DOKAZNI LANAC

U našoj kriminalističkoj literaturi, kao i u sudskoj praksi, problemu obezbjeđi-vanja autentičnosti i integriteta dokaza i dokaznog lanca se nije pridavala velika pažnja. To pitanje se rješavalo uzgredno i samo ukoliko su posebne okolnosti ukazivale na to da je došlo do narušavanja tzv. dokaznog lanca. Podrazumijevalo se da je dokaz obezbijeđen i autentičan kada se pojavi na sudu. Međutim, u zadnje vrijeme se u praksi sve više pojavljuju problemi sa autentičnošću integriteta dokaza i sa (prigovorima) povredama dokaznog lanca. Usljed navedenog bitno je da se etablira i afirmiše procedura obezbjeđivanja integriteta dokaznog lanca. U radu će se ukazati na pojam i značaj dokaznog lanca, te na mehanizme obezbjeđivanja integriteta dokaznog lanca, ukazujući na izvore digitalnih dokaza kao specifične sa aspekta obezbjeđivanja integriteta dokaznog lanca

On the influence of aging on classification performance in the visual EEG oddball paradigm using statistical and temporal features

The utilization of a non-invasive electroencephalogram (EEG) as an input sensor is a common approach in the field of the brain–computer interfaces (BCI). However, the collected EEG data pose many challenges, one of which may be the age-related variability of event-related potentials (ERPs), which are often used as primary EEG BCI signal features. To assess the potential effects of aging, a sample of 27 young and 43 older healthy individuals participated in a visual oddball study, in which they passively viewed frequent stimuli among randomly occurring rare stimuli while being recorded with a 32-channel EEG set. Two types of EEG datasets were created to train the classifiers, one consisting of amplitude and spectral features in time and another with extracted time-independent statistical ERP features. Among the nine classifiers tested, linear classifiers performed best. Furthermore, we show that classification performance differs between dataset types. When temporal features were used, maximum individuals’ performance scores were higher, had lower variance, and were less affected overall by within-class differences such as age. Finally, we found that the effect of aging on classification performance depends on the classifier and its internal feature ranking. Accordingly, performance will differ if the model favors features with large within-class differences. With this in mind, care must be taken in feature extraction and selection to find the correct features and consequently avoid potential age-related performance degradation in practice

Stroop in motion

There is conflicting evidence about how interference control in healthy adults is affected by walking as compared to standing or sitting. Although the Stroop paradigm is one of the best-studied paradigms to investigate interference control, the neurodynamics associated with the Stroop task during walking have never been studied. We investigated three Stroop tasks using variants with increasing interference levels – word-reading, ink-naming, and the switching of the two tasks, combined in a systematic dual-tasking fashion with three motor conditions – sitting, standing, and treadmill walking. Neurodynamics underlying interference control were recorded using the electroencephalogram. Worsened performance was observed for the incongruent compared to congruent trials and for the switching Stroop compared to the other two variants. The early frontocentral event-related potentials (ERPs) associated with executive functions (P2, N2) differentially signaled posture-related workloads, while the later stages of information processing indexed faster interference suppression and response selection in walking compared to static conditions. The early P2 and N2 components as well as frontocentral Theta and parietal Alpha power were sensitive to increasing workloads on the motor and cognitive systems. The distinction between the type of load (motor and cognitive) became evident only in the later posterior ERP components in which the amplitude non-uniformly reflected the relative attentional demand of a task. Our data suggest that walking might facilitate selective attention and interference control in healthy adults. Existing interpretations of ERP components recorded in stationary settings should be considered with care as they might not be directly transferable to mobile settings

Recovery of bioactive molecules from Hypericum perforatum L. dust using microwave-assisted extraction

Microwave-assisted extraction (MAE) conditions were optimized to improve extract quality of medicinal herb — Hypericum perforatum L. (St. John’s wort) dust. Response surface methodology was applied initially to obtain the highest concentration of total polyphenols in extract solids (MAE-e). St. John’s wort was mixed with 30% ethanol in 50 mL/g solvent to solid ratio, and treated with 170 W microwave power for 40 s to yield an extract with 411.26 ± 6.21 mg GAE/g of polyphenols. This extract contained a significantly higher content of polyphenols (42.50%) and had significantly higher antioxidant activity than the macerate obtained by using European Medicines Agency (EMA) recommended procedure. The advantage of the EMA procedure was the higher yield of extract per gram of plant material. Therefore, another set of MAE conditions was defined to maximize the yield of polyphenols per gram of plant material (MAE-p). The MAE-p extract was produced by using 30% ethanol, 10 mL/g solvent to solid ratio, and 170 W microwave power for 100 s, which was, again, a markedly shorter period than 72 h of maceration. The MAE-p extract had a slightly, but significantly higher yield (5.2%), more polyphenols (8.8%), and improved antioxidant activity compared to the EMA macerate. Antimicrobial activity against several pathogens was stronger for the MAE extracts. The chemical composition of extracts was slightly different and MAE favored extraction of glycosides, in particular, rutin (quercetin-3-O-rutinoside), while the EMA macerate contained quercetin aglycon in the highest concentration. Our study demonstrates that statistically planned experiments allow for significant improvement of the extraction process, which application could facilitate better use of natural resources and deliver more potent extracts than those obtained by currently recommended procedures

A data-driven machine learning approach for brain-computer interfaces targeting lower limb neuroprosthetics

Prosthetic devices that replace a lost limb have become increasingly performant in recent years. Recent advances in both software and hardware allow for the decoding of electroencephalogram (EEG) signals to improve the control of active prostheses with brain-computer interfaces (BCI). Most BCI research is focused on the upper body. Although BCI research for the lower extremities has increased in recent years, there are still gaps in our knowledge of the neural patterns associated with lower limb movement. Therefore, the main objective of this study is to show the feasibility of decoding lower limb movements from EEG data recordings. The second aim is to investigate whether well-known neuroplastic adaptations in individuals with an amputation have an influence on decoding performance. To address this, we collected data from multiple individuals with lower limb amputation and a matched able-bodied control group. Using these data, we trained and evaluated common BCI methods that have already been proven effective for upper limb BCI. With an average test decoding accuracy of 84% for both groups, our results show that it is possible to discriminate different lower extremity movements using EEG data with good accuracy. There are no significant differences (p = 0.99) in the decoding performance of these movements between healthy subjects and subjects with lower extremity amputation. These results show the feasibility of using BCI for lower limb prosthesis control and indicate that decoding performance is not influenced by neuroplasticity-induced differences between the two groups

Hemodinamika femoro-poplitealne by-pass hirurgije metodom analize konačnih elemenata

Objective. Femoropopliteal bypass is indicated in the advanced stage of peripheral arterial occlusive disease. The indications for surgical treatment are determined on the basis of a clinical exam, "ankle-brachial index" and angiographic findings. Using the finite element analysis method, three-dimensional models can be made based on angiography, and these models can be used to measure different physical quantities and calculate the value of the "ankle-brachial index". The aim of this paper is to show the hemodynamics of arteries by using the finite element analysis method based on preoperative and postoperative angiography, as well as physical quantities that can be measured in this way. Methods. This case shows the hemodynamics of femoropopliteal bypass in the preoperative and postoperative models. The models obtained by finite element analysis show: pressure, shear stress, velocities, and streamlines. The pressure, i.e. the "ankle-brachial index", was compared with the values measured on the patient, while the other three values were compared preoperatively and postoperatively. Results. Postoperatively, higher values of pressure and "ankle-brachial index" were measured on the patient and on the models. Wall shear stress and velocity values were reduced in postoperative models. The streamlines showed a dominant anterior tibial artery. Conclusion. The values of physical quantities measured on patient and on the models obtained by the finite element analysis method correlate significantly. Some physical quantities could indicate the "weak points" of a particular model.Publishe

Neuromuscular assessment of force development, postural, and gait performance under cognitive-motor dual-tasking in healthy older adults and early Parkinson\u27s disease patients

Background: Neuromuscular dysfunction is common in older adults and more pronounced in neurodegenerative diseases. In Parkinson\u27s disease (PD), a complex set of factors often prevents the effective performance of activities of daily living that require intact and simultaneous performance of the motor and cognitive tasks. Methods: The cross-sectional study includes a multifactorial mixed-measure design. Between-subject factor grouping the sample will be Parkinson’s Disease (early PD vs. healthy). The within-subject factors will be the task complexity (single- vs. dual-task) in each motor activity, i.e., overground walking, semi-tandem stance, and isometric knee extension, and a walking condition (wide vs. narrow lane) will be implemented for the overground walking activity only. To study dual-task (DT) effects, in each motor activity participants will be given a secondary cognitive task, i.e., a visual discrimination task for the overground walking, an attention task for the semi-tandem, and mental arithmetic for the isometric extension. Analyses of DT effects and underlying neuronal correlates will focus on both gait and cognitive performance where applicable. Based on an a priori sample size calculation, a total N = 42 older adults (55-75 years) will be recruited. Disease-specific changes such as laterality in motor unit behavior and cortical control of movement will be studied with high-density surface electromyography and electroencephalography during static and dynamic motor activities, together with whole-body kinematics. Discussion: This study will be one of the first to holistically address early PD neurophysiological and neuromuscular patterns in an ecologically valid environment under cognitive-motor DT conditions of different complexities. The outcomes of the study aim to identify the biomarker for early PD either at the electrophysiological, muscular or kinematic level or in the communication between these systems