Traditional solvent extraction of blueberry powder : extraction and optimization

De Nordiska skogsbären är idag väldigt attraktiva på världsmarknaden, idag används blåbäret blandanat som ett råmaterial för produktion av näringstillskott, kosmetik och hälsoprodukter. Men av de blåbär som växer i de svenska skogarna plockas bara uppskattningsvis fem procent. Det finns därmed i Sverige en outnyttjad resurs som år efter år ruttnar bort i de svenska skogarna. Syftet med denna studie var att undersöka effekten av olika extraktionsbetingelse och kunna bestämma de optimala förhållandet mellan olika processparametrar. Detta för att maximera extraktionen av fenoler ur presskaka av blåbär. Studien syftade till att jämföra traditionell lösningsmedelsextraktion och extraktion med hjälp av Rotating Bed Reactor (RBR) och hur dessa två extraktionsmetoder skiljer sig åt rent tekniskt för extraktion av antocyanin. I Studien valdes det att fokuseras på tre stycken parametrar dessa var torrsubstans (TS), temperatur (T) och etanolkoncentration (EtOH). Resultatet av studien visade på att den körparameter som hade störst påverkan på extraktionen av fenoler var torrsubstans. Detta var gemensamt för de båda extraktionsmetoderna. EtOH hade ingen signifikant påverkan för extraktionen av fenoler för den traditionella lösningsmedelsextraktionen men det fanns en liten signifikant påverkan för RBR extraktionen. Temperaturen skiljde sig så att, signifikansnivån var högre i början för RBR extraktionen jämfört med traditionella lösningsmedelsextraktionen där signifikansnivån var som störst vid 16 minuter.The Nordic berries are very attractive on the international market. The bilberry is for instance used as a raw material for the production of nutrition supplements, cosmetics and other health products. Of the bilberries that grows in the Swedish forests today only five percent is collected. There is thus an untapped resource that year after year are wasted away in the Swedish forests. The objective of this study was to investigate the effect of various extraction conditions and determine the optimal ratio between the various parameters and to find the best conditions to maximize the extraction of phenols from the press residue of bilberry. The study aimed at comparing traditional solvent extraction and extraction using Rotating Bed Reactor (RBR) and how these two extraction methods differs technically for extraction of anthocyanins. The study focuses on three extraction parameters. The parameters that was selected was dry matter extracted (TS), temperature and ethanol concentration (EtOH). The results of the study showed that the parameter with the greatest impact of extraction of phenols was TS. This was valid for the two extraction methods. EtOH had no significant impact for the extraction of phenols for the traditional solvent extraction, but there was a small significant effect of EtOH for the RBR extraction. The temperature differed in the way that the significance level was higher in the beginning for the RBR extraction method, compared to the traditional solvent extraction where the significance level was not significant until 16 minutes

Natur, Kunst und Liebe in der Philosophie Vladimir Solov'evs

Vladimir Solov'ev gehört zu den bedeutendsten Erscheinungen des geistigen Rußlands. Sein Werk fällt in die letzten Jahrzehnte des neunzehnten Jahrhunderts, die Auswirkung dieses Werkes in das zwanzigste . . . Alle geistesgeschichtlichen Arbeiten Vladimir Solov'evs kämpfen mit Leidenschaft gegen den Rationalismus in der Philosophie und für die Rückführung der in sich geeinten und befriedeten Welt in den Schoß Gottes. So ist vor allen Dingen seine Kritik an dem westeuropäischen Denken zu verstehen, die so manches Gemeinsame mit der Gedankenwelt der Slavophilen hat

Ökar en sommarkurs för tjejer jämställdhet vid högre skogliga utbildningar?

Skogsbruket har traditionellt varit mansdominerat och även idag märks tydliga skillnader mellan mäns och kvinnors förutsättningar och möjligheter inom skogssektorn. För att öka unga tjejers intresse för skog och locka dem att söka en högre utbildning inom skog och/eller arbeta inom skogssektorn anordnas det sedan 2009 en sommarkurs för tjejer i Skinnskatteberg. Initiativet till kursen togs av elever på Skogsmästarskolan och sedan 2010 har SLU anordnat och finansierat kursen. Utvärderingar har genomförts efter varje kurstillfälle men däremot ingen övergripande undersökning av deltagarnas bakgrund, uppfattning av kursen och hur kursen påverkat deras uppfattning av skogen och skogsbruket. Arbetet har bestått av en enkätundersökning av deltagare i kursen mellan åren 2009-2014. Undersökningen syftade till att utvärdera kursens upplägg, innehåll och genomförande och hur den bidragit till en högre jämställdhet vid högre skogliga utbildningar och/eller inom skogssektorn. Vikten har legat på hur många tjejer och med vilken varierande skoglig bakgrund som sökt högre utbildning inom skog efter att ha gått kursen. Undersökningen gjordes våren 2015 och utvärderingen baserades på web-enkätsvar från 65 deltagare i kursen mellan åren 2009-2014 samt kursutvärderingar, rapporter och intervjuer med nyckelpersoner för kursen. Datat sammanställdes och analyserades i MiniTab. Enkäten hade inslag av både kvantitativ och kvalitativ karaktär. Kursen är överlag väldigt uppskattad av deltagarna. En tredjedel av deltagarna har starkt skoglig bakgrund och majoriteten av deltagarna har sedan tidigare skoglig erfarenhet och/eller skogligt intresse. Kursen annonseras till största del i skogstidningar och på SLUs hemsida och når därför inte tjejer utan skoglig bakgrund. Då kursen till stor del endast når deltagare med skoglig bakgrund (mer än bara ett intresse att lära sig mer om skog) fungerar kursen främst som en informerande kurs om skogliga utbildningar och arbete inom skogssektorn. Därmed stärker kursen i de flesta fall endast den enskilde deltagarens beslut att endera söka eller inte söka en högre utbildning inom skog.Forestry has traditionally been male-dominated and even today there are distinct differences between the opportunities and prerequisite of men and women. To increase young girls' interest in forest and entice them to seek a higher education in forestry and/or work in the forestry sector a summer course for girls has been held since 2009 in Skinnskatteberg. The initiative for the course was taken by students at Skogsmästarskolan and since 2010, SLU has organized and financed the course. Evaluations have been made after each course, but no extensive survey of the participants' background, perception of the course and how the course affected their perceptions of forests and forestry has been made. The work consisted of a survey of participants between the years 2009-2014. The study aimed to evaluate the course content and advertising, and the courses role in increasing gender equality in higher education in forestry and/or the forest sector. The study’s focus was on how many girls with varying forest background who sought higher education in forestry after participating in the course. The study was conducted in the spring of 2015 and the evaluation was based on the web-survey responses from 65 participants between the years 2009-2014 and course evaluations, reports, and interviews with key persons for the course. The data were compiled and analyzed in Minitab. The questionnaire had questions with both quantitative and qualitative elements. The course is generally highly appreciated by the participants. A third of the total amount of participants has a strong forest background. The majority of participants have forest experience and/or forest interest. The course is advertised mostly in forest newspapers and on SLU's website and therefore does not reach girls without forest background. The participants have mainly some kind of forest background (more than just an interest to learn more about forests and forestry) and the course is therefore mainly an informative course about forest education and work within the forest sector. The course, in most cases, only strengthen the individual participant´s decision to seek a higher education in forestry or not to seek a higher education in forestry

Correlation of arterial blood pressure to synchronous piezo, impedance and photoplethysmographic signal features : Investigating pulse wave features and transit times

In this paper we investigate which pulse wave pick-up technologies are well suited for blood pressure trend estimation. We use custom built hardware to acquire electrocardiographic, applanation-tonometric, photo- and impedance-plethysmographic signals during low intensity workouts. Beat-to-beat features and pulse wave runtimes are correlated to the reference arterial blood pressure. Temporal lag adjustment is performed to determine the latency of feature response. Best results are obtained for systolic arterial blood pressure. These suggest that every subject has a range of well-performing features, but it is not consistent among all. Spearman Rho values reach in excess of 0.8, with their significance being validated by p-values lower than 0.01

Wearable Cardiorespiratory Monitoring Employing a Multimodal Digital Patch Stethoscope: Estimation of ECG, PEP, LVET and Respiration Using a 55 mm Single-Lead ECG and Phonocardiogram

Cardiovascular diseases are the main cause of death worldwide, with sleep disordered breathing being a further aggravating factor. Respiratory illnesses are the third leading cause of death amongst the noncommunicable diseases. The current COVID-19 pandemic, however, also highlights the impact of communicable respiratory syndromes. In the clinical routine, prolonged postanesthetic respiratory instability worsens the patient outcome. Even though early and continuous, long-term cardiorespiratory monitoring has been proposed or even proven to be beneficial in several situations, implementations thereof are sparse. We employed our recently presented, multimodal patch stethoscope to estimate Einthoven electrocardiogram (ECG) Lead I and II from a single 55 mm ECG lead. Using the stethoscope and ECG subsystems, the pre-ejection period (PEP) and left ventricular ejection time (LVET) were estimated. ECG-derived respiration techniques were used in conjunction with a novel, phonocardiogram-derived respiration approach to extract respiratory parameters. Medical-grade references were the SOMNOmedics SOMNO HDTM and Osypka ICON-CoreTM. In a study including 10 healthy subjects, we analyzed the performances in the supine, lateral, and prone position. Einthoven I and II estimations yielded correlations exceeding 0.97. LVET and PEP estimation errors were 10% and 21%, respectively. Respiratory rates were estimated with mean absolute errors below 1.2 bpm, and the respiratory signal yielded a correlation of 0.66. We conclude that the estimation of ECG, PEP, LVET, and respiratory parameters is feasible using a wearable, multimodal acquisition device and encourage further research in multimodal signal fusion for respiratory signal estimation.DFG, 414044773, Open Access Publizieren 2019 - 2020 / Technische Universität Berli

In-ear photoplethysmography for central pulse waveform analysis in non-invasive hemodynamic monitoring

In recent years, the analysis of the photoplethys-mographic (PPG) pulse waveforms has attracted much research focus. However, the considered signals are primarily recorded at the fingertips, which suffer from reduced peripheral perfusion in situations like hypovolemia or sepsis, rendering waveform analysis infeasible. The ear canal is not affected by cardiovascular centralization and could thus prove to be an ideal alternate measurement site for pulse waveform analysis. Therefore, we developed a novel system that allows for highly accurate photoplethysmographic measurements in the ear canal. We conducted a measurement study in order to assess the signal-to-noise ratio of our developed system Hereby, we achieved a mean SNR of 40.65 dB. Hence, we could show that our system allows for highly accurate PPG recordings in the ear canal facilitating sophisticated pulse waveform analysis. Furthermore, we demonstrated that the pulse decomposition analysis is also applicable to in-ear PPG recordings

Suspect identification based on descriptive facial attributes

We present a method for using human describable face attributes to perform face identification in criminal inves-tigations. To enable this approach, a set of 46 facial at-tributes were carefully defined with the goal of capturing all describable and persistent facial features. Using crowd sourced labor, a large corpus of face images were manually annotated with the proposed attributes. In turn, we train an automated attribute extraction algorithm to encode target repositories with the attribute information. Attribute extrac-tion is performed using localized face components to im-prove the extraction accuracy. Experiments are conducted to compare the use of attribute feature information, derived from crowd workers, to face sketch information, drawn by expert artists. In addition to removing the dependence on expert artists, the proposed method complements sketch-based face recognition by allowing investigators to imme-diately search face repositories without the time delay that is incurred due to sketch generation. 1

LemurFaceID: a face recognition system to facilitate individual identification of lemurs

Background: Long-term research of known individuals is critical for understanding the demographic and evolutionary processes that influence natural populations. Current methods for individual identification of many animals include capture and tagging techniques and/or researcher knowledge of natural variation in individual phenotypes. These methods can be costly, time-consuming, and may be impractical for larger-scale, populationlevel studies. Accordingly, for many animal lineages, long-term research projects are often limited to only a few taxa. Lemurs, a mammalian lineage endemic to Madagascar, are no exception. Long-term data needed to address evolutionary questions are lacking for many species. This is, at least in part, due to difficulties collecting consistent data on known individuals over long periods of time. Here, we present a new method for individual identification of lemurs (LemurFaceID). LemurFaceID is a computer-assisted facial recognition system that can be used to identify individual lemurs based on photographs. Results: LemurFaceID was developed using patch-wise Multiscale Local Binary Pattern features and modified facial image normalization techniques to reduce the effects of facial hair and variation in ambient lighting on identification. We trained and tested our system using images from wild red-bellied lemurs (Eulemur rubriventer) collected in Ranomafana National Park, Madagascar. Across 100 trials, with different partitions of training and test sets, we demonstrate that the LemurFaceID can achieve 98.7% ± 1.81% accuracy (using 2-query image fusion) in correctly identifying individual lemurs. Conclusions: Our results suggest that human facial recognition techniques can be modified for identification of individual lemurs based on variation in facial patterns. LemurFaceID was able to identify individual lemurs based on photographs of wild individuals with a relatively high degree of accuracy. This technology would remove many limitations of traditional methods for individual identification. Once optimized, our system can facilitate long-term research of known individuals by providing a rapid, cost-effective, and accurate method for individual identification

Detection of a stroke volume decrease by machine-learning algorithms based on thoracic bioimpedance in experimental hypovolaemia

Compensated shock and hypovolaemia are frequent conditions that remain clinically undetected and can quickly cause deterioration of perioperative and critically ill patients. Automated, accurate and non-invasive detection methods are needed to avoid such critical situations. In this experimental study, we aimed to create a prediction model for stroke volume index (SVI) decrease based on electrical cardiometry (EC) measurements. Transthoracic echo served as reference for SVI assessment (SVI-TTE). In 30 healthy male volunteers, central hypovolaemia was simulated using a lower body negative pressure (LBNP) chamber. A machine-learning algorithm based on variables of EC was designed. During LBNP, SVI-TTE declined consecutively, whereas the vital signs (arterial pressures and heart rate) remained within normal ranges. Compared to heart rate (AUC: 0.83 (95% CI: 0.73–0.87)) and systolic arterial pressure (AUC: 0.82 (95% CI: 0.74–0.85)), a model integrating EC variables (AUC: 0.91 (0.83–0.94)) showed a superior ability to predict a decrease in SVI-TTE ≥ 20% (p = 0.013 compared to heart rate, and p = 0.002 compared to systolic blood pressure). Simulated central hypovolaemia was related to a substantial decline in SVI-TTE but only minor changes in vital signs. A model of EC variables based on machine-learning algorithms showed high predictive power to detect a relevant decrease in SVI and may provide an automated, non-invasive method to indicate hypovolaemia and compensated shock

The detection and prediction of surgical site infections using multi-modal sensors and machine learning: Results in an animal model

IntroductionSurgical Site Infection (SSI) is a common healthcare-associated infection that imposes a considerable clinical and economic burden on healthcare systems. Advances in wearable sensors and digital technologies have unlocked the potential for the early detection and diagnosis of SSI, which can help reduce this healthcare burden and lower SSI-associated mortality rates.MethodsIn this study, we evaluated the ability of a multi-modal bio-signal system to predict current and developing superficial incisional infection in a porcine model infected with Methicillin Susceptible Staphylococcus Aureus (MSSA) using a bagged, stacked, and balanced ensemble logistic regression machine learning model.ResultsResults demonstrated that the expression levels of individual biomarkers (i.e., peri-wound tissue oxygen saturation, temperature, and bioimpedance) differed between non-infected and infected wounds across the study period, with cross-correlation analysis indicating that a change in bio-signal expression occurred 24 to 31 hours before this change was reflected by clinical wound scoring methods employed by trained veterinarians. Moreover, the multi-modal ensemble model indicated acceptable discriminability to detect the presence of a current superficial incisional SSI (AUC = 0.77), to predict an SSI 24 hours in advance of veterinarian-based SSI diagnosis (AUC = 0.80), and to predict an SSI 48 hours in advance of veterinarian-based SSI diagnosis (AUC = 0.74).DiscussionIn sum, the results of the current study indicate that non-invasive multi-modal sensor and signal analysis systems have the potential to detect and predict superficial incisional SSIs in porcine subjects under experimental conditions