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Interpreting high-dimensional data from molecular dynamics simulations is a persistent challenge. In this paper, we show that for a small peptide, deca-alanine, metastable states can be identified through a neural net based on structural information alone. While processing molecular dynamics data, dimensionality reduction is a necessary step that projects high-dimensional data onto a low-dimensional representation that, ideally, captures the conformational changes in the underlying data. Conventional methods make use of the temporal information contained in trajectories generated through integrating the equations of motion, which forgoes more efficient sampling schemes. We demonstrate that EncoderMap, an autoencoder architecture with an additional distance metric, can find a suitable low-dimensional representation to identify long-lived molecular conformations using exclusively structural information. For deca-alanine, which exhibits several helix-forming pathways, we show that this approach allows us to combine simulations with different biasing forces and yields representations comparable in quality to other established methods. Our results contribute to computational strategies for the rapid automatic exploration of the configuration space of peptides and proteins. [ABSTRACT FROM AUTHOR]

AbstractMorels (Morchella sp. pl.) are valuable mushrooms, and their applications in the pharmaceutical and food industries has steadily increased in China.White mold disease is a common and severe disease in the culturing of morels, which is mainly manifested as white villous mycelial infection on the fruiting bodies of these mushrooms. However, the causal agent is not yet known. Therefore, this study aims to identify, at the species level, the causal pathogen of this disease via morphological and molecular methods and then to confirm its pathogenicity through Koch’s postulates. The pathogen was identified as Neonectria candida. Healthy ascocarps were inoculated with N. candida, which produced the initial disease symptoms with white mold appearing at the inoculation sites. The same pathogen was then isolated again from diseased ascocarps. To our knowledge, this is the first report of Morchella importuna ascocarps with white mold disease caused by N. candida in China. Moreover, this report will inform the establishment of sustainable management strategies for white mold disease in morels. [ABSTRACT FROM AUTHOR]

Background: Uricase is a bio-drug used to reduce urate accumulation in gout disease. Thus, there is a continuous demand for screening soil samples derived from a variety of different sources in order to isolate a strain that possesses a high potential for producing uricase. Methods: Streptomyces sp. strain NEAE-5 demonstrated a significant capacity for uricase production was identified based on the physiological, morphological and biochemical characteristics, as well as 16S rDNA sequencing analysis. Using a Plackett–Burman statistical design, the impact of eighteen process factors on uricase production by Streptomyces griseorubens strain NEAE-5 was investigated. Using central composite design, the most important variables that had a favourable positive impact on uricase production by Streptomyces griseorubens strain NEAE-5 were further optimized. Results: It is clear that the morphological and chemotaxonomic features of Streptomyces sp. strain NEAE-5 are typical for the Streptomyces genus. Phylogenetic analysis indicated that Streptomyces sp. strain NEAE-5 belongs to the genus Streptomyces and closely related to Streptomyces griseorubens which it has a 95–96% identity in 16S rDNA gene sequencing. Accordingly, the strain is proposed to be identified as Streptomyces griseorubens strain NEAE-5. The three factors that had the significant positive impacts on uricase production were uric acid, hypoxanthine, and yeast extract. As a result, the best conditions for achieving the highest experimental uricase production by Streptomyces griseorubens strain NEAE-5 after central composite design were (g/L): uric acid 6.96, glycerol 5, hypoxanthine 5.51, MgSO4.7H2O 0.1, KNO3 2, CaCl2 0.5, K2HPO4 0.5, NaCl 0.5, yeast extract 1.08. In addition, the period of incubation is seven days, pH 7.5 and 37 °C with an inoculum size of 2 mL (105 cfu/mL) /100 mL medium. Conclusions: After optimization, the obtained uricase activity was 120.35 U/mL, indicating that the Streptomyces griseorubens strain NEAE-5 is a potent uricase producer and that the statistical approach used for optimization was appropriate. [ABSTRACT FROM AUTHOR]

In order to understand the types of parasitic fungi in cicadas, we isolated and identified entomophytic fungi in cicadas, then observed their main characteristics, sequenced and analyzed ITS sequences of the strains. Several pathogenic fungi were isolated and purified from the cicada infected with fungi, named Y1, Y3, and Y6, and their morphology was observed, ribosomal DNA sequencing and analysis were performed to identify and analyze them. Morphologically, it can be inferred that the colonies of fungi Y1 and Y3 are yellow brown in color, with white hyphae and yellow brown spores. They are round and uniform in size. After ITS sequence alignment and combined with morphological characteristics, they belong to the Scopulariopsis alboflavescen genus of fungi. The color of Y6 colony is white, and the hyphae on PDA medium are short and dense, growing slowly. When observed under a microscope, the hyphae are colorless, and the spores are round or elliptical, with uniform sizes. After ITS sequence alignment and combined with morphological characteristics, it is classified as a Scoporariopsis fungus. [ABSTRACT FROM AUTHOR]

Aims To explore the views and attitudes of professionals, patients and the public to a role for community pharmacists in the identification of alcohol-related liver disease (ArLD). Methods Semi-structured interviews were conducted with a purposive sample of patients with ArLD, members of the public, pharmacy staff, and clinicians managing patients with ArLD across the Wessex region of south England. The interviews explored experiences of alcohol, ArLD and health advice in pharmacies and elicited views of what a pharmacist role in identifying ArLD could entail and factors influencing this. Transcripts were analysed using reflexive thematic analysis. Results Twenty-six participants were interviewed and three themes were generated: (i) acknowledging, seeking help and engaging with a hidden problem; (ii) professional roles, boundaries and attributes; (iii) communication, relationships, collaboration and support. Participants reported key challenges to identifying people at-risk of ArLD. Offering testing for ArLD was perceived to motivate engagement but there were concerns about pharmacists performing this. A role was mostly seen to be finding people at-risk and engaging them with further care such as referral to liver services. This was perceived to require developing interprofessional collaborations, remuneration and training for pharmacy staff, and community-based liver testing. Conclusions Professionals, patient and public participants recognized a role for pharmacists in the identification of ArLD. This was envisaged to incorporate educating pharmacy users about ArLD risk, and identifying and directly engaging those at-risk with liver and support services through development of interprofessional collaborations. The findings of this study support and can inform future work to develop this role. [ABSTRACT FROM AUTHOR]

BACKGROUND: Spanish-speaking trauma and burn patients have unique needs in their postdischarge care navigation. The confluence of limited English proficiency, injury recovery, mental health, socioeconomic disadvantages, and acute stressors after hospital admission converge to enhance patients' vulnerability, but their specific needs and means of meeting these needs have not been well described. STUDY DESIGN: This prospective, cross-sectional survey study describes the results of a multi-institutional initiative devised to help Spanish-speaking trauma and burn patients in their care navigation after hospitalization. The pathway consisted of informational resources, intake and follow-up surveys, and multiple points of contact with a community health worker who aids in accessing community resources and navigating the healthcare system. RESULTS: From January 2022 to November 2023, there were 114 patients identified as eligible for the Non-English-Speaking Trauma Survivors pathway. Of these, 80 (70.2%) were reachable and consented to participate, and 68 were approached in person during their initial hospitalization. After initial screening, 60 (75.0%) eligible patients had a mental health, social services, or other need identified via our survey instrument. During the initial consultation with the community health worker, 48 of 60 patients with any identified need were connected to a resource (80%). Food support was the most prevalent need (46, 57.5%). More patients were connected to mental health resources (16) than reported need in this domain (7). CONCLUSIONS: The Non-English-Speaking Trauma Survivors pathway identified the specific needs of Spanishspeaking trauma and burn patients in their recovery, notably food, transportation, and utilities. The pathway also addressed disparities in postdischarge care by connecting patients with community resources, with particular improvement in access to mental healthcare. [ABSTRACT FROM AUTHOR]

Objective: To use a standardised reporting tool to identify potential eligible candidates for cochlear implant (CI) referral and quantify the proportion of adults who had a CI referral discussion after presenting with an audiogram within United Kingdom (UK) audiometric criteria. Design: Retrospective multicentre 6-month audit of Audiology clinic databases. Study sample: A total of 810 adults from five geographically diverse UK Audiology sites. Results: Data were collected in late 2019 after UK CI audiometric candidacy criteria changed; one site collected only 3 months of data. The proportion of potential eligible adults (based only on audiometry) considered for CI referral was 64% (521 out of 810) and varied by site (from 50% to 83%). About 24% of patients (123 out of 521) declined CI referral; this also varied across sites (12–45%). The median age of patients where CI referral was not considered was 80 years – significantly higher than the group where CI referral was considered (73 years). Conclusions: CI referral is dependent on where adults live, and how old they are. Older adults are significantly less likely to be considered for CI referral by Audiologists. Audiology clinics need more support to empower staff to talk to patients about CI referral. [ABSTRACT FROM AUTHOR]

Motor deficits typical of Parkinson's disease (PD), such as gait and balance disturbances, tremor, reduced arm swing and finger movement, and voice and breathing changes, are believed to manifest several years prior to clinical diagnosis. Here we describe the evidence for the presence and progression of motor deficits in this pre-diagnostic phase in order to provide suggestions for the design of future observational studies for an effective, quantitatively oriented investigation. On the one hand, these future studies must detect these motor deficits in as large (potentially, population-based) cohorts as possible with high sensitivity and specificity. On the other hand, they must describe the progression of these motor deficits in the pre-diagnostic phase as accurately as possible, to support the testing of the effect of pharmacological and non-pharmacological interventions. Digital technologies and artificial intelligence can substantially accelerate this process. [ABSTRACT FROM AUTHOR]

Daqu, a crucial fermentation starter in the production of various Chinese fermented foods, plays a pivotal role in shaping complex enzyme profiles and diverse flavour precursors. This review aims to elucidate the microbial communities within Daqu, focusing on their functionalities in the context of flavour development. We delve into the detection methods of microorganisms and flavour substances in Daqu, employing advanced technologies including high-performance liquid chromatography, gas chromatography, pseudo-targeted metabolomics, and headspace solid-phase microextraction-gas chromatography-mass spectrometry. This review explores high throughput sequencing technologies, including pyrosequencing, clonal library sequencing, metaproteomic, and metagenomics, to gain a comprehensive understanding of the intricate microbial dynamics. Additionally, we discuss the metabolic pathways involved in flavour substance production within Daqu. By synthesizing information on Daqu types, microorganisms present, detection methodologies, and flavour substance metabolic pathways, this review contributes to a deeper comprehension of the intricate processes underpinning the Flavors of Chinese fermented foods. [Display omitted] • Crucial role of Daqu in enzyme profiles and flavor precursors in Chinese foods. • Microbial communities in Daqu and their role in flavor development. • High throughput sequencing: pyrosequencing, clonal library sequencing, metaproteomic, metagenomics. • Comprehensive synthesis of Daqu types, microorganisms, and metabolic pathways. [ABSTRACT FROM AUTHOR]

An efficient acidic natural deep eutectic solvent (choline chloride-acetic acid, Chcl-AA) was screened out and subsequently combined with ultrasound treatment to recover seabuckthorn leaf phenolics (SLP), and the Plackett–Burman and Box-Behnken designs were used to optimize the process parameters. The optimal parameters were water content of NADES 30%, solvent to solid ratio 32 mL/g, extraction time 14 min, extraction temperature 40°C, ultrasonic power 400 W, and ultrasonic duty cycle 75%. The values of total phenolic content (TPC) and total flavonoid content (TFC) under these conditions were 99.65 ± 2.49 milligram gallic acid equivalent per gram of dry weight (mg GAE/g DW) and 52.02 ± 1.21 milligram rutin equivalent per gram of dry weight (mg RE/g DW), respectively. Twenty-five phenolics were initially identified from SLP by ultra-performance liquid chromatography coupled with quadrupole-time of flight mass spectrometry (UPLC-Q-TOF/MS), among which hydrolyzable tannins, isorhamnetin derivatives, and quercetin derivatives are the main constituents. The SLP extract was further evaluated as to its ability to inhibit metabolic enzymes, i.e., α-glucosidase, α-amylase, pancreatic lipase, cholesterol esterase, xanthine oxidase, and angiotensin-converting enzyme. SLP exhibited significant inhibition of α-glucosidase (IC50 = 3.31 μg/mL), pancreatic lipase (IC50 = 57.62 μg/mL), and angiotensin-converting enzyme (IC50 = 63.13 μg/mL). Additionally, the compounds extracted using Chcl-AA exhibited superior bioactivity when compared to those using conventional green solvents, i.e., ethanol and water. These results provide a valuable technical buttress for the efficient extraction of SLP and their further application and research in functional foods. [ABSTRACT FROM AUTHOR]

In this study, one of the most frequently used polymeric materials in fused deposition modeling (FDM) acrylonitrile butadiene styrene (ABS) is reinforced with different amount of carbon nanotubes (CNTs). Thermogravimetric analysis and differential scanning calorimetry analysis are applied to examine thermal degradation behavior of produced nanocomposite filaments. Specimens are manufactured by fused deposition modeling by using produced nanocomposite filaments. Tensile, creep and viscoelastic-viscoplastic behaviors of FDM-printed nanocomposite samples are investigated by conducting tensile, creep and loading–unloading tests under different strain rates and strain levels. Morphology of 3D printed samples is examined through scanning electron microscopy. Void densities which plays important role in mechanical behavior of additively manufactured samples are determined via ImageJ and CNT reinforcement on void densities are investigated. Data obtained from tests are used in system identification process, and multi-input–single-output model structures are proposed for the prediction of tensile, creep and recovery behaviors of 3D printed nanocomposite materials. [ABSTRACT FROM AUTHOR]

Survivors of child sex trafficking (SCST) experience high rates of adverse health outcomes. Amidst the duration of their victimization, survivors regularly seek healthcare yet fail to be identified. This study sought to utilize artificial intelligence (AI) to identify SCST and describe the elements of their healthcare presentation. An AI-supported keyword search was conducted to identify SCST within the electronic medical records (EMR) of ∼1.5 million patients at a large midwestern pediatric hospital. Descriptive analyses were used to evaluate associated diagnoses and clinical presentation. A sex trafficking-related keyword was identified in.18% of patient charts. Among this cohort, the most common associated diagnostic codes were for Confirmed Sexual/Physical Assault; Trauma and Stress-Related Disorders; Depressive Disorders; Anxiety Disorders; and Suicidal Ideation. Our findings are consistent with the myriad of known adverse physical and psychological outcomes among SCST and illuminate the future potential of AI technology to improve screening and research efforts surrounding all aspects of this vulnerable population. [ABSTRACT FROM AUTHOR]

Considering the challenges of low multi‐object detection accuracy and difficulty in identifying small targets caused by challenging environmental conditions including irregular lighting patterns and ambient noise levels in the mining environment with autonomous electric locomotives. A new network model based on SOD−YOLOv5s−4L has been proposed to detect multi‐objects for autonomous electric locomotives in underground coal mines. Improvements have been applied in YOLOv5s to construct the SOD−YOLOv5s−4L model, by introducing the SIoU loss function to address the mismatch between real and predicted bounding box directions, facilitating the model to learn target position information more efficiently. This research introduces a decoupled head to enhance feature fusion and improve the positioning precision of the network model, enabling rapid capture of multi‐scale target features. Furthermore, the detection capability of the model has been increased by introducing the small target detection layer which is developed by increasing the number of detection layers from three to four. The experimental results on multiple object detection dataset show that the proposed model achieves significant improvement in mean average precision (mAP) of almost 98% for various types of targets and an average precision (AP) of nearly 99% for small targets on the other hand it achieves 5.19% (mAP) and 9.79% (AP) compared to the YOLOv5s model. Furthermore, comparative analysis with other models like YOLOv7 and YOLOv8 shows that the proposed model has superior performance in terms of object detection. [ABSTRACT FROM AUTHOR]

Frozen shoulder (FS) is a common shoulder condition accompanied by shoulder pain and a loss of shoulder range of motion (ROM). The typical clinical assessment tools such as questionnaires and ROM measurement are susceptible to subjectivity and individual bias. To provide an objective evaluation for clinical assessment, this study proposes an inertial measurement unit (IMU)-based identification system to automatically identify shoulder tasks whether performed by healthy subjects or FS patients. Two groups of features (time-domain statistical features and kinematic features), seven machine learning (ML) techniques, and two deep learning (DL) models are applied in the proposed identification system. For the experiments, 24 FS patients and 20 healthy subjects were recruited to perform five daily shoulder tasks with two IMUs attached to the arm and the wrist. The results demonstrate that the proposed system using deep learning presented the best identification performance using all features. The convolutional neural network achieved the best identification accuracy of 88.26%, and the multilayer perceptron obtained the best F1 score of 89.23%. Further analysis revealed that the identification performance based on wrist features had a higher accuracy compared to that based on arm features. The system's performance using time-domain statistical features has better discriminability in terms of identifying FS compared to using kinematic features. We demonstrate that the implementation of the IMU-based identification system using ML is feasible for FS assessment in clinical practice. [ABSTRACT FROM AUTHOR]

Kidney stones are the most common urinary system diseases, and early identification is of great significance. The purpose of this study was to use routine urine and blood detection indices to build a deep learning (DL) model to identify the presence of kidney stones in the early stage. A retrospective analysis was conducted on patients with kidney stones who were treated at West China Hospital of Sichuan University from January 2020 to June 2023. A total of 1130 individuals presenting with kidney stones and 1230 healthy subjects were enrolled. The first blood and urine laboratory data of participants at our hospital were collected, and the data were divided into a training dataset (80%) and a verification dataset (20%). Additionally, a long short-term memory (LSTM)-based adaptive feature weighting model was trained for the early identification of kidney stones, and the results were compared with those of other models. The performance of the model was evaluated by the area under the subject working characteristic curve (AUC). The important predictive factors are determined by ranking the characteristic importance of the predictive factors. A total of 17 variables were screened; among the top 4 characteristics according to the weight coefficient in this model, urine WBC, urine occult blood, qualitative urinary protein, and microcyte percentage had high predictive value for kidney stones in patients. The accuracy of the kidney stone (KS-LSTM) learning model was 89.5%, and the AUC was 0.95. Compared with other models, it has better performance. The results show that the KS-LSTM model based on routine urine and blood tests can accurately identify the presence of kidney stones. And provide valuable assistance for clinicians to identify kidney stones in the early stage. [ABSTRACT FROM AUTHOR]

AbstractThis paper develops permutation versions of identification-robust tests in linear instrumental variables regression. Unlike the existing randomization and rank-based tests in which independence between the instruments and the error terms is assumed, the permutation Anderson-Rubin (AR), Lagrange Multiplier (LM) and Conditional Likelihood Ratio (CLR) tests are asymptotically similar and robust to conditional heteroskedasticity under standard exclusion restriction i.e. the orthogonality between the instruments and the error terms. Moreover, when the instruments are independent of the structural error term, the permutation AR tests are exact, hence robust to heavy tails. As such, these tests share the strengths of the rank-based tests and the wild bootstrap AR tests. Numerical illustrations corroborate the theoretical results. [ABSTRACT FROM AUTHOR]

Detection of underground natural gas pipeline micro-leakage based on unmanned aerial vehicle (UAV) hyperspectral remote sensing and GIS. Hyperspectral images can indirectly detect underground natural gas pipeline micro-leakage through spectral and spatial variation characteristics of surface vegetation. However, most of existing studies were based on ground-mounted platforms, which could only perform small-range single-point detection and might occur misidentifications. UAV hyperspectral remote sensing can allow wide-range detection of surface vegetation. Moreover, underground pipeline distribution GIS data can provide prior knowledge about leakage points to exclude misidentifications. Therefore, a natural gas pipeline micro-leakage experiment was set up. UAV hyperspectral images of grasslands and pipeline distribution vector data were obtained, which led to a proposed new wide-range multi-points detection methodology of underground natural gas micro-leakage. Firstly, the vegetation identification index (WVI) $\left({{R_{470}} + {R_{674}}} \right)/\left({{R_{555}} + {R_{750}}} \right)$R470+R674/R555+R750 was designed based on WOA–VMD (whale optimization algorithm – variational modal decomposition) to segment and extract the vegetation stress zones. Then, UAV- and GIS-based natural gas micro-leakage vegetation stress identification model was constructed to obtain the leak points of natural gas micro-leakage. Finally, the recognition ability was evaluated by comparing with three stress vegetation identification indices proposed in previous studies. The result showed that there was no missing or false detection in identification results; the identification and positioning effect was better than other indices, which could meet the practical application requirements. [ABSTRACT FROM AUTHOR]

The paper pursues the development of a novel methodology for the rapid identification of the diffuso-mechanical properties of polymer materials based on the employment of plates subject to asymmetric moisture concentration fields. The study is carried out on epoxy plate samples equipped with a thin aluminium foil on a surface exposed to the environment to promote asymmetric moisture absorption. The asymmetric moisture fields promote deformations of the plate. Mass gain and plate curvatures are measured as a function of time during conditioning. By using a weakly coupled diffuso-mechanical model: 1D Fick's diffusion model and 2D plane stress hygroelastic model the diffuso-mechanical properties of the material can be then identified. Due to the chosen size of the experimental samples the present study allows the identification of the coefficient of moisture expansion of the epoxy material. For the material under study, the following values can be identified for saturation mass gain, water diffusivity and coefficient of moisture expansion respectively: 1.67%, 0.025 mm2.h−1, 0.1628. [ABSTRACT FROM AUTHOR]

Background: Plastids originated from an ancient endosymbiotic event and evolved into the photosynthetic organelles in plant cells. They absorb light energy and carbon dioxide, converting them into chemical energy and oxygen, which are crucial for plant development and adaptation. However, little is known about the plastid genome to light adaptation. Petrocosmea, a member of the Gesneriaceae family, comprises approximately 70 species with diverse light environment, serve as an ideal subject for studying plastomes adapt to light. Results: In this study, we selected ten representative species of Petrocosmea from diverse light environments, assembled their plastid genomes, and conducted a comparative genomic analysis. We found that the plastid genome of Petrocosmea is highly conserved in both structure and gene content. The phylogenetic relationships reconstructed based on the plastid genes were divided into five clades, which is consistent with the results of previous studies. The vast majority of plastid protein-coding genes were under purifying selection, with only the rps8 and rps16 genes identified under positive selection in different light environments. Notably, significant differences of evolutionary rate were observed in NADH dehydrogenase, ATPase ribosome, and RNA polymerase between Clade A and the other clades. Additionally, we identified ycf1 and several intergenic regions (trnH-psbA, trnK-rps16, rpoB-trnC, petA-psbJ, ccsA-trnL, rps16-trnQ, and trnS-trnG) as candidate barcodes for this emerging ornamental horticulture. Conclusion: We newly assembled ten plastid genomes of Petrocosmea and identified several hypervariable regions, providing genetic resources and candidate markers for this promising emerging ornamental horticulture. Furthermore, our study suggested that rps8 and rps16 were under positive selection and that the evolutionary patterns of NADH dehydrogenase, ATPase ribosome, and RNA polymerase were related to the diversity light environment in Petrocosmea. This revealed an evolutionary scenario for light adaptation of the plastid genome in plants. [ABSTRACT FROM AUTHOR]

Culicoides, among the tiniest and most abundant hematophagous insects globally, serve as vectors for a variety of pathogens such as viruses, bacteria, parasites, protozoa, and nematodes. This study aimed to identify Culicoides species and assess their spatial distribution and seasonal occurrence in selected districts of the Central, South, and West Gondar zones, Northwest Ethiopia. A cross-sectional study was conducted between January to July 2023. A total of 44 UV light- onderstepoort traps were deployed in the study districts near specific areas. The traps were operational from dusk (6:00 PM) until dawn (6:00 AM) and were suspended at a height of 1.5 to 2 m above the ground. Poisson regression was used to assess associations, the Shannon diversity index to measure diversity, and QGIS 3.22.6 to create maps. In this study, 8,857 Culicoides were captured across the 44 trapping sites. Of the total flies captured flies, 8,838 were identified as belonging to 12 distinct species, while the classification of the remaining 19 flies remained unclear. Notably, C. kingi (54.01%) was the most prevalent species, followed by C. imicola (44.55%). The abundance of Culicoides observed from January to late April (3505) was significantly lower compared to the wet season (5355), with a marked increase in the capture of C. kingi (2499) from May to late July. A statistically significant association (p < 0.05) was observed between the occurrence of Culicoides and factors such as district, sampling point, and season. Spatial analysis revealed that C. kingi had a broader range of suitability than other Culicoides species, with high suitability observed in East Dembia. The diversity index analysis indicated that Culicoides species diversity was higher in samples from animal pens (H = 0.73) and during the wet season (H = 0.75). Additionally, this study documented the presence of eight Culicoides species namely C. corsicus, C. kibunensis, C. reioxi, C. kiouxi, C. saharienines, C. desertorum, C. reithi, and C. festivipennis, which have not been previously documented in Ethiopia. In conclusion, the study highlighted that the occurrence of Culicoides species was higher in East Dembia, with moderate presence in Wegera and West Armacho. Further research is needed to assess the impact of various Culicoides species on animal and human health, as well as their economic implications, and to develop corresponding control strategies based on these findings. [ABSTRACT FROM AUTHOR]

Identifying unknown deceased individuals, especially those in advanced stages of decomposition, dismemberment, or burning, is a major medico-legal challenge. Forensic anthropologists play a crucial role in these cases due to the numerous characteristics that can be derived from bone remains. Their methods help evaluate the biological profile and individual characteristics, narrowing potential matches. This research investigates the identification methods used by forensic anthropologists in Medicolegal Institutes and Medical Examiner’s Offices in Brazil and the USA. Case reports from forensic anthropology institutes in Vitória, Rio de Janeiro, Porto Velho (Brazil), and New York City (USA) were analysed. In resolved cases, details such as the biological profile, trauma, decomposition extent, and individualization markers were documented. Statistical tests evaluated the association between these variables and identification outcomes. Conventional identification methods included dental analysis, DNA testing, and fingerprint analysis. Additionally, Bayesian methods, visual identification, prosthetics, and X-ray comparison proved useful. This study highlights that forensic anthropologists can employ a variety of methodologies beyond standard practices, enhancing the identification process in complex cases. [ABSTRACT FROM AUTHOR]

ABSTRACT Aims Design Methods Results Conclusions Impact Patient or Public Contribution This study aimed to analyse and determine the risk factors of disease aggravation faced by older patients with non‐communicable diseases (NCDs) and their interwoven correlations.We employed a descriptive and cross‐sectional study, which followed the STROBE guidelines for reporting.We conducted a semi‐structured in‐depth interview with 26 older patients with NCDs from a hospital in Qingdao, China between July and August 2022 on the basis of the literature review. Then, we analysed data using the directed content analysis and determined risk factors through a focus group discussion and the Delphi consultation. Afterward, we combined interpretive structural modelling and hierarchical holographic modelling to construct a hierarchical structure model and drew relationship framework diagrams to exhibit diversified risk factors and complex interwoven correlations.We identified 30 risk factors from individual, interpersonal, organisational, community and policy levels. The hierarchical structure model constructed by interpretive structural modelling demonstrated a four‐layer structure, and the individual and interpersonal levels were at the highest layer. The relationship framework diagrams demonstrated the identification process of risk factors and interwoven correlations at individual and organisational levels.Risk factors causing disease aggravation amongst older patients with NCDs are diverse. To delay the progression of NCDs, we should comprehensively explore risk factors, interpret the root causes and effects of risks from multiple perspectives and consider the interaction amongst multi‐level risk factors to develop precise measures related to risk control.Controlling risk factors is an effective measure to postpone disease aggravation. Through this study, we provide a scientific and comprehensive basis for clinical risk screening so that healthcare providers can sense potential risk factors for disease aggravation in older patients' surroundings and formulate targeted nursing measures according to the risk factors faced by different patients.Patients participated in interviews to supplement risk factors included in our study. Experts provided opinions on the inclusion, exclusion and modification of risk factors. [ABSTRACT FROM AUTHOR]

Culicoides, among the tiniest and most abundant hematophagous insects globally, serve as vectors for a variety of pathogens such as viruses, bacteria, parasites, protozoa, and nematodes. This study aimed to identify Culicoides species and assess their spatial distribution and seasonal occurrence in selected districts of the Central, South, and West Gondar zones, Northwest Ethiopia. A cross-sectional study was conducted between January to July 2023. A total of 44 UV light- onderstepoort traps were deployed in the study districts near specific areas. The traps were operational from dusk (6:00 PM) until dawn (6:00 AM) and were suspended at a height of 1.5 to 2 m above the ground. Poisson regression was used to assess associations, the Shannon diversity index to measure diversity, and QGIS 3.22.6 to create maps. In this study, 8,857 Culicoides were captured across the 44 trapping sites. Of the total flies captured flies, 8,838 were identified as belonging to 12 distinct species, while the classification of the remaining 19 flies remained unclear. Notably, C. kingi (54.01%) was the most prevalent species, followed by C. imicola (44.55%). The abundance of Culicoides observed from January to late April (3505) was significantly lower compared to the wet season (5355), with a marked increase in the capture of C. kingi (2499) from May to late July. A statistically significant association (p < 0.05) was observed between the occurrence of Culicoides and factors such as district, sampling point, and season. Spatial analysis revealed that C. kingi had a broader range of suitability than other Culicoides species, with high suitability observed in East Dembia. The diversity index analysis indicated that Culicoides species diversity was higher in samples from animal pens (H = 0.73) and during the wet season (H = 0.75). Additionally, this study documented the presence of eight Culicoides species namely C. corsicus, C. kibunensis, C. reioxi, C. kiouxi, C. saharienines, C. desertorum, C. reithi, and C. festivipennis, which have not been previously documented in Ethiopia. In conclusion, the study highlighted that the occurrence of Culicoides species was higher in East Dembia, with moderate presence in Wegera and West Armacho. Further research is needed to assess the impact of various Culicoides species on animal and human health, as well as their economic implications, and to develop corresponding control strategies based on these findings. [ABSTRACT FROM AUTHOR]

Summary: The ipê trees belonging to the genus Handroanthus are among the most exploited species in the Amazon Forest. However, limitations in the wood identification processes can lead to an overexploitation of a single species. We compare, macroscopically, the wood anatomy of five Amazon Handroanthus species (H. barbatus , H. capitatus , H. impetiginosus , H. incanus and H. serratifolius –Bignoniaceae). Except for H. barbatus the species are trees over 20 m tall and are used commercially. We compared leaf morphology of the two most commercially used species (H. impetiginosus and H. serratifolius), aiming to separate them in the field with identification keys. For wood macroscopical analyses, 55 samples were used; the specimens were obtained in the field and from wood collections. The dichotomous key, preferable to be used in a laboratory, enables the distinction of the five species. However, the use of this key requires more knowledge about wood anatomy, since it was necessary to use more quantitative characteristics, due to the great intraspecific variation in Handroanthus woods, also reflected in the PCA (principal components analysis) and grouping analysis. To identify the plant species H. impetiginosus and H. serratifolius , the use of axial parenchyma type and vessel characteristics were important distinguishing factors, while in leaves, the most significant features were characteristics such as leaf margin, trichomes and domatia. In addition, by focusing on these key features, a multiple access identification key was created, which simplified the identification by reducing the number of characteristics necessary for the identification, facilitating its use in the field. [ABSTRACT FROM AUTHOR]

Tamaricaceae comprises about 120 species and has a long evolutionary history, Tamarix Linn accounts for approximately 75% of the total species in this family. It is the most widely distributed and diverse genus in the family. They have important ecological significance for transforming deserts and improving climate conditions. However, Tamarix is the most poorly classified genera among flowering plants owing to its large variability and high susceptibility to interspecific hybridization. In this study, the complete chloroplast genomes of three Tamarix species and one draft chloroplast genome were obtained in this study. Combined with eight chloroplast genomes deposited in GenBank, complete chloroplast sequences of 12 Tamarix species were used for further analysis. There are 176 non‐SSR‐related indels and 681 non‐indel‐related SSRs in the 12 Tamarix chloroplast genomes. The mononucleotide SSRs are the most prevalent among all types of SSRs. The mVISTA results indicate high sequence similarities across the chloroplast genome, suggesting that the chloroplast genomes are highly conserved, except for sample Tamarix androssowii (ENC850343). The IR regions and the coding regions are more conserved than the single‐copy and noncoding regions. The trnF‐ndhJ, ndhC‐trnM‐CAU, ycf1, and trnL‐UAG‐ndhF regions are the most variable and have higher variability than those of the universal DNA markers. Finally, the first phylogenetic tree of Tamaricaceae was constructed which confirmed the monophyly of Tamarix in Tamaricaceae. The first phylogenetic tree of Tamarix was based on the complete chloroplast genome to date, the changes in branch length and support rate can potentially help us clarify the phylogenetic relationships of Tamarix. All the obtained genetic resources will facilitate future studies in population genetics, species identification, and conservation biology of Tamarix. [ABSTRACT FROM AUTHOR]

This study aimed to identify the primary pathogenic bacteria responsible for the mortality of the Chinese giant salamander (Andriasd davidianus). A pathogenic bacterium was isolated from a diseased Chinese giant salamander exhibiting typical symptoms under aseptic conditions and then identified by morphological examinations, biochemical analysis, and the sequence analysis of bacterial 16S rRNA. Artificial infection testing was then conducted to determine the pathogenicity of the isolated bacteria strain. Drug susceptibility tests were conducted using the agar diffusion method. The isolated pathogenic bacteria, named DN-2, was successfully identified as Acinetobacter lwoffii. The artificial infection showed that the typical symptoms of the disease could be replicated as the ones originally occurred, and this bacterium exhibited high pathogenicity to the Chinese giant salamander. In the Chinese giant salamander, the median lethal dosage (LD50) of A. lwoffii DN-2 for A. davidianus was determined to be 4.63*104 CFU/g. Drug sensitivity testing showed that these bacteria were highly sensitive to erythromycin, gentamicin, neomycin, streptomycin, midecamycin, ciprofloxacin, piperacillin, florfenicol, doxycycline, carbenicillin, and sulfanilamide. In summary, A. lwoffii was identified as the primary pathogen responsible for the demise of A. davidianus. Our study first presents how these bacteria harm Chinese giant salamanders. [ABSTRACT FROM AUTHOR]

This article addresses the identification of unknown nonlinear continuous‐time systems through a linear time‐varying (LTV) approximation as a starting point. The mathematical form of the nonlinear system is unknown and is reconstructed by use of a well‐designed experiment, followed by LTV and linear parameter‐varying (LPV) estimations, and an integration step. The experiment used allows for a linearization of the unknown nonlinear system around a time‐varying operating point (system trajectory), resulting in an LTV approximation. After estimating the LTV model, an LPV model is identified, where the parameter‐varying (PV) coefficients represent partial derivatives of the unknown nonlinear system evaluated at the trajectory. We demonstrate a structural relation in the LPV model structure that ensures that the LPV coefficient vector is the gradient of the unknown nonlinear system. The nonlinear model of the system is then reconstructed through symbolic integration of the PV coefficients. This identification method enables the estimation of the unknown nonlinear system and its mathematical form using input–output measurements. The article concludes by illustrating the method on simulation examples. [ABSTRACT FROM AUTHOR]

A comprehensive survey of the octopus fauna around the Americas is presented to facilitate and accelerate the assessment of a full understanding of American octopus biodiversity. Brief accounts are provided summarizing research efforts on octopus species taxonomy, diversity and distribution in different regions of North and South America. Octopus americanus and O. insularis are compared and clearly distinguished from each other and from the closely-related European species, O. vulgaris. The use of genus names Paroctopus and Pinnoctopus is clarified. Included is a discussion of the recent application of genus name Paroctopus to warm-temperate and tropical species of small size, along with a cautionary note about species identifications in the light of past errors in misassigning large-to-giant cold-water species to genus Paroctopus. Related to problems with identifying species of Paroctopus, there is an appended note concerning misidentifications and the importance of thorough species descriptions to obtain species information at the levels of both phenotype and genotype. A lectotype is formally designated for Bathypolypus arcticus (Prosch, 1849); and the status of so-called 'Octopus giganteus' is reviewed briefly. A supplementary online database, AmeriCeph, provides basic information about all known octopus species of the Americas, including the institutional location of type material and the identification of voucher specimens and their depositories. DNA sequences registered in this database are not all fully compatible with barcoding standards. However, a subset of DNA sequences conforming to strict barcode identifications is provided in a second supplementary table, providing barcode sequences directly applicable also to improving standards of seafood traceability. This in turn contributes to building sustainability of exploited octopus fisheries stocks and identification of species suitable for aquaculture trials to meet the increasing commercial demand for octopus worldwide. [ABSTRACT FROM AUTHOR]

In‐between groups encompass individuals who simultaneously belong to social categories that are often seen as mutually exclusive in addition to maintaining their distinct group identity. The current paper sheds light on how members of in‐between groups manage their relations within intergroup conflicts. Three studies were conducted among the Druze minority in Israel, a group that is ethnically Arab and shares the Arab identity with the Arab–Palestinian minority in Israel and simultaneously identifies as Israeli. In Study 1 (N = 300), we found that identification as Druze was positively associated with the identification as Arab and Israeli. In Study 2, we examined Druze's endorsement of conflict narratives compared to Jewish‐Israeli and Palestinian citizens (N = 271). While the latter participants endorsed their ingroup narrative more than the outgroup narrative, Druze participants endorsed both narratives equally. In Study 3, we tested Druze's solidarity with the Palestinian minority against the 2018 Nation‐State Law. We found that overall, Druze participants (N = 568) endorsed more inclusive amendments that benefited the Druze and Palestinians than exclusive amendments that benefited the Druze only. In all studies, we tested the role of identification with the rival groups. We discuss these findings and suggest possible underlying mechanisms. [ABSTRACT FROM AUTHOR]

Joint action theorizing implies that any coordinated behaviour that induces co‐representation with a partner should increase social identification, especially when the associated actions require a high degree of coordination and are experienced as being performed effectively. The current research provides a first test of this new theoretical prediction for complementary (rather than synchronous) joint actions. In each of two pre‐registered experiments establishing a novel paradigm, participants performed a digital joystick task with a joint performance goal with three different partners. The task varied in coordination requirements across partners. In Experiment 1, results showed that when task segments were discrete between partners, they identified less as a group than when they had to coordinate their behaviour. Surprisingly, although constant coordination increased co‐representation relative to intermittent coordination, it did not correspondingly increase social identification. However, performance correlated positively with identification; as performance was worse when participants had to coordinate, this may explain the results. Experiment 2 showed that performance is causally linked to identification when coordination is necessary. Taken together, our results suggest that experiencing effective coordination leads to greater social identification. In general, paradigms capable of examining the perceptual and motor aspects of collective behaviour may offer a new perspective on social identification in general and the performance‐identification link in particular. [ABSTRACT FROM AUTHOR]

The failure of bonded composite materials is accompanied by specific failure modes. These are specifically Mode I, Mode II, Mode III, and their combination (so-called mixed mode). These modes depend on the direction and type of loading. The mechanical properties describing the damage initiation and the damage evolution are unique according to the type of adhesive and present mode of failure. However, a few research studies have focused on an adhesive thicknesses greater than 0.2 mm. The main objective of this research is to investigate the mechanical properties of a bonded joint with large adhesive thickness loaded according to Modes I and II. The observed failure parameters, the cohesive and damage parameters, are identified by minimizing the difference between the force–displacement diagram obtained from the experimental data for both Mode I and Mode II. The finite element model is confronted with these parameters and is evaluated based on their agreement. Compared to other studies with a small adhesive layer thickness, the values of failure parameters are lower. The results show that the adhesive thickness has an influence on the values of cohesive and damage parameters and that these parameter values decrease significantly compared to a small adhesive thickness. The obtained parameters can be further used to predict the fracture toughness of other bonded joints loaded in any direction. [ABSTRACT FROM AUTHOR]

The Republic of China period was the most intense and typical period in the history of Chinese clothing development with the westward trend spreading and the east-west blending. From 1912 to 1949 traditional Chinese clothing and modern Western clothing underwent multidimensional influences and integration. This article focuses on studying the changes that occurred in Chinese men's formal attire during this period believing that this period was the starting point of westernization of Chinese men's formal attire and also foreshadowing the beginning of modernization of short clothing fashion. This article analyzes the appearance and image of men's formal attire in the Republic of China. The study focuses on the form of men's formal attire stipulated in the three promulgation laws and regulations of the Republic of China from 1912 to 1936. The research draws on the cognitive psychological model and analyzes the reception recognition and translation of the visual image and clothing vocabulary of men's formal attire in the Republic of China. Using this model for reference this paper analyzes the construction process of the image and significance of the men's dress in the Republic of China especially the changes of aesthetic orientation thinking awareness lifestyle and values reflected in this process. At the same time this article also uses methods such as literature research comparative analysis and cross-research to compare the localization of Japanese men's clothing in the process of Westernization from the perspective of male-specific gender culture reflecting the differences between the two countries in terms of attitudes towards Western culture social status political systems reform ideas and many other aspects. It is found that under the general trend of the westward influence of modern China the three changes in men's dress code in the Republic of China reflected the internal patterns formed by intellectuals'thinking and concepts in the process of understanding Western civilization and Chinese tradition. Through cognitive models men's dress code and masculinity were taken as a sample to reflect the dual attributes of men's image in the Republic of China which took into account both culture and quality and gave birth to a prototype of male aesthetic that met the needs of the social situation at that time. This aesthetic sample not only has the highest ideal of masculinity and masculine image in traditional Chinese culture that gentleness and courteousness make a gentleman but also takes into account the requirements of Western modernist concepts and industrial society for masculinity and masculine image providing a style and template for modern Chinese men's clothing image. [ABSTRACT FROM AUTHOR]

Background: Long specialist outpatient waiting lists are a source of clinical risk. Triage assignment is based on subjective assessment of referrals and fails to account for dynamic changes in disease status while patients await clinical review. Aims: To pilot an innovative triage method using a trifold approach to conduct noninvasive assessment of fibrosis and to determine the feasibility of reflex hepatitis C virus (HCV) polymerase chain reaction (PCR) testing. Methods: A total of 1006 patients awaiting an initial liver clinic appointment at a tertiary Australian hospital were sent a short message service (SMS) requesting a blood test be completed. The first 60 patients received an SMS only, and the subsequent 946 patients also received a phone call from a Liver Care Guide (LCG), a nonclinician employed to increase patient engagement. Liver fibrosis assessment through noninvasive testing was performed using an aspartate aminotransferase to platelet ratio index (APRI) and fibrosis‐4 (FIB4) score. Patients with an APRI ≥1, FIB4 ≥3.25 or positive HCV PCR were retriaged to Category 1. Results: Four hundred ninety (49%) patients completed testing and 40 (4%) were triaged to Category 1. Subanalyses demonstrated increased response rates with LCG input (P = 0.012). Retriaged patients had been on the waitlist for a median of 216 days, exceeding initial category recommendations. Conclusion: This study successfully implemented a semiautomated strategy that prioritises patients with probable advanced liver disease or active HCV, demonstrating enhanced patient engagement with LCG support. It highlights the burden of patients referred for specialist care and the need for innovative strategies for monitoring and objective risk stratification. [ABSTRACT FROM AUTHOR]

The Salix genus of the Salicaceae family has advantages such as rapid initial growth, a high germination rate, and asexual reproduction; therefore, it is used as a short-rotation energy crop for biomass production. The National Institute of Forest Science created new interspecific hybrid cultivars with superior biomass production by artificially interbreeding Salix caprea L. and Salix gracilistyla Miq. Identifying these hybrids during the seedling stage is challenging because their separate reproductive and vegetative growth stages necessitate prolonged observation of their morphological characteristics. Consequently, a reliable identification method is required to overcome these limitations. This study aimed to develop nuclear DNA markers to distinguish between S. caprea, S. gracilistyla, and their interspecific hybrids. An evaluation of 35 nuclear simple-sequence repeat (nSSR) markers in the Salix genus revealed two markers that distinguish these parent species and their hybrids. A sequence analysis confirmed the presence of insertion-deletion (InDel) regions within the nSSR markers that differed between S. caprea and S. gracilistyla. To effectively identify hybrids, a primer set comprising the InDel region, which exhibited only interspecies differences and no intraspecies differences, was developed. The results of this study will facilitate the genetic resource management of interspecific hybrids between S. caprea and S. gracilistyla, thus allowing for early identification and improved management of hybrids. [ABSTRACT FROM AUTHOR]

Pediatricians' use of electronic health record (EHR) systems has become nearly ubiquitous in the United States, yet many systems lack full functionality to deliver effective and efficient pediatric care. This clinical report seeks to provide a compendium of core pediatric functionality of importance to child health care providers that may serve as the focus for EHR developers and clinicians as they evaluate their EHR needs. Also reviewed are important but less critical functions, any of which might be of importance in a specific pediatric context. The major areas described here are immunization management, growth and development, social drivers of health tracking, decision support for orders, patient identification, data normalization, privacy, and system functionality standards in pediatric contexts. [ABSTRACT FROM AUTHOR]

Summary: Monosaccharides such as glucose, fructose, and galactose are the building blocks of oligosaccharides and act as the major energy sources in our body. These three monosaccharides are the most prominent in food processing and widely consumed analytes, found in fruits or milk. Although several analytical methods are available to identify and quantify sugar solutions, their drawbacks urge the search for better possible alternatives. A simple, rapid, and efficient method for identifying monosaccharides (ᴅ‐fructose, ᴅ‐galactose, and ᴅ‐glucose) was investigated using low‐field nuclear magnetic resonance (LF‐NMR), exploring the applicability and reliability of this machine. The transverse (T2) relaxation curve was analysed to distinguish monosaccharides from each other. The increasing monosaccharide concentration in the sugar solution causes leftward shifts in signals, indicating a gradual reduction in the mobility of water molecules. The addition of sugar generated a secondary peak, which assisted in identifying monosaccharides. Notably, fructose exhibited distinct behaviour from that of glucose and galactose. The regression coefficient consistently exceeded 0.98, indicating the reliability of this experiment. LF‐NMR encountered challenges in differentiating stereo‐isomeric glucose and galactose. However, quantification of monosaccharides from known binary mixtures (water and one monosaccharide) is possible by preparing standard curves of different concentrations of sugars. These standard curves can be either T2 or the total surface area of the peaks as a function of sugar concentration. The study concludes that LF‐NMR has potential for the qualitative and quantitative analysis of monosaccharides in pure solutions or powdered samples. It is hoped that the rapid and easy way of monosaccharide identification by simple analysis of peaks obtained from NMR spectra will enhance its accessibility for users. However, it also acknowledges limitations in applying this method to complex systems (mixtures of different sugars in a solution). [ABSTRACT FROM AUTHOR]

The best empirical research in political science clearly defines substantive parameters of interest, presents a set of assumptions that guarantees their identification, and uses an appropriate estimator. We argue for the importance of explicitly integrating rigorous theory into this process and focus on the advantages of doing so. By integrating a theoretical structure into one's empirical strategy, researchers can quantify the effects of competing mechanisms, consider the ex-ante effects of new policies, extrapolate findings to new environments, estimate model-specific theoretical parameters, evaluate the fit of a theoretical model, and test competing models that aim to explain the same phenomena. As a guide to such a methodology, we provide an overview of structural estimation, including formal definitions, implementation suggestions, examples, and comparisons to other methods. [ABSTRACT FROM AUTHOR]

There is heightened awareness that a whole-of-systems approach to perpetrator responses is key to addressing domestic and family violence (DFV). This paper reports on the findings from a scoping review which mapped the international literature on how health professionals identify and respond to perpetrators of DFV within a hospital setting. A comprehensive scoping review methodology was used. The search, spanning January 2010 to January 2022, yielded 12,380 publications from four databases. Eligibility for inclusion included peer-reviewed literature with any reference to inpatient hospital health professionals identifying or responding to perpetrators of DFV. Fourteen articles were included in the final review. The review presents the literature categorized by levels of prevention, from primary, secondary, through to tertiary preventive interventions. An additional category "other practices" is added to capture practices which did not fit into existing levels. Despite glimpses into how health professionals can identify, and respond to perpetrators of DFV, the current knowledge base is sparse. The review did not identify any mandated or formal procedures for identifying and/screening or responding to perpetration of abuse in hospitals. Rather, responses to perpetrators are inconsistent and rely on the motivation, skill, and self-efficacy of health professionals rather than an embedded practice that is driven and informed by hospital policy or procedures. The literature paints a picture of missed opportunities for meaningful work with perpetrators of DFV in a hospital setting and highlights a disjuncture between policy and practice. [ABSTRACT FROM AUTHOR]

We address defining and identifying students with dyslexia within the context of multi-tier systems of support (MTSS). We review proposed definitions of dyslexia, evidence for proposed definitional attributes, and emphasize the role of instructional response in identifying students with dyslexia. We identify dyslexia as individuals with specific deficits in reading and spelling single words combined with inadequate response to evidence-based instruction. We propose a hybrid identification process in which assessment is utilized within school-wide MTSS allowing for integration of routinely collected progress monitoring data as well integrating with more formal diagnostic measures. This proposed "hybrid" method demonstrates strong evidence for valid decision-making and directly informs instruction. We close proposing a revised definition of dyslexia that incorporates these elements. [ABSTRACT FROM AUTHOR]

Cirque landforms, which are distinctive features of cold regions, play a pivotal role in understanding environmental changes and climate research. Currently, machine learning-based automatic glacier recognition models have significantly improved recognition speed. However, these models rely solely on elevation data from Digital Elevation Model (DEM), neglecting other topographic factors that influence cirque identification, such as slope and aspect. This study integrates DEM, slope, and aspect data through pseudo-color fusion technology and utilizes the RetinaNet network to achieve automatic cirque recognition. The pseudo-color fusion image-based recognition model outperforms methods solely relying on DEM, achieving mAP (Intersection over Union: IoU @0.5) of 82.3 %. In practical applications, the pseudo-color fusion image-based recognition model demonstrates balanced performance in identifying different categories of cirques, particularly excelling in recognizing intricate terrains and irregularly shaped cirques. [ABSTRACT FROM AUTHOR]

Precise identification of glioblastoma (GBM) microinfiltration, which is essential for achieving complete resection, remains an enormous challenge in clinical practice. Here, the study demonstrates that Raman spectroscopy effectively identifies GBM microinfiltration with cellular resolution in clinical specimens. The spectral differences between infiltrative lesions and normal brain tissues are attributed to phospholipids, nucleic acids, amino acids, and unsaturated fatty acids. These biochemical metabolites identified by Raman spectroscopy are further confirmed by spatial metabolomics. Based on differential spectra, Raman imaging resolves important morphological information relevant to GBM lesions in a label‐free manner. The area under the receiver operating characteristic curve (AUC) for Raman spectroscopy combined with machine learning in detecting infiltrative lesions exceeds 95%. Most importantly, the cancer cell threshold identified by Raman spectroscopy is as low as 3 human GBM cells per 0.01 mm2. Raman spectroscopy enables the detection of previously undetectable diffusely infiltrative cancer cells, which holds potential value in guiding complete tumor resection in GBM patients. [ABSTRACT FROM AUTHOR]

A data‐driven Buck converter model identification method is proposed to deal with missing (incomplete) outputs, which is robust to the data length and percentage of missing data. A nuclear norm based convex optimization problem instead of linear interpolation, to guarantee the recovered missing data satisfying the potential model structured low‐rank character, is constructed to estimate missing outputs. The alternating direction method of multiplier strategy is used to solve the nuclear norm based convex optimization problem. In this way, the high‐quality missing data can be estimated, even for short data length and high percentage of missing data. Based on the recovered data, the subspace identification method provides accurate estimates of the structure and parameter of the Buck converter synchronously. By applying the proposed method to a Buck converter, experimental results demonstrate its effectiveness. [ABSTRACT FROM AUTHOR]

The traditional Mongolian medicine Erdun-Uril is a conventional combination of 29 herbs commonly used for the treatment of cerebrovascular ailments. It has the effects of reducing inflammation, counteracting oxidative stress, and averting strokes caused by persistent cerebral hypoperfusion. Prior research on Erdun-Uril has predominantly concentrated on its pharmacodynamics and mechanism of action; however, there has been a lack of systematic and comprehensive investigation into its chemical constituents. Therefore, it is crucial to establish an efficient and rapid method for evaluating the chemical constituents of Erdun-Uril. In this study, Erdun-Uril was investigated using UHPLC-Q-Exactive Orbitrap MS combined with parallel reaction monitoring for the first time. Eventually, a total of 237 compounds, including 76 flavonoids, 68 phenolic compounds, 19 alkaloids, 7 amino acids, etc., were identified based on the chromatographic retention time, bibliography data, MS/MS2 information, neutral loss fragments (NLFs), and diagnostic fragment ions (DFIs). And of these, 225 were reported for the first time in this study. This new discovery of these complex components would provide a reliable theoretical basis for the development of pharmacodynamics and quality standards of the Mongolian medicine Erdun-Uril. [ABSTRACT FROM AUTHOR]

Crystal violet dye poses significant health risks to humans, including carcinogenic and mutagenic effects, as well as environmental hazards due to its persistence and toxicity in aquatic ecosystems. This study focuses on the efficient removal of crystal violet dye from aqueous media using novel Co3O4/Co3(BO3)2 nanostructures synthesized via the Pechini sol–gel approach. The nanostructures, which were abbreviated to EN600 and EN800, were fabricated at calcination temperatures of 600 and 800 °C, respectively. X-ray diffraction (XRD) analysis revealed that the synthesized samples have a cubic Co3O4 phase and an orthorhombic Co3(BO3)2 phase, with mean crystal sizes of 43.82 nm and 52.93 nm for EN600 and EN800 samples, respectively. The Brunauer–Emmett–Teller (BET) surface areas of EN600 and EN800 samples were 65.80 and 43.76 m2/g, respectively, indicating a significant surface area available for adsorption. Optimal removal of crystal violet dye was achieved at a temperature of 298 K, a contact time of 70 min, and a pH of 10. The maximum adsorption capacities were found to be 284.09 mg/g for EN600 and 256.41 mg/g for EN800, which are notably higher compared to many conventional adsorbents. The adsorption process followed the pseudo-second-order kinetic model and fitted well with the Langmuir isotherm. The adsorption was exothermic, spontaneous, and physical in nature. Moreover, the adsorbents exhibited excellent reusability, retaining high efficiency after multiple regeneration cycles using 6 mol/L hydrochloric acid. These findings highlight the potential of these Co3O4/Co3(BO3)2 nanostructures as effective and sustainable materials for water purification applications. [ABSTRACT FROM AUTHOR]

Spatial transcriptomics (ST) technologies allow for comprehensive characterization of gene expression patterns in the context of tissue microenvironment. However, accurately identifying domains with spatial coherence in both gene expression and histology in situ and effectively integrating data from multi-sample remains challenging. Here, we propose ResST, a graph self-supervised residual learning model based on graph neural network and Margin Disparity Discrepancy (MDD) theory. ResST aggregates gene expression, biological effects, spatial location, and morphological information to capture nonlinear relationships between a cell and surrounding cells for spatial domain identification. Also, ResST integrates multiple ST datasets and aligns latent embeddings based on MDD theory for correcting batch effects. Results show that ResST identifies continuous spatial domains at a finer scale in ten ST datasets acquired with different technologies. Moreover, ResST efficiently integrated data from multiple tissue sections vertically or horizontally while correcting batch effects. Overall, ResST demonstrates exceptional performance in analyzing ST datasets. A graph self-supervised residual learning framework (ResST) for natural domain identification and data integration of spatial transcriptomics. [ABSTRACT FROM AUTHOR]

Introduction Objectives Results Conclusion Authoritarianism and populism are used regularly to describe the individuals responsible for anti‐democratic action. These two constructs share some similarities with regard to how they hinder democracy and at times have been used interchangeably to describe such issues. However, authoritarians and populists may differ with regard to their political identification, as well as how they view the government and the existing establishment.With a US college sample, this study's goal was to examine how authoritarianism and populist attitudes influence views on pluralism, elitism, trust in government, identity fusion, and political identification (identification with American political parties).The findings indicated that right‐wing authoritarians trusted the government, endorsed elitist attitudes, but were low on pluralism; this pattern was the opposite for those high on populist attitudes. Left‐wing authoritarianism was related only to low pluralism. Moreover, low trust in the government partially mediated the link between populist attitudes and pluralism. Results also indicated that right‐wing and left‐wing authoritarians identified with the Republican and Democratic parties, respectively, whereas political identification was unrelated to populist attitudes. Furthermore, identity fusion partially mediated the link between right‐wing authoritarianism and identification with the Republican Party.Authoritarianism and populist attitudes may explain different motivations for anti‐democratic thought and behaviors. This study contributes to ongoing debates found in contemporary populism and authoritarianism research as well as different solutions to addressing their rise in mainstream politics. [ABSTRACT FROM AUTHOR]

Among patients with epilepsy, 30–40% experience recurrent seizures even after adequate antiseizure medications therapies, making them refractory. The early identification of refractory epilepsy is important to provide timely surgical treatment for these patients. In this study, we analyze interictal electroencephalography (EEG) data to predict drug refractoriness in patients with temporal lobe epilepsy (TLE) who were treated with monotherapy at the time of the first EEG acquisition. Various EEG features were extracted, including statistical measurements and interchannel coherence. Feature selection was performed to identify the optimal features, and classification was conducted using different classifiers. Functional connectivity and graph theory measurements were calculated to identify characteristics of refractory TLE. Among the 48 participants, 34 (70.8%) were responsive, while 14 (29.2%) were refractory over a mean follow-up duration of 38.5 months. Coherence feature within the gamma frequency band exhibited the most favorable performance. The light gradient boosting model, employing the mutual information filter-based feature selection method, demonstrated the highest performance (AUROC = 0.821). Compared to the responsive group, interchannel coherence displayed higher values in the refractory group. Interestingly, graph theory measurements using EEG coherence exhibited higher values in the refractory group than in the responsive group. Our study has demonstrated a promising method for the early identification of refractory TLE utilizing machine learning algorithms. [ABSTRACT FROM AUTHOR]

Summary: Multivariate longitudinal ordinal and continuous data exist in many scientific fields. However, it is a rigorous task to jointly analyse them due to the complicated correlated structures of those mixed data and the lack of a multivariate distribution. The multivariate probit model, assuming there is a multivariate normal latent variable for each multivariate ordinal data, becomes a natural modeling choice for longitudinal ordinal data especially for jointly analysing with longitudinal continuous data. However, the identifiable multivariate probit model requires the variances of the latent normal variables to be fixed at 1, thus the joint covariance matrix of the latent variables and the continuous multivariate normal variables is restricted at some of the diagonal elements. This constrains to develop both the classical and Bayesian methods to analyse mixed ordinal and continuous data. In this investigation, we proposed three Markov chain Monte Carlo (MCMC) methods: Metropolis–Hastings within Gibbs algorithm based on the identifiable model, and a Gibbs sampling algorithm and parameter‐expanded data augmentation based on the constructed non‐identifiable model. Through simulation studies and a real data application, we illustrated the performance of these three methods and provided an observation of using non‐identifiable model to develop MCMC sampling methods. [ABSTRACT FROM AUTHOR]