Design Optimization of a Speed Reducer Using Deterministic Techniques

The optimal design problem of minimizing the total weight of a speed reducer under constraints is a generalized geometric programming problem. Since the metaheuristic approaches cannot guarantee to find the global optimum of a generalized geometric programming problem, this paper applies an efficient deterministic approach to globally solve speed reducer design problems. The original problem is converted by variable transformations and piecewise linearization techniques. The reformulated problem is a convex mixed-integer nonlinear programming problem solvable to reach an approximate global solution within an acceptable error. Experiment results from solving a practical speed reducer design problem indicate that this study obtains a better solution comparing with the other existing methods

Nonsurjective zero product preservers between matrices over an arbitrary field

In this paper, we give concrete descriptions of additive or linear disjointness preservers between matrix algebras over an arbitrary field $\mathbb{F}$ of different sizes. In particular, we show that a linear map $\Phi: M_n(\mathbb{F}) \rightarrow M_r(\mathbb{F})$ preserving zero products carries the form $$\Phi(A)= S\begin{pmatrix} R\otimes A & 0 \cr 0 & \Phi_0(A)\end{pmatrix} S^{-1},$$ for some invertible matrices $R$ in $M_k(\mathbb{F})$, $S$ in $M_r(\mathbb{F})$ and a zero product preserving linear map $\Phi_0: M_n(\mathbb{F}) \rightarrow M_{r-nk}(\mathbb{F})$ with range consisting of nilpotent matrices. Here, either $R$ or $\Phi_0$ can be vacuous. The structure of $\Phi_0$ could be quite arbitrary. We classify $\Phi_0$ with some additional assumption. When $\Phi(I_n)$ has a zero nilpotent part, especially when $\Phi(I_n)$ is diagonalizable, we have $\Phi_0(X)\Phi_0(Y) = 0$ for all $X, Y$ in $M_n(\mathbb{F})$, and we give more information about $\Phi_0$ in this case. Similar results for double zero product preservers and orthogonality preservers are obtained.Comment: 29 page

Deep convolutional neural network for rib fracture recognition on chest radiographs

IntroductionRib fractures are a prevalent injury among trauma patients, and accurate and timely diagnosis is crucial to mitigate associated risks. Unfortunately, missed rib fractures are common, leading to heightened morbidity and mortality rates. While more sensitive imaging modalities exist, their practicality is limited due to cost and radiation exposure. Point of care ultrasound offers an alternative but has drawbacks in terms of procedural time and operator expertise. Therefore, this study aims to explore the potential of deep convolutional neural networks (DCNNs) in identifying rib fractures on chest radiographs.MethodsWe assembled a comprehensive retrospective dataset of chest radiographs with formal image reports documenting rib fractures from a single medical center over the last five years. The DCNN models were trained using 2000 region-of-interest (ROI) slices for each category, which included fractured ribs, non-fractured ribs, and background regions. To optimize training of the deep learning models (DLMs), the images were segmented into pixel dimensions of 128 × 128.ResultsThe trained DCNN models demonstrated remarkable validation accuracies. Specifically, AlexNet achieved 92.6%, GoogLeNet achieved 92.2%, EfficientNetb3 achieved 92.3%, DenseNet201 achieved 92.4%, and MobileNetV2 achieved 91.2%.DiscussionBy integrating DCNN models capable of rib fracture recognition into clinical decision support systems, the incidence of missed rib fracture diagnoses can be significantly reduced, resulting in tangible decreases in morbidity and mortality rates among trauma patients. This innovative approach holds the potential to revolutionize the diagnosis and treatment of chest trauma, ultimately leading to improved clinical outcomes for individuals affected by these injuries. The utilization of DCNNs in rib fracture detection on chest radiographs addresses the limitations of other imaging modalities, offering a promising and practical solution to improve patient care and management

Invited; CMOS inverters and circuits based on oxide thin-film transistors

Thin-film transistors (TFTs) based on oxide semiconductors have the advantage of promising carrier mobilities and good switching characteristics, and they can be fabricated by low-temperature and scalable processes. Complementary metal-oxide-semiconductor (CMOS) technology employing oxide TFTs shows great potential in enabling flexible electronics with versatile functionalities and low-static power consumptions. Here flexible CMOS inverters comprising p-type SnO TFTs and n-type ZnO or IGZO TFTs integrated in three different configurations were implemented and compared, as shown in Fig. 1. First, the planar inverter comprising bottom-gated SnO and ZnO TFTs with a geometric aspect ratio, (W/L)p / (W/L)n, of 5 had a static voltage gain of ~ 10 V/V at a supplied voltage (VDD) of 10 V [1]. However, the gain decreased as the inverter was subjected to a mechanical tensile strain, which may be ascribed to the degradation of TFT mobilities. Please click Download on the upper right corner to see the full abstract

Genomic diversity of citrate fermentation in Klebsiella pneumoniae

<p>Abstract</p> <p>Background</p> <p>It has long been recognized that <it>Klebsiella pneumoniae </it>can grow anaerobically on citrate. Genes responsible for citrate fermentation of <it>K. pneumoniae </it>were known to be located in a 13-kb gene cluster on the chromosome. By whole genome comparison of the available <it>K. pneumoniae </it>sequences (MGH 78578, 342, and NTUH-K2044), however, we discovered that the fermentation gene cluster was present in MGH 78578 and 342, but absent in NTUH-K2044. In the present study, the previously unknown genome diversity of citrate fermentation among <it>K. pneumoniae </it>clinical isolates was investigated.</p> <p>Results</p> <p>Using a genomic microarray containing probe sequences from multiple <it>K. pneumoniae </it>strains, we investigated genetic diversity among <it>K. pneumoniae </it>clinical isolates and found that a genomic region containing the citrate fermentation genes was not universally present in all strains. We confirmed by PCR analysis that the gene cluster was detectable in about half of the strains tested. To demonstrate the metabolic function of the genomic region, anaerobic growth of <it>K. pneumoniae </it>in artificial urine medium (AUM) was examined for ten strains with different clinical histories and genomic backgrounds, and the citrate fermentation potential was found correlated with the genomic region. PCR detection of the genomic region yielded high positive rates among a variety of clinical isolates collected from urine, blood, wound infection, and pneumonia. Conserved genetic organizations in the vicinity of the citrate fermentation gene clusters among <it>K. pneumoniae</it>, <it>Salmonella enterica</it>, and <it>Escherichia coli </it>suggest that the13-kb genomic region were not independently acquired.</p> <p>Conclusion</p> <p>Not all, but nearly half of the <it>K. pneumoniae </it>clinical isolates carry the genes responsible for anaerobic growth on citrate. Genomic variation of citrate fermentation genes in <it>K. pneumoniae </it>may contribute to metabolic diversity and adaptation to variable nutrient conditions in different environments.</p