Instant Basketball Defensive Trajectory Generation

Tactic learning in virtual reality (VR) has been proven to be effective for basketball training. Endowed with the ability of generating virtual defenders in real time according to the movement of virtual offenders controlled by the user, a VR basketball training system can bring more immersive and realistic experiences for the trainee. In this article, an autoregressive generative model for instantly producing basketball defensive trajectory is introduced. We further focus on the issue of preserving the diversity of the generated trajectories. A differentiable sampling mechanism is adopted to learn the continuous Gaussian distribution of player position. Moreover, several heuristic loss functions based on the domain knowledge of basketball are designed to make the generated trajectories assemble real situations in basketball games. We compare the proposed method with the state-of-the-art works in terms of both objective and subjective manners. The objective manner compares the average position, velocity, and acceleration of the generated defensive trajectories with the real ones to evaluate the fidelity of the results. In addition, more high-level aspects such as the empty space for offender and the defensive pressure of the generated trajectory are also considered in the objective evaluation. As for the subjective manner, visual comparison questionnaires on the proposed and other methods are thoroughly conducted. The experimental results show that the proposed method can achieve better performance than previous basketball defensive trajectory generation works in terms of different evaluation metrics.

Learning from EMG: semi-automated grading of facial nerve function

The current grading of facial nerve function is based on subjective impression with the established assessment scale of House and Brackmann (HB). Especially for research a more objective method is needed to lower the interobserver variability to a minimum. We developed a semi-automated grading system based on (facial) surface EMG-data measuring the facial nerve function of 28 patients with vestibular schwannoma surgery. The sEMG was recorded preoperatively, postoperatively and after 3–12 months. In addition, the HB grade was determined. After manual selection and preprocessing, the data were subjected to machine learning classificators (Logistic regression, SVM and KNN). Lateralization indices were calculated and multivariant machine learning analysis was performed according to three scenarios [differentiation of normal (1) and slight (2) vs. impaired facial nerve function and classification of HB 1-3 (3)]. The calculated AUC for each scenario showed overall good differentiation capability with a median AUC of 0.72 for scenario 1, 0.91 for scenario 2 and multiclass AUC of 0.74 for scenario 3. This study approach using sEMG and machine learning shows feasibility regarding facial nerve grading in perioperative VS-surgery setting. sEMG may be a viable alternative to House Brackmann regarding objective evaluation of facial function especially for research purposes.

Fractal dimension analogous scale-invariant derivative of Hirsch’s index

We propose a scale-invariant derivative of the h-index as “h-dimension”, which is analogous to the fractal dimension of the h-index for institutional performance analysis. The design of h-dimension comes from the self-similar characteristics of the citation structure. We applied this h-dimension to data of 134 Japanese national universities and research institutes, and found well-performing medium-sized research institutes, where we identified multiple organizations related to natural disasters. This result is reasonable considering that Japan is frequently hit by earthquakes, typhoons, volcanoes and other natural disasters. However, these characteristic institutes are screened by larger universities if we depend on the existing h-index. The scale-invariant property of the proposed method helps to understand the nature of academic activities, which must promote fair and objective evaluation of research activities to maximize intellectual, and eventually economic opportunity.

Emerging Advancement for Augmented Reality (AR) and Virtual Reality (VR) in Dentistry

The skill of visual reality has matured, and VR and AR are increasingly being used in educational and surgical settings. The development of virtual reality technologies allows users to mix medical knowledge, medical data, and graphical data. It can provide more precise information, allowing users to increase their safety and reduce their risk. Virtual reality (VR) or augmented reality (AR) simulators that provide direct feedback and objective evaluation could be a useful tool in dental education in the future. Not only has it been applied to education, but it has also been created in therapeutic therapy. The authors believe that in the future VR and AR training and teaching will be extended and used in every aspect of dentistry, enabling students to develop their abilities on their own. In comparison to augmented reality, virtual reality offers a far more immersive experience. It would establish a trusting relationship between patients and doctors based on the experience of the dentists and the use of different hardware and software.

Inferring microbiota functions from taxonomic genes: a review

Deciphering microbiota functions is crucial to predict ecosystem sustainability in response to global change. High-throughput sequencing at the individual or community level has revolutionized our understanding of microbial ecology, leading to the big data era and improving our ability to link microbial diversity with microbial functions. Recent advances in bioinformatics have been key for developing functional prediction tools based on DNA metabarcoding data and using taxonomic gene information. This cheaper approach in every aspect serves as an alternative to shotgun sequencing. Although these tools are increasingly used by ecologists, an objective evaluation of their modularity, portability, and robustness is lacking. Here, we reviewed 100 scientific papers on functional inference and ecological trait assignment to rank the advantages, specificities, and drawbacks of these tools, using a scientific benchmarking. To date, inference tools have been mainly devoted to bacterial functions, and ecological trait assignment tools, to fungal functions. A major limitation is the lack of reference genomes—compared with the human microbiota—especially for complex ecosystems such as soils. Finally, we explore applied research prospects. These tools are promising and already provide relevant information on ecosystem functioning, but standardized indicators and corresponding repositories are still lacking that would enable them to be used for operational diagnosis.

Can Tourism Development Make Cities More Livable? Investigating 40 Cities in China

The field of rapid urbanization has recently paid more attention to the relationship between tourism development and liveable city construction. Previous studies have mainly focused on the experiences of tourists in tourist cities and seldom paid attention to the perceptions of local residents. Based on survey data of nearly 10,000 permanent residents in 40 key tourist cities in China, this study uses a multilevel model to quantitatively analyse the natural environment characteristics, sociocultural environment characteristics and comprehensive attraction of tourism in different tourist cities to explore their impact on urban liveability satisfaction. Results show that the developed tourist cities do not exactly correspond to the cities with a high liveability evaluation. The objective evaluation of both the natural environment and the sociocultural environment has an important influence on the liveability of cities, but the influence of the natural environment is stronger than that of the sociocultural environment. An intermediary effect exists in the subjective evaluation of the natural environment and environments for liveability perception. Simultaneously, residents’ liveability satisfaction varies according to their age, education level, annual household income and other social and economic conditions. These findings provide insights for developing countries to further improve residents’ living quality and urban construction under the condition of the rapid development of tourism.

DCT Coefficients Weighting (DCTCW)-Based Gray Wolf Optimization (GWO) for Brightness Preserving Image Contrast Enhancement

Image contrast enhancement (CE) is a frequent image enhancement requirement in diverse applications. Histogram equalization (HE), in its conventional and different further improved ways, is a popular technique to enhance the image contrast. The conventional as well as many of the later versions of HE algorithms often cause loss of original image characteristics particularly brightness distribution of original image that results artificial appearance and feature loss in the enhanced image. Discrete Cosine Transform (DCT) coefficient mapping is one of the recent methods to minimize such problems while enhancing the image contrast. Tuning of DCT parameters plays a crucial role towards avoiding the saturations of pixel values. Optimization can be a possible solution to address this problem and generate contrast enhanced image preserving the desired original image characteristics. Biological behavior-inspired optimization techniques have shown remarkable betterment over conventional optimization techniques in different complex engineering problems. Gray wolf optimization (GWO) is a comparatively new algorithm in this domain that has shown promising potential. The objective function has been formulated using different parameters to retain original image characteristics. The objective evaluation against CEF, PCQI, FSIM, BRISQUE and NIQE with test images from three standard databases, namely, SIPI, TID and CSIQ shows that the presented method can result in values up to 1.4, 1.4, 0.94, 19 and 4.18, respectively, for the stated metrics which are competitive to the reported conventional and improved techniques. This paper can be considered a first-time application of GWO towards DCT-based image CE.

Evaluation of anxiolytic and anti-depressant activity of Neolamarckia cadamba in mice

Objective: Evaluation of anxiolytic and anti-depressant activity of Neolamarckia cadamba in mice. Material & Method: The aqueous and methanolic extract of “Neolamarckia cadamba” and chose low medium and high doses for therapy. The behavioral consequences of an oral acute or subacute (10 days) treatment. Neolamarckia cadamba (250 and 500 mg/kg, p.o) aqueous and methanolic stem bark extract assessed in male and female Swiss mice (EPM). Diazepam (1 mg/kg) will also be evaluated. Anti-anxiety drug testing in the lab. Results: Neolamarckia cadamba, acute oral toxicity was detected with different extracts (ENC & AQNC) having dose (5, 50, 300, 1000 mg/kg ) via the oral route, shows no change in behavioral responses and observation shows no acute oral toxicity. Hence depending upon it, Dose was selected 250 mg/kg & 500 mg/kg for our experimental work. Conclusion: Neolamarckia cadamba has both anxiolytic and antidepressant properties, which likely operate through BZD receptors, selective serotonin reuptake inhibitors. The antidepressant and anxiolytic properties of Neolamarckia cadamba ethanolic and aqueous extracts were investigated in Swiss albino mice at doses of 250 and 500 mg/kg, respectively. Both extracts (ANC & ENC) showed strong antidepressant and anxiolytic efficacy using TST and EPM parameters.

Electrophysiology and Auditory Training

Electrophysiology is an objective evaluation method that allows investigating the responses of the central auditory nervous system arising from the capture of neuronal responses through surface electrodes. In addition to the possibility of investigating and diagnosing different pathologies, electrophysiology proves to be an effective and effective instrument in monitoring auditory intervention programs. Auditory rehabilitation programs is based on the premise of neuroplasticity that derives from a capacity for neuronal change due to intense sound stimulation, specific and directed to the patient’s needs. Throughout this chapter, current studies that correlate electrophysiology with auditory training programs in different clinical populations will be presented, such as: hearing in typically developed individuals, hearing and school difficulties, hearing and CAPD, hearing and otitis media, hearing and hearing loss, and hearing and voice. Electrophysiological tests are important objective measures in predicting the gains to be expected from auditory training programs.