Miracle-dz/UniFAR-FTUs huggingface dataset:
Implementing AI Models for Prognostic Predictions in High-Risk Burn Patients

Background and Objectives: Burn injuries range from minor medical issues to severe, life-threatening conditions. The severity and location of the burn dictate its treatment; while minor burns might be treatable at home, severe burns necessitate medical intervention, sometimes in specialized burn centers with extended follow-up care. This study aims to leverage artificial intelligence (AI)/machine learning (ML) to forecast potential adverse effects in burn patients. Methods: This retrospective analysis considered burn patients admitted to Chi Mei Medical Center from 2010 to 2019. The study employed 14 features, comprising supplementary information like prior comorbidities and laboratory results, for building models for predicting graft surgery, a prolonged hospital stay, and overall adverse effects. Overall, 70% of the data set trained the AI models, with the remaining 30% reserved for testing. Three ML algorithms of random forest, LightGBM, and logistic regression were employed with evaluation metrics of accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC). Results: In this research, out of 224 patients assessed, the random forest model yielded the highest AUC for predictions related to prolonged hospital stays (>14 days) at 81.1%, followed by the XGBoost (79.9%) and LightGBM (79.5%) models. Besides, the random forest model of the need for a skin graft showed the highest AUC (78.8%), while the random forest model and XGBoost model of the occurrence of adverse complications both demonstrated the highest AUC (87.2%) as well. Based on the best models with the highest AUC values, an AI prediction system is designed and integrated into hospital information systems to assist physicians in the decision-making process. Conclusions: AI techniques showcased exceptional capabilities for predicting a prolonged hospital stay, the need for a skin graft, and the occurrence of overall adverse complications for burn patients. The insights from our study fuel optimism for the inception of a novel predictive model that can seamlessly meld with hospital information systems, enhancing clinical decisions and bolstering physician–patient dialogues.
Ongoing fragmentation of the subducting Cocos slab, Central America

Fundamental to plate tectonics is the subduction of cold and mechanically strong oceanic plates. While the subducted plates are conventionally regarded to be impermeable to mantle flow and separate the mantle wedge and the subslab region, isolated openings have been proposed. By combining new shear wave splitting measurements with results from geodynamic modeling and recent seismic tomography and geochemical observations, we show that the upper ∼200 km of the Cocos slab in northern Central America is intensively fractured. The slab there is strong enough to produce typical arc volcanoes and Benioff Zone earthquakes but allows mantle flow to traverse from the subslab region to the mantle wedge. Upwelling of hot subslab mantle flow through the slab provides a viable explanation for the behind-the-volcanic-front volcanoes that are geochemically distinct from typical arc volcanoes, and for the puzzling high heat flow, high elevation, and low Bouguer gravity anomalies observed in northern Central America.
Development of a Perfusing Small Intestine–Liver Microphysiological System Device

There is an increasing need to develop alternatives to animal modeling and testing for pre-clinical studies as researchers face major challenges, such as the study of dynamic systems in laboratory settings. Microphysiological system (MPS) technology has recently shown great potential for addressing such limitations. We developed a perfusing small intestine–liver-connected device that is easy to operate and highly reproducible. In non-clinical pharmacokinetics and safety studies, the use of human-derived materials is necessary. We used human iPS cell-derived small intestinal epithelial cells (HiEs) and cryopreserved human primary hepatocytes. Hepatocytes in 3D culture were co-cultured with swiss-albino 3T3 cells as feeder cells. We evaluated the effects of co-culturing hepatocytes and HiEs using our small intestine–liver device. The mRNA expression levels of CYP1A2 and CYP3A4 in hepatocytes were significantly increased in the 3D culture. The TEER values were increased in HiEs co-cultured with hepatocytes in the 3D culture. We evaluated the differential proliferation and function characteristics of the hepatocytes and HiEs following perfusion and verified the utility of our proposed small intestine–liver device for evaluating multiple cell populations. The perfusion culture system of our small intestine–liver device can be used to investigate distinct effects on co-cultured hepatocytes and HiEs.
Acylated ghrelin suppresses doxorubicin-induced testicular damage and improves sperm parameters in rats via activation of Nrf2 and mammalian target of rapamycin

Background: Exogenous administration of acylated ghrelin (AG) afforded reproductive protective effect in several animal models but not in those treated with doxorubicin (DOX). This study evaluated the protective effect of AG against DOX-induced testicular damage and impairment in sperm parameters in rats and examined the potential mechanisms of action. Materials and Methods: Adult male rats were divided into five groups (n = 8/each) as control, control + AG (40 nmol/kg/day; subcutaneous), DOX (10 mg/kg/day 1; intraperitoneal [i.p.]), DOX + AG, and DOX + AG + brusatol (an Nrf2 inhibitor) (2 mg/kg/every 3 days; i.p.). The treatment regimen continued for 65 days. Results: AG prevented testicular damage and apoptosis; increased sperm count, motility, and viability; and reduced the number of abnormal sperms. It also increased their circulatory levels of AG, des-acylated ghrelin (DAG), and AG/DAG ratio and the testicular mRNA levels of ghrelin and growth hormone secretagogue receptor 1a Concomitantly, AG increased serum and testicular testosterone levels, reduced serum levels of the follicle-stimulating hormone and luteinizing hormone, and upregulated the testicular protein levels of the steroidogenic acute regulatory protein and 3β-hydroxysteroid dehydrogenase in DOX-treated rats. In the testes of the control and DOX-treated rats, AG increased the phosphorylation of mammalian target of rapamycin and stimulated the levels of glutathione and superoxide dismutase, as well as the nuclear activation of Nrf2. All these effects were completely prevented by co-treatment with brusatol. Conclusion: AG replacement therapy could be a novel strategy to prevent reproductive toxicity in cancer patients.
ZnO-Based Flexible UV Photodetector for Wearable Electronic Applications

This study pivots on the ZnO-based flexible ultraviolet (UV) photodetector (PD) for wearable electronic applications. The high-quality ZnO thin film is deposited via reactive magnetron sputtering on a polyimide (PI) flexible substrate. Furthermore, metal–semiconductor–metal (MSM) PD device performance is investigated in both normal and device bending conditions to evaluate the various photography detecting performance parameters comprising <inline-formula> <tex-math notation="LaTeX">${I}$ </tex-math></inline-formula>–<inline-formula> <tex-math notation="LaTeX">${V}$ </tex-math></inline-formula>, responsivity (R), external quantum efficiency (EQE), and switching response. The important aspect of this study is, at higher voltage, the dark and photocurrent of the MSM PD at normal and bending conditions of substrate, does not change significantly. The morphology and optical property of the ZnO thin film is verified via atomic force microscope (AFM) and ellipsometry characterization. In addition, the device performance is attributed to governing physics, which are thermionic field-emission theory and piezophototronic effect, collectively. The peak R and EQE at 6 V for normal conditions are 0.5 A/W and 45%, respectively, which remain almost the same for bending conditions also. The rise time of the PD at the highest bending condition is 215 ms with an <inline-formula> <tex-math notation="LaTeX">${I}_{ \mathrm{\scriptscriptstyle ON}}/{I}_{ \mathrm{\scriptscriptstyle OFF}}$ </tex-math></inline-formula> ratio for all the conditions higher than <inline-formula> <tex-math notation="LaTeX">$10^{{2}}$ </tex-math></inline-formula> times. The robust response of this flexible PD device under bent conditions at higher voltage clears the prospect of the PD for the Internet of Things (IoT) and other wearable electronic applications.
Hidden-charm pentaquarks and 
Pc
 states

Recently, the LHCb Collaboration reported three $P_c$ states in the ${J/\psi}p$ channel. We systematically study the mass spectrum of the hidden charm pentaquark in the framework of an extended chromomagnetic model. For the $nnnc\bar{c}$ pentaquark with $I=1/2$, we find that (i) the lowest state is $P_{c}(4327.0,1/2,1/2^{-})$ [We use $P_{c}(m,I,J^{P})$ to denote the $nnnc\bar{c}$ pentaquark], which corresponds to the $P_{c}(4312)$. Its dominant decay mode is $\Lambda_{c}\bar{D}^{*}$. (ii) We find two states in the vicinity of $P_{c}(4380)$. The first one is $P_{c}(4367.4,1/2,3/2^{-})$ and decays dominantly to $N{J/\psi}$ and $\Lambda_{c}\bar{D}^{*}$. The other one is $P_{c}(4372.4,1/2,1/2^{-})$. Its dominant decay mode is $\Lambda_{c}\bar{D}$, and its partial decay width of $N\eta_{c}$ channel is comparable to that of $N{J/\psi}$. (iii) In higher mass region, we find $P_{c}(4476.3,1/2,3/2^{-})$ and $P_{c}(4480.9,1/2,1/2^{-})$, which correspond to $P_{c}(4440)$ and $P_{c}(4457)$. In the open charm channels, both of them decay dominantly to the $\Lambda_{c}\bar{D}^{*}$. (iv) We predict two states above $4.5~\text{GeV}$, namely $P_{c}(4524.5,1/2,3/2^{-})$ and $P_{c}(4546.0,1/2,5/2^{-})$. The masses of the $nnnc\bar{c}$ state with $I=3/2$ are all over $4.6~\text{GeV}$. Moreover, we use the model to explore the $nnsc\bar{c}$, $ssnc\bar{c}$ and $sssc\bar{c}$ pentaquark states.
Miniaturized, Low-Profile, Triple-Band Microstrip Antenna and its Four-Antenna Module for Smartphone Applications

A miniaturized, low-profile, triple-band, and four-port multi-input multi-output (MIMO) microstrip antenna module (MAM) is proposed for smartphones. First, a planar integrated L-shaped capacitively coupled feeding probe, a stepped slot, and a grounding via are sequentially exploited. As a result, TM0,1, TM1,1, and quasi-TM2,0 modes are independently manipulated to make a microstrip antenna (MA) operate in the 2.4-GHz WLAN, fifth-generation (5G) N78, and N79 bands, respectively. Both good impedance matching and radiation properties are realized with a small volume of $28.4\times 28.4\times 1$ mm3. Then, a triple-band four-port MIMO MAM is constructed by sequentially rotating the proposed antenna element. As a validation of the concept, the proposed integrated four-port antenna module with an electrical volume of only $0.48\lambda _{\text {L}} \times 0.48\lambda _{\text {L}} \times 0.008\lambda _{\text {L}}$ is fabricated and experimentally tested, presenting a good consistency between the measurements and simulations. Without adding any extra decoupling structures between antenna elements, port isolations are better than 15.9 dB and envelope correlation coefficients (ECCs) are lower than 0.07, respectively. Compared with the existing triple-band four-MAMs, the proposed one is with the advantages of small volume, easy integration, and high isolation for 5G smartphone and terminal applications.
Combining Federated Learning and Edge Computing Toward Ubiquitous Intelligence in 6G Network: Challenges, Recent Advances, and Future Directions

Full leverage of the huge volume of data generated on a large number of user devices for providing intelligent services in the 6G network calls for Ubiquitous Intelligence (UI). A key to developing UI lies in the involvement of the large number of network devices, which contribute their data to collaborative Machine Learning (ML) and provide their computational resources to support the learning process. Federated Learning (FL) is a new ML method that enables data owners to collaborate in model training without exposing private data, which allows user devices to contribute their data to developing UI. Edge computing deploys cloud-like capabilities at the network edge, which enables network devices to offer their computational resources for supporting FL. Therefore, a combination of FL and edge computing may greatly facilitate the development of ubiquitous intelligence in the 6G network. In this article, we present a comprehensive survey of the recent developments in technologies for combining FL and edge computing with a holistic vision across the fields of FL and edge computing. We conduct our survey from both the perspective of an FL framework deployed in an edge computing environment (FL in Edge) and the perspective of an edge computing system providing a platform for FL (Edge for FL). From the FL in Edge perspective, we first identify the main challenges to FL in edge computing and then survey the representative technical strategies for addressing the challenges. From the Edge for FL perspective, we first analyze the key requirements for edge computing to support FL and then review the recent advances in edge computing technologies that may be exploited to meet the requirements. Then we discuss open problems and identify some possible directions for future research on combining FL and edge computing, with the hope of arousing the research community’s interest in this emerging and exciting interdisciplinary field.
Genetic Mutation Signature for Relapse Prediction in Normal Karyotype Acute Myeloid Leukemia.

OBJECTIVES Risk stratification for normal karyotype acute myeloid leukemia (NK-AML) remains unsatisfactory, which is reflected by the high incidence of leukemia relapse. This study aimed to evaluate the role of gene mutations and clinical characterization in predicting the relapse of patients with NK-AML. METHODS A prognostic system for NK-AML was constructed. A panel of gene mutations was explored using next-generation sequencing. A nomogram algorithm was used to build a genomic mutation signature (GMS) nomogram (GMSN) model that combines GMS, measurable residual disease, and clinical factors to predict relapse in 347 patients with NK-AML from four centers. RESULTS Patients in the GMS-high group had a higher 5-year incidence of relapse than those in the GMS-low group (P < 0.001). The 5-year incidence of relapse was also higher in patients in the GMSN-high group than in those in the GMSN-intermediate and -low groups (P < 0.001). The 5-year disease-free survival and overall survival rates were lower in patients in the GMSN-high group than in those in the GMSN-intermediate and -low groups (P < 0.001) as confirmed by training and validation cohorts. CONCLUSION This study illustrates the potential of GMSN as a predictor of NK-AML relapse.
Modelling ungauged lowland basins: Does complementary groundwater data add value to topography driven conceptual modelling?

A common practice for hydrologists to determine the performance of a hydrological model and its parameter values, is by calibrating the model parameters on observed discharge data, but this data is not always available. For this reason, other data should be used as complementary data in order to reduce the uncertainty of outflow and processes in the ungauged basins. This thesis presents a case study on an area in Baden-Wurttemberg, Germany, to see whether groundwaterlevel data can be used as complementary data for hydrological models of ungauged basins. It has been divided into two Hydrological Response Units (Lowland and Hillslope) with use of the surface slope and the height above the nearest drainage (HAND) algorithm. The main result is that a combined addition of groundwater level measurements and constraints did show reduced uncertainty, and thus improvement, of the internal model processes, especially the fluxes towards and out of the slow responding reservoir. Validation of these processes still remains difficult in ungauged areas, but it is believed that valid results can be made on the outflow out of the lowland areas with a combination of constraints and groundwater measurements to determine internal processes, and evaporation estimates obtained from satellite imagery to reduce the uncertainty of the total runoff out of the area.
The Dynamics of Corporate Governance: Evidence from Brazil

We study the evolution of corporate governance (CG) practices in Brazil over 2010-2019, using a country-specific Brazil Corporate Governance Index (BCGI) validated in prior work. We study separately firms in high-governance and low-governance legal regimes, in a single country. CG improved considerably in Brazil over 2010-2015, with much smaller changes over 2015-2019. Positive CG changes are much more common than negative changes. Some firms made only minimal changes, despite low initial CG levels. We also study which firm financial factors predict both CG levels and changes in levels. None of the firm financial variables we study consistently predicts CG levels. However, for CG changes, a measure of equity financing need predicts CG improvements in the first half of the sample period, but only for firms in the lower governance regime, not for firms in the higher regime. This is the first article to find evidence for firm financial characteristics predicting CG changes, consistent with theoretical predictions, including stronger effects for firms in the lower governance regime.
SELD U-Net: Joint Optimization of Sound Event Localization and Detection With Noise Reduction

Sound event localization and detection (SELD) is a combined task that classifies acoustic events from audio signals, estimates temporal boundaries, and identifies event locations. With the advancement of industries utilizing audio signals, SELD has been applied in various fields, and deep-learning-based research is being conducted for its effective application. However, current deep-learning-based SELD research focuses mainly on performance improvement in noise-free environments, which leads to performance degradation issues in noisy environments. To address this problem, this study proposes a robust SELD U-Net model that performs SELD in noisy environments. The proposed model combines a U-Net to remove noise and a SELDnet to perform SELD. The proposed model was trained and evaluated using noisy environmental data with various sizes. Consequently, it was confirmed that the proposed model has superior performance compared with existing deep learning-based SELD models in environments with high levels of noise.
A Multidisciplinary Approach to the Development of Thermal Clay Modules

This study focuses on the idea that industrial production methods, combined with a craft-based approach, enable the production of distinctive expressive thermal functionalities. We developed extruded modules based on a hands-on explorative craft approach in parallel with virtual simulations to explore how heat and cold are transported dynamically through building modules. This paper discusses the developed method and process used in a multidisciplinary approach that combines the quality of craft-based practice with architecture, engineering and programming, focusing on how craft practitioners experiment with material, technique and aesthetics in such a multidisciplinary approach. In this study, immediate concrete design proposals demonstrated a helpful way of establishing common ground for multidisciplinary collaboration. Concrete design proposals are pivotal in addressing the suggested design’s advantages and disadvantages and clarifying the differences and potentials between the specialisations in question. Based on the initial design proposals, it was clear how the craftsperson’s previous experiences within crafts practice quickly led to the identification of realisable solutions based on experimental setups and aesthetic solutions and, at the same time, was able to foresee possible complications.
Monoclonal War: The Antibody Arsenal and Targets for Expanded Application

Advancements in sequencing and screening technology have made monoclonal antibodies more accessible, cost-effective, and precise. These drugs effectively target pathogens and cancer cells and even regulate metabolic pathways by focusing on specific intermediates. Monoclonal antibodies play a key role in mitigating a rise in occupation-related cancers, neurodegenerative disorders, and multidrug-resistant organisms. Here, we review the origins, mechanisms, and applications of this important drug class and explore future avenues for research.
Efficacy of Dexamethasone Diluted Saline Irrigant on Postoperative Sequelae in Patients Undergoing Lower Third Molar Surgery: A Prospective Clinical Study

Background Third molar impaction surgery is one of the most common yet challenging procedures done as a part of minor oral surgery. Years of research and improvisation of techniques have been done, yet there are still a lot of postoperative sequelae after surgical removal of the impacted tooth. In our study, we have compared the efficacy of dexamethasone diluted saline solution over plain saline solution used as an irrigant in the reduction of postoperative sequelae for lower third molar surgery. Aim The aim of the study was to evaluate the efficacy of dexamethasone diluted saline solution over plain saline solution in the reduction of postoperative sequelae for lower third molar surgery. Materials and methods The research was conducted at Saveetha Dental College and Hospital in the Department of Oral and Maxillofacial Surgery. The study consisted of 48 individuals, 24 of whom had dexamethasone saline as an irrigant (8 mg of dexamethasone was diluted in 100 ml of plain saline) (Group 1), and 24 in whom plain saline was used as an irrigant (Group 2) in the lower third molar surgery. Patients were evaluated postoperatively for pain and swelling. The postoperative swelling was measured on postoperative day two and day seven. Postoperative pain was measured on day two, day four, and day seven after surgery using a visual analog scale. Data were analyzed using SPSS (IBM Corp., Armonk, NY) with P-values less than 0.05 considered statistically significant. The statistical test used to compare the outcomes between the two groups was the independent samples t-test. Results It was found that study participants in the dexamethasone saline irrigation group reported statistically significantly lesser pain than participants receiving plain saline irrigation on day two (P = 0.001), day four (P = 0.001), and day seven (P = 0.001), respectively. Also, there was a reduction in swelling among participants in the dexamethasone saline irrigation group when compared to the normal saline irrigation group, which was statistically significant (P = 0.001) on day two, while the postoperative swelling was not statistically significant on day seven (P = 0.08) between the two study groups. Conclusion Based on the results obtained, it can be concluded that dexamethasone saline solution (8 mg/100 mL) was more effective as an irrigant in reducing the postoperative sequelae than regular saline solution in the lower third molar surgery.