Financial Analysis of a Grid-connected Photovoltaic System in South Florida

In this paper the performance and financial analysis of a grid-connected photovoltaic system installed at Florida Atlantic University (FAU) is evaluated. The power plant has the capacity of 14.8 kW and has been under operation since August 2014. This solar PV system is composed of two 7.4 kW sub-arrays, one fixed and one with single axis tracking. First, an overview of the system followed by local weather characteristics in Boca Raton, Florida is presented. In addition, monthly averaged daily solar radiation in Boca Raton as well as system AC are calculated utilizing the PVwatts simulation calculator. Inputs such as module and inverter specifications are applied to the System Advisor Model (SAM) to design and optimize the system. Finally, the estimated local load demand as well as simulation results are extracted and analyzed.Comment: 6 Pages, IEEE PVSC 2017 Conference, Washington D.

DP-ACT: Decentralized Privacy-Preserving Asymmetric Digital Contact Tracing

Digital contact tracing substantially improves the identification of high-risk contacts during pandemics. Despite several attempts to encourage people to use digital contact-tracing applications by developing and rolling out decentralized privacy-preserving protocols (broadcasting pseudo-random IDs over Bluetooth Low Energy-BLE), the adoption of digital contact tracing mobile applications has been limited, with privacy being one of the main concerns.In this paper, we propose a decentralized privacy-preserving contact tracing protocol, called DP-ACT, with both active and passive participants. Active participants broadcast BLE beacons with pseudo-random IDs, while passive participants model conservative users who do not broadcast BLE beacons but still listen to the broadcasted BLE beacons. We analyze the proposed protocol and discuss a set of interesting properties. The proposed protocol is evaluated using both a face-to-face individual interaction dataset and five real-world BLE datasets. Our simulation results demonstrate that the proposed DP-ACT protocol outperforms the state-of-the-art protocols in the presence of passive users

Lightweight Machine Learning for Seizure Detection on Wearable Devices

For patients with epilepsy, automatic epilepsy monitoring, i.e., the process of direct observation of the patient’s health status in real time, is crucial. Wearable systems provide the possibility of real-time epilepsy monitoring and alerting caregivers upon the occurrence of a seizure. In the context of the ICASSP 2023 Seizure Detection Challenge, we pro- pose a lightweight machine-learning framework for real-time epilepsy monitoring on wearable devices. We evaluate our proposed framework on the SeizeIT2 dataset from the wear- able SensorDot (SD) of Byteflies. The experimental results show that our proposed framework achieves a sensitivity of 73.6% and a specificity of 96.7% in seizure detection

Immunotherapy of Metastatic Mouse Breast Cancer by Adherent Splenocytes Pulsed With Extracts of Heated Tumor Cells and Lactobacillus Casei

Introduction: Flask-adherent Splenocytes (SACs) fulfill antigen-presenting cell requirementsof acquired immune responses. This study was done to evaluate the efficacy of newimmunotherapy against breast cancer made by SACs pulsed with the extract of heated 4T1cells and Lactobacillus casei, as a probiotic.Materials and Methods: Mammary carcinoma was induced by injection of 4T1 cell line inthe flank of female Balb/c mice. The first SACs therapy was started on day 11 after tumorinduction when all animals had developed a palpable tumor. SACs therapy was done twice ata 10-day interval.Results: Mice with mammary tumors received SACs pulsed with combined heated 4T1 cellsand L. casei determined a more desirable survival curve and a slower rate of tumor developmentcompared to the other groups. At least 20% of the group receiving combined immunotherapywere alive by day 58. Those mice receiving SACs pulsed with the Lysate of heated tumorcells died by day 45.The maximum survival of other mice was up to 38 days after tumorinduction. Moreover, SAC pulsed with combined agents significantly amplified the secretionof Interferon-γ (IFN-γ), and conversely reduced the secretion of Transforming growth factor-β(TGF-β) and Interleukin 4 (IL-4) in the splenocyte population compared to splenocytes fromother groups. Combined immunotherapy increased the expression of p53 and caspase 3 genesand reduced the exertion of BCL2 more than other immunotherapy protocols.Conclusion: Immunotherapy with SACs pulsed with heated 4T1 cells and L. casei promotesbeneficial outcomes in the mouse model of breast cancer

Hand Motion Detection in fNIRS Neuroimaging Data

As the number of people diagnosed with movement disorders is increasing, it becomes vital to design techniques that allow the better understanding of human brain in naturalistic settings. There are many brain imaging methods such as fMRI, SPECT, and MEG that provide the functional information of the brain. However, these techniques have some limitations including immobility, cost, and motion artifacts. One of the most emerging portable brain scanners available today is functional near-infrared spectroscopy (fNIRS). In this study, we have conducted fNIRS neuroimaging of seven healthy subjects while they were performing wrist tasks such as flipping their hand with the periods of rest (no movement). Different models of support vector machine is applied to these fNIRS neuroimaging data and the results show that we could classify the action and rest periods with the accuracy of over 80% for the fNIRS data of individual participants. Our results are promising and suggest that the presented classification method for fNIRS could further be applied to real-time applications such as brain computer interfacing (BCI), and into the future steps of this research to record brain activity from fNIRS and EEG, and fuse them with the body motion sensors to correlate the activities

Bivariate Autoregressive State-Space Modeling of Psychophysiological Time Series Data

Heart rate (HR) and electrodermal activity (EDA) are often used as physiological measures of psychological arousal in various neuropsychology experiments. In this exploratory study, we analyze HR and EDA data collected from four participants, each with a history of suicidal tendencies, during a cognitive task known as the Paced Auditory Serial Addition Test (PASAT). A central aim of this investigation is to guide future research by assessing heterogeneity in the population of individuals with suicidal tendencies. Using a state-space modeling approach to time series analysis, we evaluate the effect of an exogenous input, i.e., the stimulus presentation rate which was increased systematically during the experimental task. Participants differed in several parameters characterizing the way in which psychological arousal was experienced during the task. Increasing the stimulus presentation rate was associated with an increase in EDA in participants 2 and 4. The effect on HR was positive for participant 2 and negative for participants 3 and 4. We discuss future directions in light of the heterogeneity in the population indicated by these findings

Učinak različitih biljnih ekstrakata na aktivnost hidrolaze žučnih soli sojeva bakterije Lactobacillus izolirane iz probavnog sustava peradi

The bile salt hydrolysis (BSH) enzyme weakens fat metabolism through bile salt deconjugation and reduces poultry performance, in order to cope with the antibacterial properties of the bile. Therefore, reducing the activity of this enzyme through the use of feed additives is probably a promising alternative to antibiotics for improving poultry performance. Plant extracts have long been used as feed additives for promoting poultry growth. In the current experiment, five Lactobacillus strains including Lactobacillus animalis, Lactobacillus acidophillus, Lactobacillus gallinarum, Lactobacillus lactis, and Lactobacillus returi were obtained from the poultry hindgut and were used as the probiotic application. A plate test and two-step enzymatic reaction method were used for deconjugation activity determination of the Lactobacillus strains. Further, four plant extracts (i.e., the aerial parts of Rosemary (Rosmarinus officinalis), Roselle calyx (Hibiscus sabdariffa), Berberis vulgaris root, and Green tea) were examined in terms of BSH enzyme inhibitors using the cell-free extracts as the potential antibiotic alternative. Furthermore, the gallbladders of the broilers were freshly collected from the poultry slaughterhouses, and their contents were extracted. The results showed that all Lactobacillus strains could hydrolyze the taurocholate acid (TCA) and chicken bile salt mixture (CBSM) to unconjugated bile acid. Moreover, ethanolic extracts of B. vulgaris root and Green tea relatively reduced the activity of the BSH enzyme that could potentially be investigated as an appropriate alternative in poultry feed in vivo. In conclusion, all five Lactobacillus strains were resistant to bile salts (i.e. TCA and CBSM) by BSH activity, and the addition of Green tea and B. vulgaris root extracts to the bacterial medium demonstrated inhibitory effects against the BSH enzyme.Enzimi hidrolaze žučnih soli (BSH) oslabljuju metabolizam masti dekonjugacijom žučnih soli što dovodi do smanjenja proizvodnosti u peradi. Smanjenje aktivnosti ovog enzima, upotrebom dodataka prehrani, mogla bi biti obećavajuća alternativa za primjenu određenih antibiotika u peradarstvu. Biljni ekstrakti dugo se upotrebljavaju kao dodaci prehrani za poticanje rasta. U ovom je istraživanju pet sojeva bakterije Lactobacillus, uključujući Lactobacillus animalis, Lactobacillus acidophillus, Lactobacillus gallinarum, Lactobacillus lactis i Lactobacillus returi, dobiveno iz stražnjeg dijela crijeva peradi te upotrijebljeno kao probiotik. Test na ploči i enzimska reakcija u dva koraka primijenjene su za utvrđivanje aktivnosti dekonjugacije u sojeva Lactobacillus. Nadalje, četiri biljna ekstrakta - nadzemni dijelovi ružmarina (Rosmarinus officinalis), hibiskusa (Hibiscus sabdariffa), korijen obične žutike (Berberis vulgaris) i zeleni čaj - istraživana su s obzirom na inhibitore enzima BSH upotrebom izvanstaničnih ekstrakata kao moguća zamjena antibiotiku. Osim toga, nakon usmrćivanja, prikupljeni su svježi žučni mjehuri brojlera te je izvađen njihov sadržaj. Rezultati su pokazali da svi sojevi bakterije Lactobacillus mogu hidrolizirali tauroholatnu kiselinu i žučne soli pilića (CBSM) u nekonjugiranu žučnu kiselinu. Štoviše, ekstrakti etanola korijena B. vulgaris i zelenog čaja relativno su smanjili aktivnost BSH enzima što bi se moglo istražiti u hranidbi peradi in vivo. Zaključno, svih pet sojeva bakterije Lactobacillus bilo je otporno na žučne soli npr. tauroholičnu kiselinu (TCA) i (CBSM) putem BSH aktivnosti, a dodatak zelenog čaja i ekstrakta korijena B. vulgaris mediju s bakterijama pokazali su inhibitorne učinke protiv BSH enzima

EpilepsyNet: Interpretable Self-Supervised Seizure Detection for Low-Power Wearable Systems

Epilepsy is one of the most common neurological disorders that is characterized by recurrent and unpredictable seizures. Wearable systems can be used to detect the onset of a seizure and notify family members and emergency units for rescue. The majority of state-of-the-art studies in the epilepsy domain currently explore modern machine learning techniques, e.g., deep neural networks, to accurately detect epileptic seizures. However, training deep learning networks requires a large amount of data and computing resources, which is a major challenge for resource-constrained wearable systems. In this paper, we propose EpilepsyNet, the first interpretable self-supervised network tailored to resource-constrained devices without using any seizure data in its initial offline training. At runtime, however, once a seizure is detected, it can be incorporated into our self-supervised technique to improve seizure detection performance, without the need to retrain our learning model, hence incurring no energy overheads. Our self-supervised approach can reach a detection performance of 79.2%, which is on par with the state-of-the-art fully-supervised deep neural networks trained on seizure data. At the same time, our proposed approach can be deployed in resource-constrained wearable devices, reaching up to 1.3 days of battery life on a single charge

Emotional reactivity monitoring using electrodermal activity analysis in individuals with suicidal behaviors

Suicide, considered as one of the leading causes of death, has not been given enough attention in order to reduce it\u27s rate. The problem addressed in this paper is the analysis of the relation between an extra stimulus and physiological data\u27s responses. In order to record the physiological data set from multiple subjects over many weeks, we used an acoustic startle during a Paced Auditory Serial Addition Task (PASAT) test that spontaneously leads subjects to real emotional reactivity, without any deliberate laboratory setting. Crucially, we show that, by inducing anxiety during the test, changes appear in Electrodermal activity, Electrocardiogram, Heart Rate and Respiration Rate. A wide range of physiological features from various analysis domains, including modeling, time/frequency analysis, an algorithm and etc., is proposed in order to find the best emotional reactivity feature to correlate them with emotional states which can be considered as a suicide factor. More specifically, this paper is focused on the EDA data analysis. Experimental results highlight that all cited techniques perform well and we achieved a high resolution of tonic and phasic components which allow us to measure the latency, onsets and amplitudes of EDA responses to a stimulus. This paper follows the association of recommendations for advancement of health care instruments

Knowledge management in government organizations

A great need has been felt in recent years for using knowledge management that is hardly established in government organizations. Globalization in alterations and the induction of values such as contribution, citizen-orientedness and knowledge-oriented ness in modern theories of public administration and also issues such as government-shrinkage and exertion of instead of incumbency make it necessary for government sectors to take knowledge management in government organizations; there are three main subjects: 1-Is it possible to use management knowledge in government organizations?2-Can the existing knowledge management models be used? 3-What are the components and dimensions of knowledge management in government organizations? Finally, this article clarifies the possible restrictions on utilizing knowledge management in government organizations