithreading without the need for trained data, as well as an independent environment of language to be supported for this. © 2011 IEEE.

Assessment of a new infrared laser transillumination technology (808nm) for the detection of occlusal caries-an in vitro study

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Cooperative communication and distributed detection in wireless sensor networks

Recent progress in microelectronic and wireless communications have enabled the development of low cost, low power, multifunctional sensors, which has allowed the birth of new type of networks named wireless sensor networks (WSNs). The main features of such networks are: the nodes can be positioned randomly over a given field with a high density; each node operates both like sensor (for collection of environmental data) as well as transceiver (for transmission of information to the data retrieval); the nodes have limited energy resources. The use of wireless communications and the small size of nodes, make this type of networks suitable for a large number of applications. For example, sensor nodes can be used to monitor a high risk region, as near a volcano; in a hospital they could be used to monitor physical conditions of patients. For each of these possible application scenarios, it is necessary to guarantee a trade-off between energy consumptions and communication reliability. The thesis investigates the use of WSNs in two possible scenarios and for each of them suggests a solution that permits to solve relating problems considering the trade-off introduced. The first scenario considers a network with a high number of nodes deployed in a given geographical area without detailed planning that have to transmit data toward a coordinator node, named sink, that we assume to be located onboard an unmanned aerial vehicle (UAV). This is a practical example of reachback communication, characterized by the high density of nodes that have to transmit data reliably and efficiently towards a far receiver. It is considered that each node transmits a common shared message directly to the receiver onboard the UAV whenever it receives a broadcast message (triggered for example by the vehicle). We assume that the communication channels between the local nodes and the receiver are subject to fading and noise. The receiver onboard the UAV must be able to fuse the weak and noisy signals in a coherent way to receive the data reliably. It is proposed a cooperative diversity concept as an effective solution to the reachback problem. In particular, it is considered a spread spectrum (SS) transmission scheme in conjunction with a fusion center that can exploit cooperative diversity, without requiring stringent synchronization between nodes. The idea consists of simultaneous transmission of the common message among the nodes and a Rake reception at the fusion center. The proposed solution is mainly motivated by two goals: the necessity to have simple nodes (to this aim we move the computational complexity to the receiver onboard the UAV), and the importance to guarantee high levels of energy efficiency of the network, thus increasing the network lifetime. The proposed scheme is analyzed in order to better understand the effectiveness of the approach presented. The performance metrics considered are both the theoretical limit on the maximum amount of data that can be collected by the receiver, as well as the error probability with a given modulation scheme. Since we deal with a WSN, both of these performance are evaluated taking into consideration the energy efficiency of the network. The second scenario considers the use of a chain network for the detection of fires by using nodes that have a double function of sensors and routers. The first one is relative to the monitoring of a temperature parameter that allows to take a local binary decision of target (fire) absent/present. The second one considers that each node receives a decision made by the previous node of the chain, compares this with that deriving by the observation of the phenomenon, and transmits the final result to the next node. The chain ends at the sink node that transmits the received decision to the user. In this network the goals are to limit throughput in each sensor-to-sensor link and minimize probability of error at the last stage of the chain. This is a typical scenario of distributed detection. To obtain good performance it is necessary to define some fusion rules for each node to summarize local observations and decisions of the previous nodes, to get a final decision that it is transmitted to the next node. WSNs have been studied also under a practical point of view, describing both the main characteristics of IEEE802:15:4 standard and two commercial WSN platforms. By using a commercial WSN platform it is realized an agricultural application that has been tested in a six months on-field experimentation.

Detection of small buried objects: asymptotic factorization and MUSIC

In this work, we consider a simple model problem for the electromagnetic exploration of small perfectly conducting objects buried within the lower halfspace of an unbounded two–layered background medium. In possible applications, such as, e.g., humanitarian demining, the two layers would correspond to air and soil. Moving a set of electric devices parallel to the surface of ground to generate a time–harmonic field, the induced field is measured within the same devices. The goal is to retrieve information about buried scatterers from these data. In mathematical terms, we are concerned with the analysis and numerical solution of the inverse scattering problem to reconstruct the number and the positions of a collection of finitely many small perfectly conducting scatterers buried within the lower halfspace of an unbounded two–layered background medium from near field measurements of time–harmonic electromagnetic waves. For this purpose, we first study the corresponding direct scattering problem in detail and derive an asymptotic expansion of the scattered field as the size of the scatterers tends to zero. Then, we use this expansion to justify a noniterative MUSIC–type reconstruction method for the solution of the inverse scattering problem. We propose a numerical implementation of this reconstruction method and provide a series of numerical experiments.

Feasibility of Using EMG for Early Detection of the Facial Nerve During Robotic Direct Cochlear Access

HYPOTHESIS Facial nerve monitoring can be used synchronous with a high-precision robotic tool as a functional warning to prevent of a collision of the drill bit with the facial nerve during direct cochlear access (DCA). BACKGROUND Minimally invasive direct cochlear access (DCA) aims to eliminate the need for a mastoidectomy by drilling a small tunnel through the facial recess to the cochlea with the aid of stereotactic tool guidance. Because the procedure is performed in a blind manner, structures such as the facial nerve are at risk. Neuromonitoring is a commonly used tool to help surgeons identify the facial nerve (FN) during routine surgical procedures in the mastoid. Recently, neuromonitoring technology was integrated into a commercially available drill system enabling real-time monitoring of the FN. The objective of this study was to determine if this drilling system could be used to warn of an impending collision with the FN during robot-assisted DCA. MATERIALS AND METHODS The sheep was chosen as a suitable model for this study because of its similarity to the human ear anatomy. The same surgical workflow applicable to human patients was performed in the animal model. Bone screws, serving as reference fiducials, were placed in the skull near the ear canal. The sheep head was imaged using a computed tomographic scanner and segmentation of FN, mastoid, and other relevant structures as well as planning of drilling trajectories was carried out using a dedicated software tool. During the actual procedure, a surgical drill system was connected to a nerve monitor and guided by a custom built robot system. As the planned trajectories were drilled, stimulation and EMG response signals were recorded. A postoperative analysis was achieved after each surgery to determine the actual drilled positions. RESULTS Using the calibrated pose synchronized with the EMG signals, the precise relationship between distance to FN and EMG with 3 different stimulation intensities could be determined for 11 different tunnels drilled in 3 different subjects. CONCLUSION From the results, it was determined that the current implementation of the neuromonitoring system lacks sensitivity and repeatability necessary to be used as a warning device in robotic DCA. We hypothesize that this is primarily because of the stimulation pattern achieved using a noninsulated drill as a stimulating probe. Further work is necessary to determine whether specific changes to the design can improve the sensitivity and specificity.

Annexin A5-Conjugated Polymeric Micelles For Dual SPECT and Optical Detection of Apoptosis

Apoptosis, a form of programmed cell death, is critical to homoeostasis, normal development, and physiology. Dysregulation of apoptosis can lead to the accumulation of unwanted cells, such as occurs in cancer, and the removal of needed cells or disorders of normal tissues, such as heart, neurodegenerative, and autoimmune diseases. Noninvasive detection of apoptosis may play an important role in the evaluation of disease states and response to therapeutic intervention for a variety of diseases. It is desirable to have an imaging method to accurately detect and monitor this process in patients. In this study, we developed annexin A5-conjugated polymeric micellar nanoparticles dual-labeled with a near-infrared fluorescence fluorophores (Cy7) and a radioisotope (111In), named as 111In-labeled annexin A5-CCPM. In vitro studies demonstrated that annexin A5-CCPM could strongly and specifically bind to apoptotic cells. In vivo studies showed that apoptotic tissues could be clearly visualized by both single photon emission computed tomography (SPECT) and fluorescence molecular tomography (FMT) after intravenous injection of 111In-labeled Annexin A5-CCPM in 6 different apoptosis models. In contrast, there was little signal in respective healthy tissues. All the biodistribution data confirmed imaging results. Moreover, histological analysis revealed that radioactivity count correlated with fluorescence signal from the nanoparticles, and both signals co-localized with the region of apoptosis. In sum, 111In-labeled annexin A5-CCPM allowed visualization of apoptosis by both nuclear and optical imaging techniques. The complementary information acquired with multiple imaging techniques should be advantageous in improving diagnostics and management of patients.

Daytime Low Stratiform Cloud Detection on AVHRR Imagery

The near-real time retrieval of low stratiform cloud (LSC) coverage is of vital interest for such disciplines as meteorology, transport safety, economy and air quality. Within this scope, a novel methodology is proposed which provides the LSC occurrence probability estimates for a satellite scene. The algorithm is suited for the 1 × 1 km Advanced Very High Resolution Radiometer (AVHRR) data and was trained and validated against collocated SYNOP observations. Utilisation of these two combined data sources requires a formulation of constraints in order to discriminate cases where the LSC is overlaid by higher clouds. The LSC classification process is based on six features which are first converted to the integer form by step functions and combined by means of bitwise operations. Consequently, a set of values reflecting a unique combination of those features is derived which is further employed to extract the LSC occurrence probability estimates from the precomputed look-up vectors (LUV). Although the validation analyses confirmed good performance of the algorithm, some inevitable misclassification with other optically thick clouds were reported. Moreover, the comparison against Polar Platform System (PPS) cloud-type product revealed superior classification accuracy. From the temporal perspective, the acquired results reported a presence of diurnal and annual LSC probability cycles over Europe.

A New Approach for Automatic Removal of Movement Artifacts in Near-Infrared Spectroscopy Time Series by Means of Acceleration Data

Abstract: Near-infrared spectroscopy (NIRS) enables the non-invasive measurement of changes in hemodynamics and oxygenation in tissue. Changes in light-coupling due to movement of the subject can cause movement artifacts (MAs) in the recorded signals. Several methods have been developed so far that facilitate the detection and reduction of MAs in the data. However, due to fixed parameter values (e.g., global threshold) none of these methods are perfectly suitable for long-term (i.e., hours) recordings or were not time-effective when applied to large datasets. We aimed to overcome these limitations by automation, i.e., data adaptive thresholding specifically designed for long-term measurements, and by introducing a stable long-term signal reconstruction. Our new technique (“acceleration-based movement artifact reduction algorithm”, AMARA) is based on combining two methods: the “movement artifact reduction algorithm” (MARA, Scholkmann et al. Phys. Meas. 2010, 31, 649–662), and the “accelerometer-based motion artifact removal” (ABAMAR, Virtanen et al. J. Biomed. Opt. 2011, 16, 087005). We describe AMARA in detail and report about successful validation of the algorithm using empirical NIRS data, measured over the prefrontal cortex in adolescents during sleep. In addition, we compared the performance of AMARA to that of MARA and ABAMAR based on validation data.

Sentinel node mapping using hysteroscopic injection of indocyanine green and laparoscopic near-infrared fluorescence imaging in endometrial cancer staging.

Herein is presented a technique for minimally invasive sentinel node mapping. The patient had apparently early stage endometrial cancer. Sentinel node mapping was performed using a hysteroscopic injection of indocyanine green followed by laparoscopic sentinel node detection via near-infrared fluorescence. This technique ensures delineation of lymphatic drainage from the tumor area, thus achieving accurate detection of sentinel nodes.

Near infra-red-activatable nanocarriers for selective cancer diagnosis and treatment

Standard treatment strategies for cancer patients include surgery, radiation therapy, and chemotherapy. Although these strategies have been proven effective, they also have associated limitations. An attractive and innovative approach that can be used alone or in combination with the above modalities is based on the systemic or topical administration of a nanomaterial-based photoactive compound. Interaction with light in the near infrared (NIR) region results in either emission of fluorescence, which can be used for photodetection, or absorption of light which results in phototherapy. Nanomaterials have the advantage of providing multi-functional and unique properties in a single device that cannot be readily acquired with conventional small molecular weight compounds. ^ In this study, three different novel nanocarrier systems were designed and evaluated in mediating photodetection and phototherapy in the NIR. The first compound synthesized was a dual-labeled magnetic resonance/optical imaging agent for sentinel lymph node mapping and biopsy. This dual-labeled agent combines the high resolution of magnetic resonance imaging with the highly sensitive detection of optical imaging. The second imaging agent was an activatable optical imaging agent used to monitor cathepsin B activity in vivo and to probe the degradation of poly(L-glutamic acid). This polymeric nanocarrier offers highly sensitive technique for the detection of enzymatic activity, with is not yet possible with small molecular weight compounds. The third agent was a C225-conjugated hollow nanoshell that is targeted to epidermal growth factor receptors. This targeting agent has been demonstrated to mediate photothermal therapy both in vitro and in vivo. ^ These nanocarrier systems are an invaluable tool for the detection of cancer and many other diseases. With improved targeted delivery of these agents, the ability to diagnose diseases will become more sensitive and more specific. Finally, when designed properly, these agents would allow concurrent diagnosis and treatment of patients of various diseases. ^

Near-coastal circum-Antarctic iceberg size distributions determined from Synthetic Aperture Radar images

The Radarsat-1 Antarctic Mapping Project (RAMP) compiled a mosaic of Antarctica and the adjacent ocean zone from more than 3000 high-resolution Synthetic Aperture Radar (SAR) images acquired in September and October 1997. The mosaic with a pixel size of 100 m was used to determine iceberg size distributions around Antarctica, combining an automated detection with a visual control of all icebergs larger than 5 km**2 and correction of recognized false detections. For icebergs below 5 km**2 in size, the numbers of false detections and accuracies of size retrievals were analyzed for three test sites. Nearly 7000 icebergs with horizontal areas between 0.3 and 4717.7 km**2 were identified in a near-coastal zone of varying width between 20 and 300 km. The spatial distributions of icebergs around Antarctica were calculated for zonal segments of 20° angular width and related to the types of the calving fronts in the respective section. Results reveal that regional variations of the size distributions cannot be neglected. The highest ice mass accumulations were found at positions of giant icebergs (> 18.5 km) but also in front of ice shelves from which larger numbers of smaller icebergs calve almost continuously. Although the coastal oceanic zone covered by RAMP is too narrow compared to the spatial coverage needed for oceanographic research, this study nevertheless demonstrates the usefulness of SAR images for iceberg research and the need for repeated data acquisitions extending ocean-wards over distances of 500 km and more from the coast to monitor iceberg melt and disintegration and the related freshwater input into the ocean.

Study on the effects of near-future ocean acidification on marine yeasts: a microcosm approach

Marine yeasts play an important role in biodegradation and nutrient cycling and are often associated with marine flora and fauna. They show maximum growth at pH levels lower than present-day seawater pH. Thus, contrary to many other marine organisms, they may actually profit from ocean acidification. Hence, we conducted a microcosm study, incubating natural seawater from the North Sea at present-day pH (8.10) and two near-future pH levels (7.81 and 7.67). Yeasts were isolated from the initial seawater sample and after 2 and 4 weeks of incubation. Isolates were classified by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and representative isolates were identified by partial sequencing of the large subunit rRNA gene. From the initial seawater sample, we predominantly isolated a yeast-like filamentous fungus related to Aureobasidium pullulans, Cryptococcus sp., Candida sake, and various cold-adapted yeasts. After incubation, we found more different yeast species at near-future pH levels than at present-day pH. Yeasts reacting to low pH were related to Leucosporidium scottii, Rhodotorula mucilaginosa, Cryptococcus sp., and Debaryomyces hansenii. Our results suggest that these yeasts will benefit from seawater pH reductions and give a first indication that the importance of yeasts will increase in a more acidic ocean.