4 research outputs found
The 8th International Conference on Time Series and Forecasting
The aim of ITISE 2022 is to create a friendly environment that could lead to the establishment or strengthening of scientific collaborations and exchanges among attendees. Therefore, ITISE 2022 is soliciting high-quality original research papers (including significant works-in-progress) on any aspect time series analysis and forecasting, in order to motivating the generation and use of new knowledge, computational techniques and methods on forecasting in a wide range of fields
Iterative OPDD Based Signal Probability Calculation
This paper presents an improved method to accurately estimate signal probabilities using ordered partial decision diagrams (OPDDs) [Kodavarti 93] for partial representation of the functions at the circuit lines. OPDDs which are limited to a certain maximum number of nodes are built iteratively with different variable orderings to efficiently explore different regions of the function. Signal probability bounds (upper and lower) are computed from the OPDDs. From each OPDD, information is extracted to tighten the signal probability bound and guide the variable ordering for the next OPDD. By restricting the size of each OPDD to a small number of nodes, they can be constructed and processed quickly to obtain a fast and accurate estimate of signal probabilities. Experimental results demonstrate the effectiveness of the approach compared with existing methods. 1
Ultrasensitive detection of toxocara canis excretory-secretory antigens by a nanobody electrochemical magnetosensor assay.
peer reviewedHuman Toxocariasis (HT) is a zoonotic disease caused by the migration
of the larval stage of the roundworm Toxocara canis in the human host.
Despite of being the most cosmopolitan helminthiasis worldwide, its
diagnosis is elusive. Currently, the detection of specific immunoglobulins
IgG against the Toxocara Excretory-Secretory Antigens (TES), combined
with clinical and epidemiological criteria is the only strategy to diagnose
HT. Cross-reactivity with other parasites and the inability to distinguish
between past and active infections are the main limitations of this
approach. Here, we present a sensitive and specific novel strategy to
detect and quantify TES, aiming to identify active cases of HT. High
specificity is achieved by making use of nanobodies (Nbs), recombinant
single variable domain antibodies obtained from camelids, that due to
their small molecular size (15kDa) can recognize hidden epitopes not
accessible to conventional antibodies. High sensitivity is attained by the
design of an electrochemical magnetosensor with an amperometric readout
with all components of the assay mixed in one single step. Through
this strategy, 10-fold higher sensitivity than a conventional sandwich
ELISA was achieved. The assay reached a limit of detection of 2 and15
pg/ml in PBST20 0.05% or serum, spiked with TES, respectively. These
limits of detection are sufficient to detect clinically relevant toxocaral
infections. Furthermore, our nanobodies showed no cross-reactivity
with antigens from Ascaris lumbricoides or Ascaris suum. This is to our
knowledge, the most sensitive method to detect and quantify TES so far,
and has great potential to significantly improve diagnosis of HT. Moreover,
the characteristics of our electrochemical assay are promising for the
development of point of care diagnostic systems using nanobodies as a
versatile and innovative alternative to antibodies. The next step will be the
validation of the assay in clinical and epidemiological contexts