Horneoneal6005

Prior work on automated methods demonstrated that it is possible to recognize pain intensity from frontal faces in videos, while there is an assumption that humans are very adept at this task compared to machines. In this paper, we investigate whether such an assumption is correct by comparing the results achieved by two human observers with the results achieved by a Random Forest classifier (RFc) baseline model (called RFc-BL) and by three proposed automated models. The first proposed model is a Random Forest classifying descriptors of Action Unit (AU) time series; the second is a modified MobileNetV2 CNN classifying face images that combine three points in time; and the third is a custom deep network combining two CNN branches using the same input as for MobileNetV2 plus knowledge of the RFc. We conduct experiments with X-ITE phasic pain database, which comprises videotaped responses to heat and electrical pain stimuli, each of three intensities. Distinguishing these six stimulation types plus no stimulation was the main 7-class classification task for the human observers and automated approaches. Further, we conducted reduced 5-class and 3-class classification experiments, applied Multi-task learning, and a newly suggested sample weighting method. Experimental results show that the pain assessments of the human observers are significantly better than guessing and perform better than the automatic baseline approach (RFc-BL) by about 1%; however, the human performance is quite poor due to the challenge that pain that is ethically allowed to be induced in experimental studies often does not show up in facial reaction. We discovered that downweighting those samples during training improves the performance for all samples. The proposed RFc and two-CNNs models (using the proposed sample weighting) significantly outperformed the human observer by about 6% and 7%, respectively.In traditional oriental medicines, Commiphora myrrha and its resinous exudate (i.e., myrrh) are used as herbal remedies to treat various inflammatory and metabolic disorders. Until now, C. myrrha-derived herbal products are considered useful source for bioactive compounds to manage numerous human diseases. This study investigated the effects of water extract of C. myrrha resin (WCM) and its polysaccharide (WCM-PE) on modulatory effects of osteoclast differentiation and/or ovariectomized-induced bone loss. Oral administration of WCM (200 and 500 mg/kg/day for four weeks) notably decreased trabecular bone loss and lipid accumulation in the bone marrow cavity. WCM and WCM-PE dose-dependently inhibited receptor activator of nuclear factor-κB ligand (RANKL)-induced osteoclastogenesis and suppressed RANKL-mediated overexpression of c-Fos and nuclear factor of activated T cells, cytoplasmic 1, thereby downregulating osteoclast-specific gene (Atp6v0d2, DC-STAMP and cathepsin K) expression. Thus, our results suggest that WCM and WCM-PE are promising nutraceutical candidates for the management of osteoporosis in postmenopausal women.Parkinson's disease (PD) is a debilitating neurodegenerative disease, which progresses over time, causing pathological depigmentation of the substantia nigra (SN) in the midbrain due to loss of dopaminergic neurons. Emerging studies revealed the promising effects of some nutrient compounds in reducing the risk of PD. One such nutrient compound that possess neuroprotective effects and prevents neurodegeneration is tocotrienol (T3), a vitamin E family member. In the present study, a single dose intracisternal injection of 250 µg 6-hydroxydopamine (6-OHDA) was used to induce parkinsonism in male Sprague Dawley (SD) rats. Forty-eight hours post injection, the SD rats were orally supplemented with alpha (α)- and gamma (γ)-T3 for 28 days. The neuroprotective effects of α- and γ-T3 were evaluated using behavioural studies and immunohistochemistry (IHC). The findings from this study revealed that supplementation of α- and γ-T3 was able to ameliorate the motor deficits induced by 6-OHDA and improve the neuronal functions by reducing inflammation, reversing the neuronal degradation, and preventing further reduction of dopaminergic neurons in the SN and striatum (STR) fibre density.Polyphenols are naturally derived compounds that are increasingly being explored for their various health benefits. In fact, foods that are rich in polyphenols have become an attractive source of nutrition and a potential therapeutic strategy to alleviate the untoward effects of metabolic disorders. The last decade has seen a rapid increase in studies reporting on the bioactive properties of polyphenols against metabolic complications, especially in preclinical models. Various experimental models involving cell cultures exposed to lipid overload and rodents on high fat diet have been used to investigate the ameliorative effects of various polyphenols against metabolic anomalies. Here, we systematically searched and included literature reporting on the impact of polyphenols against metabolic function, particularly through the modulation of mitochondrial bioenergetics within the skeletal muscle. This is of interest since the skeletal muscle is rich in mitochondria and remains one of the main sites of energy homeostasis. Notably, increased substrate availability is consistent with impaired mitochondrial function and enhanced oxidative stress in preclinical models of metabolic disease. This explains the general interest in exploring the antioxidant properties of polyphenols and their ability to improve mitochondrial function. click here The current review aimed at understanding how these compounds modulate mitochondrial bioenergetics to improve metabolic function in preclinical models on metabolic disease.We report a Japanese 5-year-old boy with primary ciliary dyskinesia (PCD) which was diagnosed owing to Clostridium difficile (CD) infection caused by prolonged antibiotic exposure. He had intractable otitis media with effusion (OME) and had abdominal pain and diarrhea for 4 months after starting antibiotics administration. His stool contained CD toxin. After vancomycin treatment, his symptoms improved and his stools did not contain CD toxin. His past medical history included frequent pneumonia. We, therefore, performed electron microscopy of the biopsy specimen from his nasal mucosa and genetic testing, and he was diagnosed with PCD. PCD is a rare inherited genetic disease causing ciliary dysfunction, which is very difficult to diagnose because some children without PCD also develop the same symptoms. Therefore, children who have intractable OME, rhinosinusitis, frequent pneumonia, or bronchitis and are taking antibiotics for long periods of time should be checked for underlying diseases, such as PCD.The principal objective of this research is to conceive a mobile system based on electrical tomography for subsurface imaging and monitoring in order to enable simultaneous recording of electrical potentials of cardiac and pulmonary activity. For an exploration of excitation waveforms in electrical tomography, specialized hardware is required. As the main principle of tomography is the measurement of electrical perturbations on an unknown object, it is crucial to synchronize excitation and sensing processes in a very precise way for the purpose of acquiring meaningful data. To cope with this problem, an FPGA device is used, with an architecture that allows us to trigger excitation signals and to read sensed data simultaneously via independent processes that share the same clock. In this way, waveform reconfiguration on frequency and shape can be provided and studied. The system is connected to a standard microcontroller SoC with a simple API that allows for IoT capabilities for on-line operation and tracking, given that the design is targeted for in vivo medical monitoring. As a result of the research work, a measuring device was developed, the surface data analyzed and the image was reconstructed using the selected configuration.A new non-stationary (NS) geometry-based stochastic model (GBSM) is presented for developing and testing the communication systems of vehicle-to-vehicle (V2V) applications, which considers the three-dimensional (3D) scattering environments and allows 3D velocity as well. In this paper, the proposed GBSM for NS V2V channels allowed 3D velocity variations and was more suitable for actual V2V communications because it provided smoother transitions between the consecutive channel segments. The time-variant channel coefficient and the channel parameters, i.e., Doppler frequencies, path delay and power, angle of arrival (AoA), and angle of departure (AoD), were analyzed and derived. Likewise, the theoretical statistical properties as the probability density function (PDF), the auto-correlation function (ACF), and Doppler power spectral density (DPSD) were also analyzed and derived under the von Mises-Fisher (VMF) distribution. Finally, the theoretical and measured results were well coordinated alongside the implemented results, which confirmed the feasibility of the introduced model along with the theoretical expressions.The environmental pollution, pesticide resistance, and other associated problems caused by traditional chemical pesticides with limited modes of action make it urgent to seek alternative environmentally-friendly pesticides from natural products. Tung meal, the byproduct of the detoxified Vernicia fordii (Hemsl.) seed, has been commonly used as an agricultural fertilizer and as a pesticide. However, its active insecticidal extracts and ingredients remain elusive. In the present study, the contact toxicities of tung meal extracts against the agricultural and forest pests like O. formosanus and P. xylostella were examined. Our results showed that ethyl acetate and petroleum ether extracts showed the strongest toxicity against O. formosanus and P. xylostella, respectively. In order to further explore the chemical profiles of the ethyl acetate and petroleum ether extracts, UPLC-Q/TOF-MS and GC-MS analyses have been performed, and 20 and 29 compounds were identified from EA and PE extracts, respectively. The present study, for the first time, verified the noteworthy insecticidal activities on the aforementioned agricultural and forest pesticides and revealed the potential active parts and chemical composition, which are conducive to further exploiting the potential of tung meal as a natural plant-derived insecticide for biological control of agricultural and forest pests.AlGaN/GaN HEMT hydrogen gas sensors were optimized by AlGaN barrier thickness in the gate-source connected configuration demonstrated high response and robust stability up to 500 °C. First, we found that the hydrogen sensing performance of a conventional normally-on HEMT-based sensor was enhanced when zero voltage was applied on the gate in comparison with a floating-gate condition due to a reduced level of the base current. In the next step, to take advantage of the response increase by VGS = 0 V, a new type of sensor with a source-connected gate (SCG) was fabricated to utilize the normally-on operation of the GaN HEMT sensor as a two-terminal device. AlGaN barrier thickness was thinned by the dry-etching process to gain higher transconductance at a zero-gate bias with the reduction of the distance from the 2DEG channel to the AlGaN surface, thereby significantly improve the hydrogen response. The SCG GaN sensor with an ultra-thin AlGaN barrier (9 nm) exhibited responses of 85% and 20% at 200 and 500 °C, respectively, onto 4%-hydrogen gas, which demonstrates a promising ability for harsh environment applications.