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Quantum annealing has been actively researched since D-Wave Systems produced the first commercial machine in 2011. Controlling a large fleet of automated guided vehicles is one of the real-world applications utilizing quantum annealing. In this study, we propose a formulation to control the traveling routes to minimize the travel time. We validate our formulation through simulation in a virtual plant and authenticate the effectiveness for faster distribution compared to a greedy algorithm that does not consider the overall detour distance. Furthermore, we utilize reverse annealing to maximize the advantage of the D-Wave’s quantum annealer. Starting from relatively good solutions obtained by a fast greedy algorithm, reverse annealing searches for better solutions around them. Our reverse annealing method improves the performance compared to standard quantum annealing alone and performs up to 10 times faster than a commercial classical solver, Gurobi. This study extends a use of optimization with general problem solvers in the application of multi-AGV systems and reveals the potential of reverse annealing as an optimizer.

Quantum annealing was originally proposed as an approach for solving combinatorial optimization problems using quantum effects. D-Wave Systems has released a production model of quantum annealing hardware. However, the inherent noise and various environmental factors in the hardware hamper the determination of optimal solutions. In addition, the freezing effect in regions with weak quantum fluctuations generates outputs approximately following a Gibbs–Boltzmann distribution at an extremely low temperature. Thus, a quantum annealer may also serve as a fast sampler for the Ising spin-glass problem, and several studies have investigated Boltzmann machine learning using a quantum annealer. Previous developments have focused on comparing the performance in the standard distance of the resulting distributions between conventional methods in classical computers and sampling by a quantum annealer. In this study, we focused on the performance of a quantum annealer as a generative model from a different aspect. To evaluate its performance, we prepared a discriminator given by a neural network trained on an a priori dataset. The evaluation results show a higher performance of quantum annealer compared with the classical approach for Boltzmann machine learning in training of the generative model. However the generation of the data suffers from the remanent quantum fluctuation in the quantum annealer. The quality of the generated images from the quantum annealer gets worse than the ideal case of the quantum annealing and the classical Monte-Carlo sampling.

Quantum annealing has garnered significant attention as meta-heuristics inspired by quantum physics for combinatorial optimization problems. Among its many applications, nonnegative/binary matrix factorization stands out for its complexity and relevance in unsupervised machine learning. The use of reverse annealing, a derivative procedure of quantum annealing to prioritize the search in a vicinity under a given initial state, helps improve its optimization performance in matrix factorization. This study proposes an improved strategy that integrates reverse annealing with a linear programming relaxation technique. Using relaxed solutions as the initial configuration for reverse annealing, we demonstrate improvements in optimization performance comparable to the exact optimization methods. Our experiments on facial image datasets show that our method provides better convergence than known reverse annealing methods. Furthermore, we investigate the effectiveness of relaxation-based initialization methods on randomized datasets, demonstrating a relationship between the relaxed solution and the optimal solution. This research underscores the potential of combining reverse annealing and classical optimization strategies to enhance optimization performance.

Familial adenomatous polyposis (FAP) is an autosomal dominant syndrome caused by germline variants in the APC gene, leading to the development of numerous colorectal polyps and significantly increases the risk of colorectal cancer. A diagnosis is typically made using colonoscopy, and genetic testing can assist in patient surveillance and carrier identification. Recent advances include the use of whole-genome array comparative genomic hybridization (a-CGH), which provides better resolution of genetic imbalances. We aimed to explore the specific features of FAP patients with whole APC gene deletions using high-resolution a-CGH and to compare patient characteristics. Two polyposis patients with whole APC deletions were identified, and the lost genetic sizes ranged from 0.3–1.1 Mb. Nervous abnormalities were a characteristic symptom in a patient with a 1.1 Mb loss. A patient with an approximately 0.3 Mb loss, which included the entire APC gene, presented a polyposis phenotype without intellectual disability. The comparison of genetic losses, with or without intellectual disability, revealed 7 genetic changes. Consequently, EPB41L4A is a candidate gene associated with the neurogenic phenotype.

Background Pancreatic cancer is associated with an extremely poor prognosis, so new biomarkers that can detect the initial stages are urgently needed. The significance of serum microRNA (miR) levels in pancreatic neoplasm such as pancreatic cancer and intraductal papillary mucinous neoplasm (IPMN) diagnosis remains unclear. We herein evaluated the usefulness of miRs enclosed in serum exosomes (ExmiRs) as diagnostic markers. Methods The ExmiRs from patients with pancreatic cancer ( n  = 32) or IPMN ( n  = 29), and patients without neoplasms (controls; n  = 22) were enriched using ExoQuick-TC™. The expression of ExmiRs was evaluated using a next-generation sequencing analysis, and the selected three miRs through this analysis were confirmed by a quantitative real-time polymerase chain reaction. Results The expression of ExmiR-191, ExmiR-21 and ExmiR-451a was significantly up-regulated in patients with pancreatic cancer and IPMN compared to the controls ( p  < 0.05). A receiver operating characteristic curve analysis showed that the area under the curve and the diagnostic accuracy of ExmiRs were 5–20% superior to those of three serum bulky circulating miRs (e.g.; ExmiR-21: AUC 0.826, accuracy 80.8%. Circulating miR-21: AUC 0.653, accuracy 62.3%). In addition, high ExmiR-451a was associated with mural nodules in IPMN ( p  = 0.010), and high ExmiR-21 was identified as a candidate prognostic factor for the overall survival ( p  = 0.011, HR 4.071, median OS of high-ExmiR-21: 344 days, median OS of low-ExmiR-21: 846 days) and chemo-resistant markers ( p  = 0.022). Conclusions The level of three ExmiRs can thus serve as early diagnostic and progression markers of pancreatic cancer and IPMN, and considered more useful markers than the circulating miRs (limited to these three miRs).

Timely detection of anomalies and automatic interpretation of an electrocardiogram (ECG) play a crucial role in many healthcare applications, such as patient monitoring and post treatments. Beat-wise segmentation is one of the essential steps in ensuring the confidence and fidelity of many automatic ECG classification methods. In this sense, we present a reliable ECG beat segmentation technique using a CNN model with an adaptive windowing algorithm. The proposed adaptive windowing algorithm can recognise cardiac cycle events and perform segmentation, including regular and irregular beats from an ECG signal with satisfactorily accurate boundaries.The proposed algorithm was evaluated quantitatively and qualitatively based on the annotations provided with the datasets and beat-wise manual inspection. The algorithm performed satisfactorily well for the MIT-BIH dataset with a 99.08% accuracy and a 99.08% of F1-score in detecting heartbeats along with a 99.25% of accuracy in determining correct boundaries. The proposed method successfully detected heartbeats from the European S-T database with a 98.3% accuracy and 97.4% precision. The algorithm showed 99.4% of accuracy and precision for Fantasia database. In summary, the algorithm’s overall performance on these three datasets suggests a high possibility of applying this algorithm in various applications in ECG analysis, including clinical applications with greater confidence.

Background Placenta accreta is a major cause of massive obstetric hemorrhage during cesarean section. In recent years, pregnancy by in vitro fertilization-embryo transfer has been reported as a risk factor for placenta accreta. Case presentation A 36-year-old G1P0 woman with systemic lupus erythematosus became pregnant by frozen-thawed embryo transfer. Emergency cesarean section was performed under general anesthesia due to the diagnosis of non-reassuring fetal status. The placenta invaded the myometrium and completely covered the entire anterior uterine wall. Following birth, 3000 mL of blood loss required rapid fluid infusion and blood transfusion. Total hysterectomy was performed because the placenta could not be separated from the uterine wall. Histological examination revealed placenta accreta/increta. Conclusions When performing cesarean section on patients who have undergone frozen-thawed embryo transfer, preoperative examinations to assess for placenta accreta should be performed, and the anesthetic management should include sufficient planning for massive obstetric hemorrhage.

The quantitative estimation of stereoscopic molecular orientations in semicrystalline polymer thin films with characteristic heterogeneous structures is essential for the development of advanced film materials. Grazing-incidence X-ray diffraction (GI-XRD) is a powerful technique used to evaluate the orientational order of crystalline lattices; however, it provides the orientational order of only ordered regions (crystal and glassy liquid crystal regions). In contrast, infrared (IR) p-polarized multiple-angle incidence resolution spectrometry (pMAIRS) can provide the averaged orientational order of overall regions in a film regardless of sample crystallinity. This paper combines variable-temperature (VT) pMAIRS, static GI-XRD and spectroscopic ellipsometry and reports general insight into the molecular orientation mechanism occurring in polymer films revealed through the precise analysis of the structural evolution of linear poly(amic n-alkyl ester), PAE, with different lengths of n-alkyl chains during thermal curing, which involves solvent evaporation and dehydration imidization reactions to form the corresponding polyimide (PI). This combined method clarified that the PAE and PI thin films had a heterogeneous structure consisting of a glassy liquid-crystalline (ordered) region and a nonoriented amorphous region. Furthermore, imidization proceeded faster in the amorphous region than in the ordered (oriented) region. In addition, anomalies of refractive index and birefringence were found by comparing pMAIRS and spectroscopic ellipsometry, although the effect of the side chain length on the molecular orientation of PI was insignificant. The anomalies indicate that an isotropic void structures were generated by the elimination reaction of the side chains and that the volume fraction of voids increased with increasing side chain length. These results demonstrated that the combination of VT-pMAIRS and GI-XRD is a very powerful tool for the in situ structural analyses of noncrystalline (disordered crystal, glassy liquid crystal, and oriented amorphous) thin-film materials ongoing chemical reactions in their components and is inherently applicable to all kinds of interesting polymeric thin-film materials.Thin film aromatic polyimides were quantitatively analyzed by grazing-incidence X-ray diffraction (GI-XRD), variable-temperature infrared p-polarized multiple-angle resolution spectroscopy (VT-pMAIRS), and spectroscopic ellipsometry (SE) methods. Combining VT-pMAIRS and GI-XRD revealed characteristic heterogeneous structures comprising non-oriented amorphous and oriented liquid-crystalline glass regions. Additionally, SE indicated that the film involved anisotropic-shaped void inducing form-birefringence. Such an excess of birefringence can make it difficult to estimate orientational order using birefringence measurement. This methodology presented here will remarkably contribute to general structural analyses of all intriguing thin-film polymers with characteristic heterogeneity.

Background A workforce of foreign workers, mainly from Southeast Asia (SEA), is increasing because of an aging society and a declining birthrate. However, there are a few hospitals that can accept them. In this study, we evaluated whether SEA persons can understand medication-related information translated from Japanese into SEA languages using Google Translate. Methods The study was a questionnaire survey of simulated cases. Information on simulated cases in Japanese was translated into each target language using Google Translate. We set the answer to the questionnaire based on the simulated cases. Participants’ backgrounds and answers to the questionnaire were aggregated for each target language and category. Results The participants were 24 people from Thailand, Vietnam, Indonesia, and Burma. Comprehension outcomes differed across medications and information types. While understanding of main effects and side effects was generally adequate, comprehension of medication usage was limited, particularly for loxoprofen, with substantial variation across language groups. Conclusions It’s challenging to communicate medical information accurately to the SEA patients when relying solely on Google Translate. Therefore, we may need to provide medication guidance orally to improve and enhance medication-related information, even if we cannot speak SEA languages.

Synanthropic wild rodents associated with agricultural operations may represent a risk path for transmission of high pathogenicity avian influenza viruses (HPAIVs) from wild birds to poultry birds. However, their susceptibility to HPAIVs remains unclear. In the present study, house mice (Mus musculus), brown rats (Rattus norvegicus), and black rats (Rattus rattus) were experimentally exposed to H5N1 subtype HPAIVs to evaluate their vulnerability to infection. After intranasal inoculation with HA clade 2.2 and 2.3.2.1 H5N1 subtype HPAIVs, wild rodents did not show any clinical signs and survived for 10- and 12-day observation periods. Viruses were isolated from oral swabs for several days after inoculation, while little or no virus was detected in their feces or rectal swabs. In euthanized animals at 3 days post-inoculation, HPAIVs were primarily detected in respiratory tract tissues such as the nasal turbinates, trachea, and lungs. Serum HI antibodies were detected in HA clade 2.2 HPAIV-inoculated rodents. These results strongly suggest that synanthropic wild rodents are susceptible to infection of avian-origin H5N1 subtype HPAIVs and contribute to the virus ecosystem as replication-competent hosts. Detection of infectious viruses in oral swabs indicates that wild rodents exposed to HPAIVs could contaminate food, water, and the environment in poultry houses and play roles in the introduction and spread of HPAIVs in farms.