Imunokromatografsko testiranje lateralnog toka (LFIA) čitača trake temeljeno na rasporedu i 8051 IP jezgri

Lateral flow immunochromatographic assay (LFIA) testing is essential for accurate detection and diagnoses of diseases and physical conditions. However, the existing LFIA strip reader equipped with high cost of hardware confines its simplicity and portability. Therefore, this study develops a simple, low cost LFIA strip reader comprising 4 major modules --- mechanical, optical, processing and control modules. The mechanical module pulls in and out the test strip automatically to be read by the optical module and the data processing module provides the test results by analyzing the data sent by the optical module. All the individual modules are controlled by a control module. To reduce the hardware budget and control complexity, a time-triggered cooperative (TTC) scheduler implemented on an 8051 IP core was chosen as control system. In addition, special, high sensitivity C- reactive protein (CRP) strips with 10 different concentrations were tested to evaluate the performance of the system. Further, a commercial ESEQuant lateral flow reader (QIAGEN, Germany) was tested as a comparative study. The test results show that the proposed reader was stable with a coefficient of variation (CV) factor within 3%. To test the qualitative performance of the system, each of the CRP concentration were examined for 10 times, which indicates that the system has a large dynamic detection range and good detection linearity (^2 = 0.998). In short, the proposed LFIA strip reader has high potential relative to existing readers, especially in simplicity and cost.Imunokromatografsko testiranje lateralnog toka (LFIA) nužno je za preciznu detekciju i dijagnozu oboljenja te psihičkih stanja. Međutim, postojeći LFIA opremljeni s hardverom visoke cijene limitiraju jednostavnost i prenosivost. Ovo istraživanje razvija jednostavni, niske cijene, čitač traka koji se sastoji od 4 glavna dijela - mehanički, optički, procesni i upravljački. Mehanički modul povlači testnu traku automatski kako bi optički modul mogao čitati. Procesni modul analizira podatke dobivene s optičkog čitača. Svaki modula upravlja se upravljačkim modulom. Vremensko ovisno kooperativni raspored implementiran je na 8051 IP jezgri kako bi se smanjili računski zahtjevi. Dodatno, visoko osjetljiva CRP traka s deset različitih koncentracija korištena je u svrhe evaluacije sustava. Rezultati su uspoređeni s komercijalnim čitačem lateralnog toka ESEQuant (QIAGEN, Njemačka). Rezultati pokazuju da je predložena metoda stabilna s koeficijentom varijacije unutar 3%. Kako bi se kvalitativno testirao sustav, svaka od CRP koncentracija testirana je deset puta, što ukazuje da sustav veliki dinamički raspon detekcije te dobru linearnost detekcije (R^2 = 0.998). Predloženi LFIA čitač traka ima dosta potencijala u usporedbi s postoječim čitačima, posebno u smislu jednostavnosti i cijene

An Assay for Systematically Quantifying the Vestibulo-Ocular Reflex to Assess Vestibular Function in Zebrafish Larvae

Zebrafish (Danio rerio) larvae are widely used to study otic functions because they possess all five typical vertebrate senses including hearing and balance. Powerful genetic tools and the transparent body of the embryo and larva also make zebrafish a unique vertebrate model to study otic development. Due to its small larval size and moisture requirement during experiments, accurately acquiring the vestibulo-ocular reflex (VOR) of zebrafish larva is challenging. In this report, a new VOR testing device has been developed for quantifying linear VOR (LVOR) in zebrafish larva, evoked by the head motion about the earth horizontal axis. The system has a newly designed larva-shaped chamber, by which live fish can be steadily held without anesthesia, and the system is more compact and easier to use than its predecessors. To demonstrate the efficacy of the system, the LVORs in wild-type (WT), dlx3b and dlx4b morphant zebrafish larvae were measured and the results showed that LVOR amplitudes were consistent with the morphological changes of otoliths induced by morpholino oligonucleotides (MO). Our study represents an important advance to obtain VOR and predict the vestibular conditions in zebrafish

Evolutionary computing and fuzzy logic applied to generation scheduling in systems with renewables

Dissertação apresentada para obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores (Área de Energia) na Faculdade de Engenharia da Universidade do Porto, sob a orientação do Prof. Dr. Vladimiro Henrique B. P. de Miranda e do Prof. Hang Ying-duo da Faculdade de Ciência e Tecnologia da Universidade de Maca

A Unified Knowledge Extraction Method Based on BERT and Handshaking Tagging Scheme

In the actual knowledge extraction system, different applications have different entity classes and relationship schema, so the generalization and migration ability of knowledge extraction are very important. By training a knowledge extraction model in the source domain and applying the model to an arbitrary target domain directly, open domain knowledge extraction technology becomes crucial to mitigate the generalization and migration ability issues. Traditional knowledge extraction models cannot be directly transferred to new domains and also cannot extract undefined relation types. In order to deal with the above issues, in this paper, we proposed an end-to-end Chinese open-domain knowledge extraction model, TPORE (Extract Open-domain Relations through Token Pair linking), which combined BERT with a handshaking tagging scheme. TPORE can alleviate the nested entities and nested relations issues. Additionally, a new loss function that conducts a pairwise comparison of target category score and non-target category score to automatically balance the weight was adopted, and the experiment results indicate that the loss function can bring speed and performance improvements. The extensive experiments demonstrate that the proposed method can significantly surpass strong baselines. Specifically, our approach can achieve new state-of-the-art Chinese open Relation Extraction (ORE) benchmarks (COER and SAOKE). In the COER dataset, F1 increased from 66.36% to 79.63%, and in the SpanSAOKE dataset, F1 increased from 46.0% to 54.91%. In the medical domain, our method can obtain close performance compared with the SOTA method in the CMeIE and CMeEE datasets

An Exploratory Study of Intensive Neurofeedback Training for Schizophrenia

Schizophrenia is a chronic and devastating brain disorder with ongoing cognitive, behavioral, and emotional deteriorated functions. Neurofeedback training, which enables the individuals to regulate their brain activity using a real-time feedback loop, is increasingly investigated as a potential alternative intervention for schizophrenia. This study aimed to explore the effect of short but intensive neurofeedback training for schizophrenic patients with difficulty for long-time training. A middle-aged woman with chronic schizophrenia completed the intensive training of alpha/beta2 (20–30 Hz) in four consecutive days with a total training duration of 13.5 hours. The results showed that her alpha/beta2 increased over sessions, and her behavior performance including short-term memory, mood, and speech pattern was improved at the end of neurofeedback training. Importantly, a 22-month follow-up found a dramatic improvement in both positive and negative symptoms. These positive outcomes suggest that such intensive neurofeedback training may provide new insight into the treatment of schizophrenia and thus deserves further study to fully examine its scope

SpikoPoniC: A Low-Cost Spiking Neuromorphic Computer for Smart Aquaponics

Aquaponics is an emerging area of agricultural sciences that combines aquaculture and hydroponics in a symbiotic way to enhance crop production. A stable smart aquaponic system requires estimating the fish size in real time. Though deep learning has shown promise in the context of smart aquaponics, most smart systems are extremely slow and costly and cannot be deployed on a large scale. Therefore, we design and present a novel neuromorphic computer that uses spiking neural networks (SNNs) for estimating not only the length but also the weight of the fish. To train the SNN, we present a novel hybrid scheme in which some of the neural layers are trained using direct SNN backpropagation, while others are trained using standard backpropagation. By doing this, a blend of high hardware efficiency and accuracy can be achieved. The proposed computer SpikoPoniC can classify more than 84 million fish samples in a second, achieving a speedup of at least 3369× over traditional general-purpose computers. The SpikoPoniC consumes less than 1100 slice registers on Virtex 6 and is much cheaper than most SNN-based hardware systems. To the best of our knowledge, this is the first SNN-based neuromorphic system that performs smart real-time aquaponic monitoring

A Novel Field-Circuit FEM Modeling and Channel Gain Estimation for Galvanic Coupling Real IBC Measurements

Existing research on human channel modeling of galvanic coupling intra-body communication (IBC) is primarily focused on the human body itself. Although galvanic coupling IBC is less disturbed by external influences during signal transmission, there are inevitable factors in real measurement scenarios such as the parasitic impedance of electrodes, impedance matching of the transceiver, etc. which might lead to deviations between the human model and the in vivo measurements. This paper proposes a field-circuit finite element method (FEM) model of galvanic coupling IBC in a real measurement environment to estimate the human channel gain. First an anisotropic concentric cylinder model of the electric field intra-body communication for human limbs was developed based on the galvanic method. Then the electric field model was combined with several impedance elements, which were equivalent in terms of parasitic impedance of the electrodes, input and output impedance of the transceiver, establishing a field-circuit FEM model. The results indicated that a circuit module equivalent to external factors can be added to the field-circuit model, which makes this model more complete, and the estimations based on the proposed field-circuit are in better agreement with the corresponding measurement results