Neural Representation of Vocalizations in Noise in the Primary Auditory Cortex of Marmoset Monkeys

Robust auditory perception plays a pivotal function in processing behaviorally relevant sounds, particularly when there are auditory distractions from the environment. The neuronal coding enabling this ability, however, is still not well understood. In this study we recorded single-unit activity from the primary auditory cortex of alert common marmoset monkeys (Callithrix jacchus) while delivering conspecific vocalizations degraded by two different background noises: broadband white noise (WGN) and vocalization babble (Babble). Noise effects on single-unit neural representation of target vocalizations were quantified by measuring the response similarity elicited by natural vocalizations as a function of signal-to-noise ratio (SNR). Four consistent response classes (robust, balanced, insensitive, and brittle) were found under both noise conditions, with an average of about two-thirds of the neurons changing their response class when encountering different noises. These results indicate that the distortion induced by one particular masking background in single-unit responses is not necessarily predictable from that induced by another, which further suggests the low likelihood of a unique group of noise-invariant neurons across different background conditions in the primary auditory cortex. In addition, for a relatively large fraction of neurons, strong synchronized responses can be elicited by white noise alone, countering the conventional wisdom that white noise elicits relatively few temporally aligned spikes in higher auditory regions. The variable single-unit responses yet consistent population responses imply that the primate primary auditory cortex performs scene analysis predominately at the population level. Next, by pooling all single units together, pseudo-population analysis was implemented to gain more insight on how individual neurons work together to encode and discriminate vocalizations at various intensities and SNR levels. Population response variability with respect to time was found to synchronize well with the stimulus-driven firing rate of vocalizations at multiple intensities in a negative way. A much weaker trend was observed for vocalizations in noise. By applying dimensionality reduction techniques to the pooled single neuron responses, we were able to visualize the dynamics of neural ensemble responses to vocalizations in noise as trajectories in low-dimensional space. The resulting trajectories showed a clear separation between neural responses to vocalizations and WGN, while trajectories of neural responses to vocalization and Babble were much closer to each other together. Discrimination of neural populations evaluated by neural response classifiers revealed that a finer optimal temporal resolution and longer time scale of temporal dynamics were needed for vocalizations in noise than vocalizations at multiple different intensities. Last, among the whole population, a subpopulation of neurons yielded optimal discrimination performance. Together, for different background noises, the results in this dissertation provide evidence for heterogeneous responses on the individual neuron level, and for consistent response properties on the population level

The accuracy of three-dimensional rapid prototyped surgical template guided anterior segmental osteotomy

Surgical guiding templates provided a reliable way to transfer the simulation to the actual operation. However, there was no template designed for anterior segmental osteotomy so far. The study aimed to introduce and evaluate a set of 3D rapid prototyping surgical templates used in anterior segmental osteotomy. From August 2015 to August 2017, 17 patients with bimaxillary protrusions were recruited and occlusal-based multi-sectional templates were applied in the surgeries. The cephalometric analysis and 3D superimposition were performed to evaluate the differences between the simulations and actual post-operative outcomes. The patients were followed-up for 12 months to evaluate the incidence rate of complications and relapse. Bimaxillary protrusion was corrected in all patients with no complication. In radiographic evaluations, there was no statistically significant difference between the actual operations and the computer-aided 3D simulations (p >0.05, the mean linear and angular differences were less than 1.32mm and 1.72° consequently, and 3D superimposition difference was less than 1.4mm). The Pearson intraclass correlation coefficient reliabilities were high (0.897), and the correlations were highly significant (P< 0.001). The 3D printed surgical template designed in this study can safely and accurately transfer the computer-aided 3D simulation into real practice

Unraveling the microbial puzzle: exploring the intricate role of gut microbiota in endometriosis pathogenesis

Endometriosis (EMs) is a prevalent gynecological disorder characterized by the growth of uterine tissue outside the uterine cavity, causing debilitating symptoms and infertility. Despite its prevalence, the exact mechanisms behind EMs development remain incompletely understood. This article presents a comprehensive overview of the relationship between gut microbiota imbalance and EMs pathogenesis. Recent research indicates that gut microbiota plays a pivotal role in various aspects of EMs, including immune regulation, generation of inflammatory factors, angiopoietin release, hormonal regulation, and endotoxin production. Dysbiosis of gut microbiota can disrupt immune responses, leading to inflammation and impaired immune clearance of endometrial fragments, resulting in the development of endometriotic lesions. The dysregulated microbiota can contribute to the release of lipopolysaccharide (LPS), triggering chronic inflammation and promoting ectopic endometrial adhesion, invasion, and angiogenesis. Furthermore, gut microbiota involvement in estrogen metabolism affects estrogen levels, which are directly related to EMs development. The review also highlights the potential of gut microbiota as a diagnostic tool and therapeutic target for EMs. Interventions such as fecal microbiota transplantation (FMT) and the use of gut microbiota preparations have demonstrated promising effects in reducing EMs symptoms. Despite the progress made, further research is needed to unravel the intricate interactions between gut microbiota and EMs, paving the way for more effective prevention and treatment strategies for this challenging condition

Barrel Sanitation &amp; Solid Phase Extraction of Phenolic Compounds in Columns

Because of laboratory constraints posed by the pandemic, two projects are included as part of this thesis, a theoretical prediction of barrel sanitization and an experimental exploration of phenolic extraction in columns.Oak barrels are often used to give wine, beer, and distilled beverages flavors and colors. However, microorganisms can penetrate into the wood, making cleaning and sterilization difficult. This can lead to undesired microbial growth in the contents of the barrel during subsequent use. Information on heat penetration into barrel staves during steam treatment and associated thermal inactivation rates is scarce. Therefore, we incorporated heat transfer and Arrhenius-type death kinetics to build a mathematical model to predict the killing rate of the microorganisms when steam sterilizing a wooden barrel. First, we use this model to predict temperature profiles in barrel staves as a function of distance from the steamed surface and time of steaming. Next, we evaluated the thermal inactivation of microorganisms at 0.8 cm into the stave (the maximum wine penetration depth into a stave) to calculate the time needed to achieve 5-log reduction in live cells. Using this approach, we found that the required sterilization times for Brettanomyces bruxellensis, Saccharomyces cerevisiae, and Leuconostoc mesenteroides are 9 minutes, 12 minutes, and 200 minutes, respectively. This result is useful for winemakers to determine how long they desire to steam a barrel to prevent growth and contamination of key microbes in their wine. Phenolic extraction is essential for red winemaking. Fermentation along with phenolic extraction usually takes 7 to 14 days, although the tannin extraction can continue for weeks until an equilibrium is reached. Yet process intensification would allow winery equipment to be used multiple times during harvest, thus decreasing capital investment. While previous work showed the potential to speed up the conversion of sugar to alcohol considerably, this methodology will only be truly useful for red winemaking if phenolic extraction can be completed more rapidly and with more control. In this work, we performed phenolic extraction from grape solids in a column setup and let juice or wine flow through the column to model a continuous extraction. The effect of four different factors was tested: column temperature, liquid ethanol concentration, flow rate through the column, and column diameter using a design of experiments approach. We found that liquid flow rate is the most significant factor, and the temperature and ethanol concentration had minor effects but not statistically significant. With all optimized factors, we were able to reach the same concentration as the bucket control for the final extraction in 86 hours on the bench scale compared to 144 hours for the control process. Both the pigment concentration and tannin concentration were similar. This work shows the potential to achieve process intensification and more control of the phenolic values in the finished wine

Model Friele’a dla wielobarwnej przędzy mieszanej uzyskanej przędzeniem rotorowym

Multi-channel rotor spinning equipment can produce multi-colour mixed yarn by changing the feed speeds of three primary coloured slivers separately. The method realises the mixing of colour fibres during the spinning process, and has the characteristics of high production flexibility, simplicity and quickness. The colour mixing effect and colour blending ratio prediction are important conditions for industrial production. In this paper, two-component and three-component samples were spun with rovings of red, yellow and blue with different blending ratios. A colour model of the rotor spun multi-primary-colour-blended yarn was established based on Friele theory by determining the σ value, which is the model parameter determined by experiments. Two methods were employed to calculate the σ value to improve the accuracy of the model:1. under the condition of all wavelengths and 2. at various wavelengths. The results showed that the model parameters calculated at various wavelengths could better predict the colour of multi-channel rotor spun colour-blended yarn.Wielokanałowy wirnik może wytwarzać wielobarwną przędzę mieszaną zmieniając oddzielnie prędkości podawania trzech podstawowych kolorowych taśm. Zaprezentowana metoda pozwala na mieszanie włókien barwnych podczas procesu przędzenia i ma cechy wysokiej elastyczności produkcji, prostoty i szybkości. Efekt mieszania kolorów i przewidywania stosunku mieszania kolorów są ważnymi czynnikami w produkcji przemysłowej. W pracy wyprzędziono próbki dwuskładnikowe i trójskładnikowe z niedoprzędami koloru czerwonego, żółtego i niebieskiego o różnych stosunkach mieszania. W oparciu o teorię Friele’a ustalono model barwny przędzy wielobarwnej mieszanej określając wartość σ, która jest parametrem modelu określonym przez eksperymenty. W celu poprawy dokładności modelu do obliczenia wartości σ zastosowano dwie metody: 1) w warunkach wszystkich długości fal i 2) przy różnych długościach fal. Wyniki pokazały, że parametry modelu obliczone przy różnych długościach fali służą do lepszego przewidywania koloru przędzy

Locomotive Schedule Optimization for Da-qin Heavy Haul Railway

The main difference between locomotive schedule of heavy haul railways and that of regular rail transportation is the number of locomotives utilized for one train. One heavy-loaded train usually has more than one locomotive, but a regular train only has one. This paper develops an optimization model for the multilocomotive scheduling problem (MLSP) through analyzing the current locomotive schedule of Da-qin Railway. The objective function of our paper is to minimize the total number of utilized locomotives. The MLSP is nondeterministic polynomial (NP) hard. Therefore, we convert the multilocomotive traction problem into a single-locomotive traction problem. Then, the single-locomotive traction problem (SLTP) can be converted into an assignment problem. The Hungarian algorithm is applied to solve the model and obtain the optimal locomotive schedule. We use the variance of detention time of locomotives at stations to evaluate the stability of locomotive schedule. In order to evaluate the effectiveness of the proposed optimization model, case studies for 20 kt and 30 kt heavy-loaded combined trains on Da-qin Railway are both conducted. Compared to the current schedules, the optimal schedules from the proposed models can save 62 and 47 locomotives for 20 kt and 30 kt heavy-loaded combined trains, respectively. Therefore, the effectiveness of the proposed model and its solution algorithm are both valid

The Dual Role of Small Extracellular Vesicles in Joint Osteoarthritis: Their Global and Non-Coding Regulatory RNA Molecule-Based Pathogenic and Therapeutic Effects

OA is the most common joint disease that affects approximately 7% of the global population. Current treatment methods mainly relieve its symptoms with limited repairing effect on joint destructions, which ultimately contributes to the high morbidity rate of OA. Stem cell treatment is a potential regenerative medical therapy for joint repair in OA, but the uncertainty in differentiation direction and immunogenicity limits its clinical usage. Small extracellular vesicles (sEVs), the by-products secreted by stem cells, show similar efficacy levels but have safer regenerative repair effect without potential adverse outcomes, and have recently drawn attention from the broader research community. A series of research works and reviews have been performed in the last decade, providing references for the application of various exogenous therapeutic sEVs for treating OA. However, the clinical potential of target intervention involving endogenous pathogenic sEVs in the treatment of OA is still under-explored and under-discussed. In this review, and for the first time, we emphasize the dual role of sEVs in OA and explain the effects of sEVs on various joint tissues from both the pathogenic and therapeutic aspects. Our aim is to provide a reference for future research in the field

A Hybrid Taguchi Particle Swarm Optimization Algorithm for Reactive Power Optimization of Deep-Water Semi-Submersible Platforms with New Energy Sources

In order to realize the sustainable development of energy, the combination of new energy power generation technology and the traditional offshore platform has excellent research prospects. The access to new energy sources can provide a powerful supplement to the power grid of the offshore platform, but will also create new challenges for the planning, operation, and control of the power grid of the platform; hence, it is very important to optimize the reactive power of the offshore platform with new study, a mathematical model was first built for the reactive power optimization of offshore platform power systems with new energy sources, and the Taguchi method was then used to optimize the parameters and population of particle swarm optimization, thereby addressing a defect in particle swarm optimization, namely, that it can easily fall into local optimal solutions. Finally, the algorithm proposed in this paper was applied to solve the reactive power optimization problem of the offshore platform power system with new energy sources. The experimental results show that the proposed algorithm has stronger optimization ability, reduces the system active power loss to the greatest extent, and improves the voltage quality. These results provide theoretical support for the practical application and optimization of the deep-water semi-submersible production platform integrated with new energy sources