Organsko-biološka (ekološka) proizvodnja sve je zastupljenija u poljoprivredi svijeta tako i Hrvatske. Njome se želi postići održivost sustava bez uporabe sintetičkih gnojiva, pesticida, regulatora ...rasta i genetski modificiranih biljaka. Organska proizvodnja voća u svijetu prostire se na 12,6 milijuna hektara, od čega se jabuka uzgaja na 82 983 hektara. U Europi su najznačajniji proizvođači Italija, Njemačka, Austrija, Nizozemska, Belgija i Francuska. U Republici Hrvatskoj organsko-biološka proizvodnja voća zauzima 8 962 hektara, od čega na proizvodnju jabuka otpada 470 hektara. Prema dosadašnjim istraži-vanjima, prirodi u organskim proizvodnim sustavima manji su od onih u integriranim proizvodnjama, međutim cijena proizvoda je veća pa se time taj nedostatak može nadomjestiti. Hrana iz organske proizvodnje ime više nutricionistički poželjnih spojeva (vitamini, antioksidansi), a manje nepoželjnih spojeva kao što su teški metali, mikotoksini i ostatci pesticida. Osim toga, jabuke iz organske proizvodnje imaju veću tvrdoću i bolji okus.
The COVID-19 pandemic has adverse consequences on human psychology and behavior long after initial recovery from the virus. These COVID-19 health sequelae, if undetected and left untreated, may lead ...to more enduring mental health problems, and put vulnerable individuals at risk of developing more serious psychopathologies. Therefore, an early distinction of such vulnerable individuals from those who are more resilient is important to undertake timely preventive interventions. The main aim of this article is to present a comprehensive multimodal conceptual approach for addressing these potential psychological and behavioral mental health changes using state-of-the-art tools and means of artificial intelligence (AI). Mental health COVID-19 recovery programs at post-COVID clinics based on AI prediction and prevention strategies may significantly improve the global mental health of ex-COVID-19 patients. Most COVID-19 recovery programs currently involve specialists such as pulmonologists, cardiologists, and neurologists, but there is a lack of psychiatrist care. The focus of this article is on new tools which can enhance the current limited psychiatrist resources and capabilities in coping with the upcoming challenges related to widespread mental health disorders. Patients affected by COVID-19 are more vulnerable to psychological and behavioral changes than non-COVID populations and therefore they deserve careful clinical psychological screening in post-COVID clinics. However, despite significant advances in research, the pace of progress in prevention of psychiatric disorders in these patients is still insufficient. Current approaches for the diagnosis of psychiatric disorders largely rely on clinical rating scales, as well as self-rating questionnaires that are inadequate for comprehensive assessment of ex-COVID-19 patients' susceptibility to mental health deterioration. These limitations can presumably be overcome by applying state-of-the-art AI-based tools in diagnosis, prevention, and treatment of psychiatric disorders in acute phase of disease to prevent more chronic psychiatric consequences.
Contemporary psychiatry is looking at affective sciences to understand human behavior, cognition and the mind in health and disease. Since it has been recognized that emotions have a pivotal role for ...the human mind, an ever increasing number of laboratories and research centers are interested in affective sciences, affective neuroscience, affective psychology and affective psychopathology. Therefore, this paper presents multidisciplinary research results of Laboratory for Interactive Simulation System at Faculty of Electrical Engineering and Computing, University of Zagreb in the stress resilience. Patient's distortion in emotional processing of multimodal input stimuli is predominantly consequence of his/her cognitive deficit which is result of their individual mental health disorders. These emotional distortions in patient's multimodal physiological, facial, acoustic, and linguistic features related to presented stimulation can be used as indicator of patient's mental illness. Real-time processing and analysis of patient's multimodal response related to annotated input stimuli is based on appropriate machine learning methods from computer science. Comprehensive longitudinal multimodal analysis of patient's emotion, mood, feelings, attention, motivation, decision-making, and working memory in synchronization with multimodal stimuli provides extremely valuable big database for data mining, machine learning and machine reasoning. Presented multimedia stimuli sequence includes personalized images, movies and sounds, as well as semantically congruent narratives. Simultaneously, with stimuli presentation patient provides subjective emotional ratings of presented stimuli in terms of subjective units of discomfort/distress, discrete emotions, or valence and arousal. These subjective emotional ratings of input stimuli and corresponding physiological, speech, and facial output features provides enough information for evaluation of patient's cognitive appraisal deficit. Aggregated real-time visualization of this information provides valuable assistance in patient mental state diagnostics enabling therapist deeper and broader insights into dynamics and progress of the psychotherapy.
Significant proportion of psychological problems related to combat stress in recent large peacekeeping operations underscores importance of effective methods for strengthening the stress resistance ...of military personnel. Adaptive control of virtual reality (VR) stimulation, based on estimation of the subject's emotional state from physiological signals, may enhance existing stress inoculation training (SIT). Physiology-driven adaptive VR stimulation can tailor the progress of stressful stimuli delivery to the physiological characteristics of each individual, which is indicated for improvement in stress resistance. Therefore, following an overview of SIT and its applications in the military setting, generic concept of physiology-driven adaptive VR stimulation is presented in the paper. Toward the end of the paper, closed-loop adaptive control strategy applicable to SIT is outlined.
Contemporary psychiatry is looking at affective sciences to understand human behavior, cognition and the mind in health and
disease. Since it has been recognized that emotions have a pivotal role for ...the human mind, an ever increasing number of
laboratories and research centers are interested in affective sciences, affective neuroscience, affective psychology and affective
psychopathology. Therefore, this paper presents multidisciplinary research results of Laboratory for Interactive Simulation System
at Faculty of Electrical Engineering and Computing, University of Zagreb in the stress resilience. Patient’s distortion in emotional
processing of multimodal input stimuli is predominantly consequence of his/her cognitive deficit which is result of their individual
mental health disorders. These emotional distortions in patient’s multimodal physiological, facial, acoustic, and linguistic features
related to presented stimulation can be used as indicator of patient’s mental illness. Real-time processing and analysis of patient’s
multimodal response related to annotated input stimuli is based on appropriate machine learning methods from computer science.
Comprehensive longitudinal multimodal analysis of patient’s emotion, mood, feelings, attention, motivation, decision-making, and
working memory in synchronization with multimodal stimuli provides extremely valuable big database for data mining, machine
learning and machine reasoning. Presented multimedia stimuli sequence includes personalized images, movies and sounds, as well
as semantically congruent narratives. Simultaneously, with stimuli presentation patient provides subjective emotional ratings of
presented stimuli in terms of subjective units of discomfort/distress, discrete emotions, or valence and arousal. These subjective
emotional ratings of input stimuli and corresponding physiological, speech, and facial output features provides enough information
for evaluation of patient’s cognitive appraisal deficit. Aggregated real-time visualization of this information provides valuable
assistance in patient mental state diagnostics enabling therapist deeper and broader insights into dynamics and progress of the
psychotherapy.
The paper presents design and evaluation of emotional state estimator based on artificial neural networks for physiology-driven adaptive virtual reality (VR) stimulation. Real-time emotional state ...estimation from physiological signals enables adapting the stimulations to the emotional response of each individual. Estimation is first evaluated on artificial subjects, which are convenient during software development and testing of physiology-driven adaptive VR stimulation. Artificial subjects are implemented in the form of parameterized skin conductance and heart rate generators that respond to emotional inputs. Emotional inputs are a temporal sequence of valence/arousal annotations, which quantitatively express emotion along unpleasant-pleasant and calm-aroused axes. Preliminary evaluation of emotional state estimation is also performed with a limited set of humans. Human physiological signals are acquired during simultaneous presentation of static pictures and sounds from valence/arousal-annotated International Affective Picture System and International Affective Digitized Sounds databases.