Laimutis Telksnys’s research while affiliated with Vilnius University and other places

Capillary electrophoresis often causes unrepeatable peak migration times in the electropherogram due to changes of electroosmosis, yet in some cases this separation technique does not have a replacement alternative. Some attempts to overcome this issue have been performed introducing internal standards into the sample and compensating peak shifting in time. However, existing vector calculation-based methods are computationally intensive for portable instrumentation and usually limited to post-processing applications with 1 or 2 markers. In this work, an original approach of compensating peak migration time shift via signal discretization period correction is proposed. Using the proposed method, the number of reference points or markers that are used for compensation is extended. This method is effective in compensating migration time of peaks in real samples, where high sample injection volumes are used. Using 4 reference peaks in compensation, the method was capable of reducing the relative standard deviation of migration time of the peaks in the electropherograms more than 15 times. Corrected signal discretization periods indicated very high correlations with recorded separation currents, what can be perspective developing an adaptive peak migration time compensation method in capillary electrophoresis.

Portable and autonomous analytical instrumentation is becoming more important. Portable instrumentation can be designed via the miniaturization approach and this is a challenging task due to: (i) the limited battery power supply, (ii) a low number of mechanical and moving parts allowed in the design and (iii) susceptibility to changing environment and temperature fluctuations. In this work we describe the design of a light emitting diode (LED) based 3D printed miniaturized colorimeter (dimensions: 5 cm × 4 cm × 4.5 cm (length, width, height), weight less than 56 g). The colorimeter was optimized for determination of the total phenolic compound content, the total flavonoid content and radical scavenging activity. The designed instrument provides comparable results to those of a conventional desktop spectrophotometer existing on the market. The designed LED based miniaturized colorimeter has wireless communication capability. This work demonstrates that this instrument can be applied investigating real samples.

The methodology described in this paper will significantly reduce the time required for understanding the relations between chromatographic data and bio-activity assays. The methodology is a hybrid of hypothesis based and data-driven scientific approaches. In this work, a novel chromatographic data segmentation method is proposed, which demonstrates the capability of finding what volatile substances are responsible for antiviral and cytotoxic effects in the medicinal plant extracts. Up to now the full potential of the separation methods has not been exploited in the life sciences. This was due to the lack of data ordering methods capable to adequately preparing the chromatographic information. Furthermore, the data analysis methods suffer of multidimensionality requiring a large number of investigated data points. A new method is described for processing any chromatographic information into a vector. The obtained vectors of highly complex and different origin samples can be compared mathematically. The proposed method, efficient with relatively small sized datasets, does not suffer of multidimensionality. In this novel analytical approach, the samples did not need fractionation and purification, what is typically used in hypothesis based scientific research. All investigations were performed using crude extracts possessing hundreds of phyto-substances. The antiviral properties of medicinal plant extracts were investigated using gas chromatography-mass spectrometry, antiviral tests and proposed data analysis method. The findings suggested that: (i) beta-cis-caryophyllene, linalool, eucalyptol possess antiviral activity, while (ii) thujone does not, and (iii) alpha-, beta-thujones, cis-p-menthan-3-one, estragole show cytotoxic effects.

The problem of speech corpus for design of human-computer interfaces working in voice recognition and synthesis mode is investigated. Specific requirements of speech corpus for speech recognizers and synthesizers were accented. It has been discussed that in order to develop above mentioned speech corpus, it has to consist of two parts. One part of speech corpus should be presented for the needs of Lithuanian text-to-speech synthesizers, another part of speech corpus-for the needs of Lithuanian speech recognition engines. It has been determined that the part of speech corpus designed for speech recognition engines has to ensure the availability to present language specificity by the use of different sets of phonemes. According to the research results, the speech corpus Liepa, which consists of two parts, was developed. This speech corpus opens possibilities for cost-effective and flexible development of human-computer interfaces working in voice recognition and synthesis mode.

One of the main problems of the remote complex sample analysis instrumentation is that such systems are susceptible to temperature fluctuations. Temperature regulation is energetically ineffective, and it is not used in most of the field portable analytical systems. Separations performed in a changing temperature environment provide electropherograms with considerable baseline fluctuations, resulting in significant errors in detection and integration of the peaks. This paper describes electropherogram baseline compensation that is suitable for the capillary electrophoresis ‐ contactless conductivity detection analytical method. The baseline compensation utilizes linear or polynomial data processing methods, and can be programmed in‐line using simple microcontroller, or on‐line and off‐line in data acquisition software. This method is targeted for field portable and autonomous analytical systems that are utilized in a fluctuating environment. This article is protected by copyright. All rights reserved

In the present work we demonstrate the novel approach to improve the sensitivity of the “out of lab” portable capillary electrophoretic measurements. Nowadays, many enhancement methods are: (i) underused (non-optimal), (ii) overused (distorts the data), or (iii) inapplicable in field-portable instrumentation due to lack of computational power. Described innovative migration velocity-adaptive moving average method uses optimal averaging window size and can be easily implemented with microcontroller. The contactless conductivity detection was used as a model for the development of a signal processing method and the demonstration of its impact on the sensitivity. The frequency characteristics of the recorded electropherograms and peaks were clarified. Higher electrophoretic mobility analytes exhibit higher frequency peaks, while lower electrophoretic mobility analytes exhibit lower frequency peaks. Based on obtained data, a migration velocity-adaptive moving average algorithm was created, adapted and programmed into capillary electrophoresis data processing software. Employing the developed algorithm, each data point is processed depending on a certain migration time of the analyte. Because of the implemented migration velocity-adaptive moving average method the signal-to-noise ratio improved up to 11 times for sampling frequency of 4.6 Hz and up to 22 times for sampling frequency of 25 Hz. This paper could potentially be used as a methodological guideline for the development of new smoothing algorithms that require adaptive conditions in capillary electrophoresis, and other separation methods.

The problem of the parsing accuracy of simple sentences is solved. The case of the language with high inflexion is investigated. The task is addressed by the example of the Lithuanian language, which one root can give hundreds or even more than one thousand word forms. The method of estimation of the parsing accuracy of the simple sentences of such language is given, which is based on the usage of knowledge of language consistent patterns. It is taken note, that in the case of language with high inflection and small number of users the usage of the statistical data on language is strongly restricted. The method of the accuracy estimation of the parsing of simple sentences is presented. The algorithm of implementation of the software is described. The validity of the propositions is proved by experiments. The material of the Lithuanian corpus was used for the experiments. The recommendations are given for the increasing of the accuracy of the parsing of simple sentences for the languages with high inflection.

The mobile application capabilities for extensive heart rate data analysis systems. The architecture and design of the environment tools for the software described. Presenting visualized graphs of the data structures and examples of the software created. Analyzed results for tablet computers capabilities working with large data arrays are provided. Explains the difficulties of medical personnel while working with patients that have heart disease.

Speech keyword spotting is a retrieval of all instances of a given keyword in utterances. This paper presents improved template based keyword spotting algorithm. It solves speaker dependent speech segment detection in continuous speech with small vocabulary. The rules based segmentation algorithm allows to extract quasi-syllables. We evaluated the algorithm by experimental with synthetic signals. The algorithm results outperform classical keyword spotting algorithm with experimental data.