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Abstract The Marine Isotope Stage (MIS) 11c interglacial and its preceding glacial termination represent an enigmatically intense climate response to relatively weak insolation forcing. So far, a lack of radiometric age control has confounded a detailed assessment of the insolation-climate relationship during this period. Here, we present 230Th-dated speleothem proxy data from northern Italy and compare them with palaeoclimate records from the North Atlantic region. We find that interglacial conditions started in subtropical to middle latitudes at 423.1 ± 1.3 thousand years (kyr) before present, during a first weak insolation maximum, whereas northern high latitudes remained glaciated (sea level ~ 40 m below present). Some 14.5 ± 2.8 kyr after this early subtropical onset, peak interglacial conditions were reached globally, with sea level 6–13 m above present, despite weak insolation forcing. We attribute this remarkably intense climate response to an exceptionally long (~15 kyr) episode of intense poleward heat flux transport prior to the MIS 11c optimum.

The hospital-at-home (HaH) model delivers hospital-level acute care, including diagnostics, monitoring, and treatments, in a patient’s home. It is particularly effective for managing conditions such as pneumonia. Point-of-care ultrasonography (PoCUS) is a key diagnostic tool in the HaH model, and it often serves as a substitute for imaging-based diagnosis in the HaH setting. Both standard and handheld ultrasound equipment are suitable for lung ultrasound (LUS) evaluation. Curvelinear and linear probes are typically used. Patient positioning depends on their clinical condition and specific diagnostic protocols. To enhance sensitivity, we recommend using at least 10-point protocols supported by studies for pneumonia. Five essential LUS patterns should be identified, including A-line, multiple B-lines (alveolar-interstitial syndrome), confluent B-lines, subpleural consolidation, and consolidation with air bronchogram. Pleural effusion is common, and its internal echogenicity can indicate severity and the need for invasive procedures. The current evidence on various etiologies and types of pneumonia is limited, but LUS demonstrates good sensitivity in detecting abnormal sonographic patterns in atypical pneumonia, tuberculosis, and ventilator-associated pneumonia. Further LUS studies in the HaH setting are required to validate and generalize the findings.

Abstract The vagal nervous system is central to the physiological responses and systemic diseases of the liver. We evaluated the subsequent risk of liver and intrahepatic cancer (HCC/ICC) in non-H. pylori (HP)-infected perforated peptic ulcer (PPU) patients with and without vagotomy. Hospitalized PPU patients who underwent simple closure or truncal vagotomy/pyloroplasty (TVP) in the National Health Insurance Research Database from 2000 to 2008 were enrolled. The exclusion criteria included: (1) Multiple surgeries for PPU were received at the same admission; (2) Any cancer history; (3) Previous peptic ulcer-associated surgery; (4) HP infection history; (5) Viral hepatitis infection history; (6) Follow-up duration

As the population worldwide continues to age and the percentage of elderly people continues to increase, falls have been become the second leading cause of death from accidental or unintentional injuries. Although many imaging sensing devices have been used to detect falls for elderly people, most involve using the Internet to transfer images taken by a camera to a large back-end server, which performs the necessary calculations; however, algorithm limitations and computational complexity may cause bottlenecks in image outflow, and the image transfer can result in privacy problems. To address these problems, in this paper, an artificial intelligence (AI) fall detection method is proposed that operates using an edge computing architecture, called the pose estimation-based fall detection methodology (PEFDM), which is based on a human body posture recognition technique. The proposed PEFDM can effectively reduce the computational load, runs smoothly on mainstream edge computing systems and possesses artificial intelligence computing capabilities. By using edge computing, the privacy and upload bandwidth issues caused by image outflow can be eliminated. Experiments with real humans show that the PEFDM can detect falls for elderly people with a recognition accuracy of up to 98.1%.

Today, with the arrival of an aging society, the average age of the population is rising. It is known that the physiology of a person degrades with age. There are approximately 285 million visually impaired people in the world, of whom 140 million are elderly people over the age of 50, and 110 million of these visually impaired elderly people suffer from multiple chronic diseases. In the case of multiple medication usage, these 110 million vulnerable people will be more likely to take the wrong medicines or forget to take their medication. To solve this problem, this paper proposes a wearable smart-glasses-based drug pill recognition system using deep learning, named MedGlasses, for visually impaired people to improve their medication-use safety. The proposed MedGlasses system consists of a pair of wearable smart glasses, an artificial intelligence (AI)-based intelligent drug pill recognition box, a mobile device app, and a cloud-based information management platform. Experimental results show that a recognition accuracy of up to 95.1% can be achieved. Therefore, the proposed MedGlasses system can effectively mitigate the problem of drug interactions caused by taking incorrect drugs, thereby reducing the cost of medical treatment and providing visually impaired chronic patients with a safe medication environment.

Neurons are highly specialized cells with polarized cellular processes and subcellular domains. As vital organelles for neuronal functions, mitochondria are distributed by microtubule-based transport systems. Although the essential components of mitochondrial transport including motors and cargo adaptors are identified, it is less clear how mitochondrial distribution among somato-dendritic and axonal compartment is regulated. Here, we systematically study mitochondrial motors, including four kinesins, KIF5, KIF17, KIF1, KLP-6, and dynein, and transport regulators in C. elegans PVD neurons. Among all these motors, we found that mitochondrial export from soma to neurites is mainly mediated by KIF5/UNC-116. Interestingly, UNC-116 is especially important for axonal mitochondria, while dynein removes mitochondria from all plus-end dendrites and the axon. We surprisingly found one mitochondrial transport regulator for minus-end dendritic compartment, TRAK-1, and two mitochondrial transport regulators for axonal compartment, CRMP/UNC-33 and JIP3/UNC-16. While JIP3/UNC-16 suppresses axonal mitochondria, CRMP/UNC-33 is critical for axonal mitochondria; nearly no axonal mitochondria present in unc-33 mutants. We showed that UNC-33 is essential for organizing the population of UNC-116-associated microtubule bundles, which are tracks for mitochondrial trafficking. Disarrangement of these tracks impedes mitochondrial transport to the axon. In summary, we identified a compartment-specific transport regulation of mitochondria by UNC-33 through organizing microtubule tracks for different kinesin motors other than microtubule polarity.

Aim: Taiwan’s response to the coronavirus disease 2019 (COVID-19) differed in that it successfully prevented the spread without having to shutdown or overburden medical services. Patients’ fear regarding the pandemic would be the only reason to reduce surgeries, so Taiwan could be the most suitable place for research on the influence of psychological factors. This study aimed to assess the impact of patients’ fear on orthopedic surgeries in Taiwan amid the peak period of the COVID-19 pandemic. Patients and Methods: The investigation period included the COVID-19 pandemic (March 2020 to April 2020) and the corresponding period in the previous year. The following data on patients with orthopedic diseases were collected: outpatient visits, hospital admission, and surgical modalities. Results: The COVID-19 pandemic led to a 22%–29% and 20%–26% reduction in outpatients, 22%–27% and 25%–37% reduction in admissions, and 26%–35% and 18%–34% reduction in surgeries, respectively, at both hospitals. The weekly mean number of patients was significantly smaller during the COVID-19 pandemic for all types of surgery and elective surgeries at the university hospital, and for all types of surgery, elective surgeries, and total knee arthroplasties at the community hospital. Further, patients visiting the community hospital during the pandemic were significantly younger, for all types of surgery, elective surgeries, and total knee arthroplasties. Conclusions: The reduction in orthopedic surgeries in Taiwan’s hospitals during COVID-19 could be attributed to patients’ fear. Even without restriction, the pandemic inevitably led to a reduction of about 20%–30% of the operation volume.

This paper proposes an intelligent medicine recognition system based on deep learning techniques, named ST-Med-Box. The proposed system can assist chronic patients in taking multiple medications correctly and avoiding in taking the wrong medications, which may cause drug interactions, and can provide other medication-related functionalities such as reminders to take medications on time, medication information, and chronic patient information management. The proposed system consists of an intelligent medicine recognition device, an app running on an Android-based mobile device, a deep learning training server, and a cloud-based management platform. Currently, eight different medicines can be recognized by the proposed system. The experimental results show that the recognition accuracy reaches 96.6%. Therefore, the proposed system can effectively reduce the problem of drug interactions caused by taking incorrect drugs, thereby reducing the cost of medical treatment and giving patients with chronic diseases a safe medication environment.

INTRODUCTION:Enteral nutrition (EN) is important in the management of critically illness. Yet, the best route (e.g. pre-pyloric or post-pyloric) for EN in critically ill patients remains to be investigated, especially in specific surgical patients group. In addition, EN could be associated with a higher risk of aspiration pneumonia. Therefore, we evaluate the effect of various EN routes in surgical critically ill perforated peptic ulcer (PPU) patients who underwent surgery and required mechanical ventilation. METHOD:We collected data of surgical critically ill PPU patients admitted to intensive care unit. The patients were managed with appropriate care bundle and program. To reduce the impact of surgery types, we excluded those who had received other surgical procedures and included patients that only received simple closure. Patients were classified into nasogastric and jejunostomy feeding groups. The demographics, severity scores (e.g.: APACHE II, SOFA, and POSSUM), body mass index (BMI), comorbidities, ventilator days, use of proton pump inhibitors (PPIs), pneumonia occurrence, mortality and complications were collected for analysis. RESULTS:A total of 136 critically ill PPU patients that received surgery and mechanical ventilation were enrolled. There were 53 patients in NG group and 83 patients in FJ group. There were no differences in demographics, severity scores, BMI, comorbidities, ventilator days, use of PPIs, pneumonia occurrence, mortalities and complications between groups. CONCLUSION:Our study indicates that there are no differences in mortalities and pneumonia occurrence using nasogastric or feeding jejunostomy in surgical critically ill PPU patients underwent surgery. However, further studies are required.

A protein concentration measurement system with two-port flexural plate-wave (FPW) biosensors using a frequency-shift readout technique is presented in this paper. The proposed frequency-shift readout method employs a peak detecting scheme to measure the amount of resonant frequency shift. The proposed system is composed of a linear frequency generator, a pair of peak detectors, two registers, and a subtractor. The frequency sweep range of the linear frequency generator is limited to 2 MHz to 10 MHz according to the characteristics of the FPW biosensors. The proposed frequency-shift readout circuit is carried out on silicon using a standard 0.18 μm CMOS technology. The sensitivity of the peak detectors is measured to be 10 mV. The power consumption of the proposed protein concentration measurement system is 48 mW given a 0.1 MHz system clock.

The hull of high performance submarines must resist underwater shock loading due to exploding torpedoes or depth bombs. An underwater shock involving an initial shock wave and successive bubble pulsating waves is so complex that a theoretical technique for deriving shock pressure distribution is required for improving simulation efficiency. Complete shock loading is obtained theoretically in this work, and responses of a submarine pressure hull are calculated using ABAQUS USA (Underwater Shock Analysis) codes. In the long run, this deflection and stress data will assist in examining the structural arrangement of the submarine pressure hull.

Notch signaling pathway defines an evolutionarily conserved mechanism in cell-fate determination in a broad spectrum of developmental processes through local cell interactions. mind bomb (mib) encodes an E3 ubiquitin ligase that is involved in Notch activation through Delta ubiquitylation and internalization. To further dissect the function of Mib, two yeast two-hybrid screens for zebrafish Mib/Mib2-binding proteins with different strategies have been performed. 81 putative interesting proteins were discovered and classified into six groups: ubiquitin proteasome pathway, cytoskeleton, trafficking, replication/transcription/translation factors, cell signaling and others. Confirmed by coimmunoprecipitation (Co-IP), Mib interacted with four tested proteins: ubiquitin specific protease 1 (Usp1), ubiquitin specific protease 9 (Usp9), tumor-necrosis-factor-receptor-associated factor (TRAF)-binding domain (Trabid)/zinc finger, RAN-binding domain containing 1 (Zranb1) and hypoxia-inducible factor 1, alpha subunit inhibitor (Hif1an)/factor inhibiting HIF 1 (Fih-1). Usp1, Usp9, Trabid and Fih-1 also bound to zebrafish Mib2, a Mib homolog with similar structural domains and functions. Both Mib and Mib2 can ubiquitylate Trabid and Fih-1, indicating a potential regulating role of Mib and Mib2 on Trabid and Fih-1 and, furthermore, the possible involvement of Notch signaling in hypoxia-regulated differentiation, tumorigenesis and NF-κB pathway. Finally, functions of confirmed Mib/Mib2-interacting proteins are collated, summarized and hypothesized, which depicts a regulating network beyond Notch signaling.

Data acquisition and supervisory control are usually performed using client-server architecture and centralized control in conventional power systems. However, the message transmission and fault clearing are too slow for large-scale complex power systems. Microgrid systems have various types of distributed energy resources (DERs) which are quite different in characteristics and capacities, thus, the client-server architecture and centralized control are inadequate to control and operate in microgrids. Based on MATLAB/Simulink (ver.R2012a) simulation software and Java Agent Development Framework (JADE) (JADE 4.1.1-revision 6532), this paper proposes a novel fault protection technology that used multi-agent system (MAS) to perform fault detection, fault isolation and service restoration in microgrids. A new topology identification method using the YBus Matrix Algorithm is presented to successfully recognize the network configurations. The identification technology can respond to microgrid variations. Furthermore, the interactive communications among intelligent electronic devices (IEDs), circuit breakers (CBs), and agents are clarified during fault occurrence. The simulation results show that the proposed MAS-based microgrids can promptly isolate faults and protect the system against faults in real time.

Many organs in vertebrates are left-right asymmetrical located. For example, liver is at the right side and stomach is at the left side in human. Fibroblast growth factor (Fgf) signaling is important for left-right asymmetry. To investigate the roles of Fgfr2 signaling in zebrafish left-right asymmetry, we used splicing blocking morpholinos to specifically block the splicing of fgfr2b and fgfr2c variants, respectively. We found that the relative position of the liver and the pancreas were disrupted in fgfr2c morphants. Furthermore, the left-right asymmetry of the heart became random. Expression pattern of the laterality controlling genes, spaw and pitx2c, also became random in the morphants. Furthermore, lefty1 was not expressed in the posterior notochord, indicating that the molecular midline barrier had been disrupted. It was also not expressed in the brain diencephalon. Kupffer's vesicle (KV) size became smaller in fgfr2c morphants. Furthermore, KV cilia were shorter in fgfr2c morphants. We conclude that the fgfr2c isoform plays an important role in the left-right asymmetry during zebrafish development.