Miracle-dz/UniFAR-FTUs huggingface dataset:
Case report: Dissolving carotid plaque associated to Lorlatinib-related dyslipidemia

We present a case with prolonged Lorlatinib-related dyslipidemia causing internal carotid artery stenosis, putting the patient at risk of cerebrovascular events. Through intensified lipid-lowering treatment and dose reduction of Lorlatinib, LDL-C levels decreased markedly. Surprisingly, the left sided internal carotid artery stenosis dissolved accordingly. Due to the high efficacy of the new selective tyrosine kinase inhibitors and resulting long-term treatment, it is essential to carefully follow-up and include drug specific side effect monitoring. This case emphasizes that Loraltinib-related dyslipidemia has to be taken seriously and treatment should be initiated as promptly as possible. We conclude that in cases were lipid dysregulation remains and Lorlatinib treatment has to be continued, cerebrovascular appraisal through ultrasound should be considered and, if stenosis is evident, intensified treatment regimen of dyslipidemia or dose reduction of Lorlatinib should be discussed in an interdisciplinary setting.
Bayesian Inference for Non-Linear Forward Model by Using a VAE-Based Neural Network Structure

In this paper, a Variational Autoencoder (VAE) based framework is introduced to solve parameter estimation problems for non-linear forward models. In particular, we focus on applications in the field of medical imaging where many thousands of model-based inference analyses might be required to populate a single parametric map. We adopt the concept from Variational Bayes (VB) of using an approximate representation of the posterior, and the concept from the VAE of using the latent space representation to encode the parameters of a forward model. Our work develops the idea of mapping between time-series data and latent parameters using a neural network in variational way. A loss function that differs from the classic VAE formulation and a new sampling strategy are proposed to enable uncertainty estimation as part of the forward model inference. The VAE-based structure is evaluated using simulation experiments on a simple example and two perfusion MRI forward models. Compared with analytical VB (aVB) and Markov Chain Monte Carlo (MCMC), our VAE-based model achieves comparable accuracy, and hundredfold improvement in computational time (100ms/image). We believe this VAE-like framework can be generalized to imaging modularities with higher complexity and thus benefit clinical adoption where otherwise long processing time associated with conventional inference methods is prohibitive.
PERILAKU INOVATIF GURU DALAM PEMBELAJARAN DI SMK NEGERI KOTA PADANG.

Penelitian ini dilatar belakangi dari hasil pengamatan yang peneliti lakukan dibeberapa SMK Negeri Kota Padang, terlihat bahwa perilaku inovatif guru masih belum optimal. Penelitian ini bertujuan untuk mengetahui seberapa tinggi tingkat perilaku inovatif guru dalam proses pembelajaran yang mencakup eksplorasi ide, menghasilkan ide dan implementasi ide. Ada 3 (tiga) pertanyaan yang dijawab dalam penelitian ini, yaitu: 1) seberapa baik perilaku inovatif guru mengeksplorasi ide dalam pembelajaran di SMK Negeri Kota Padang; 2) seberapa baik perilaku inovatif guru menghasilkan ide dalam pembelajaran di SMK Negeri Kota padang; 3) seberapa baik perilaku inovatif guru mengimplementasikan ide dalam pembelajaran di SMK Negeri Kota Padang. Jenis penelitian yang digunakan adalah deskriptif kuantitatif dengan populasi adalah seluruh guru SMK Negeri Kota Padang yang berjumlah 818 orang. Dengan sample 135 orang. Besarnya sampel ditentukan dengan menggunakan Cluster random sampling yaitu dengan sistem undian. Instrumen penelitian yang digunakan adalah angket dengan model skala likert tentang perilaku inovatif guru dalam proses pembelajaran yang berjumlah 30 item. Sebelum angket tersebut digunakan sudah terlebih dahulu di uji validitas dan reabilitasnya. Data yang terkumpul di olah dengan mencari skor rata-rata dan tingkat capaian rata-rata. Dari hasil pengolahan tersebut diperoleh bahwa perilaku inovatif guru di SMK Negeri Kota padang dari aspek inovatif guru di SMK Negeri Kota Padang dalam eksplorasi ide pembelajaran (merencanakan pembelajaran, melaksanakan pembelajaran, mengevaluasi pembelajaran). Menurut hasil penilaian guru skor rata-rata yaitu 4.28 dengan TCR (85.59%) kategori baik. Perilaku inovatif guru di SMK Negeri Kota Padang dilihat dari menghasilkan ide dalam pembelajaran (merencanakan pembelajaran, melaksanakan pembelajaran, mengevaluasi pembelajaran). Menurut penilaian guru skor rata-rata yaitu 4.14 dengan TCR (82.74%) kategori baik. Inovatif guru di SMK Negeri Kota Padang di lihat dari implementasi ide guru dalam pembelajaran (merencanakan pembelajaran, melaksanakan pembelajaran, mengevaluasi pembelajaran). Menurut penilaian guru skor rata-rata yaitu 4.19 dengan TCR (83.80%) berada pada kategori baik. Berdasarkan hasil penelitian penulis dapat ditarik kesimpulan bahwa 3 indikator dari 3 sub variabel yang penulis teliti mencapai kriteria baik dengan skor rata-rata 4,20. Keywords: Perilaku Inovatif Guru
Improving the disaggregation of MODIS land surface temperatures in an urban environment: a statistical downscaling approach using high-resolution emissivity

ABSTRACT Spatially and temporally dense land surface temperature (LST) data are necessary to capture the high variability of the urban thermal environment. Sensors on board satellites with high revisit time cannot provide adequately detailed spatial information; thus, the downscaling of LST is recognized as being an important and inevitable intermediate process. In this paper, improvement in the downscaled LST accuracy is investigated, employing the statistical downscaling methodology in an urban setting. A new approach is proposed, where thermal radiances are disaggregated using multiple regression analysis and are then combined with emissivity values derived from a high-resolution image classification. Predictors include reflectance values, built-up and vegetation indices, and topographic data. Surface classification is performed utilizing machine learning techniques and fusing Sentinel-2 imagery with ancillary data. Thermal data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor are downscaled from their original resolution to 100 m in the city of Athens, Greece. Validation of sharpened temperatures is performed using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) surface temperature product and in-situ measurements. It is demonstrated that the proposed downscaling framework using ridge regression has the potential to produce reliable, high temporal LST estimates with an average error of fewer than 2 K, while consistently having a better accuracy than the reference, single-predictor downscaling of the MODIS LST product.
LYSIMETRIC EVALUATION OF SEBAL ALGORITHM IN SUBTROPICAL CLIMATE

Understanding the spatio-temporal variation of evapotranspiration (ET) over irrigated agricultural areas is important to help the water management. Many remote sensing methods have been developed to estimate ET, among them the most used is the Surface Energy Balance Algorithm for Land (SEBAL). However, SEBAL was developed for particular sensors and regions, in which functions and empirical parameters inherent to its algorithm correspond to these regions and sensors. Therefore, the aim of this study was to evaluate the SEBAL algorithm for images of Landsat 8, through lysimetric data in a subtropical climate region. The study was carried out in two subtropical climate regions in Brazil. The first in the city of Piracicaba in the São Paulo state and the second in the city of Dourados in the Mato Grosso do Sul state. The images of Landsat 8 and the meteorological data are matching for the year 2013 to 2017 on a monthly scale for images and of 15 minutes for the meteorological data. Utilizing the SEBAL algorithm was estimated all the components of the energy balance and consequently the ET. Thus, the evaluation was done using goodness of fit measures to residuals. The results were reasonable; thus, the algorithm SEBAL can be used to the Landsat 8 images in subtropical climates, carefully. However, the calibration of the algorithm SEBAL must be performed to improve the estimates.
Extraribosomal Functions of Bacterial Ribosomal Proteins—An Update, 2023

Ribosomal proteins (r-proteins) are abundant, highly conserved, and multifaceted cellular proteins in all domains of life. Most r-proteins have RNA-binding properties and can form protein–protein contacts. Bacterial r-proteins govern the co-transcriptional rRNA folding during ribosome assembly and participate in the formation of the ribosome functional sites, such as the mRNA-binding site, tRNA-binding sites, the peptidyl transferase center, and the protein exit tunnel. In addition to their primary role in a cell as integral components of the protein synthesis machinery, many r-proteins can function beyond the ribosome (the phenomenon known as moonlighting), acting either as individual regulatory proteins or in complexes with various cellular components. The extraribosomal activities of r-proteins have been studied over the decades. In the past decade, our understanding of r-protein functions has advanced significantly due to intensive studies on ribosomes and gene expression mechanisms not only in model bacteria like Escherichia coli or Bacillus subtilis but also in little-explored bacterial species from various phyla. The aim of this review is to update information on the multiple functions of r-proteins in bacteria.
Life After Traumatic Brain Injury: Effects on the Lifestyle and Quality of Life of Community-Dwelling Patients

Persons who have experienced traumatic brain injury (TBI) may encounter a range of changes in their physical, mental, and cognitive functions as well as high fatigue levels. To gain a comprehensive understanding of the challenges faced by persons after TBI, we conducted multi-domain assessments among community-dwelling persons with a history of TBI and compared them with age- and sex-matched controls from the Northeastern Taiwan Community Medicine Research Cohort between 2019 and 2021. A total of 168 persons with TBI and 672 non-TBI controls were not different in terms of demographics, comorbidities, and physiological features. However, compared with the non-TBI group, the TBI group had a distinct lifestyle that involved increased reliance on analgesics (6.9% vs. 15.0%, respectively; p = 0.001) and sleep aids (p = 0.008), which negatively affected their quality of life. Moreover, they consumed more coffee (p < 0.001), tea (p < 0.001), cigarettes (p = 0.002), and betel nuts (p = 0.032) than did the non-TBI group. Notably, the use of coffee had a positive effect on the quality of life of the TBI group (F = 4.034; p = 0.045). Further, compared with the non-TBI group, the TBI group had increased risks of sarcopenia (p = 0.003), malnutrition (p = 0.003), and anxiety (p = 0.029) and reduced blood levels of vitamin D (29.83 ± 10.39 vs. 24.20 ± 6.59 ng/mL, respectively; p < 0.001). Overall, the TBI group had a reduced health-related quality of life, with significant challenges related to physical health, mental well-being, social interactions, pain management, and fatigue levels. Moreover, the TBI group experienced poorer sleep quality and efficiency than did the non-TBI group. In conclusion, persons who have sustained brain injuries that require comprehensive and holistic care that includes lifestyle modification, mental and physical healthcare plans, and increased long-term support from their communities. ClinicalTrials.gov (identifier: NCT04839796)
The Mediterranean Mussel Mytilus galloprovincialis (Mollusca: Bivalvia) in Chile: Distribution and Genetic Structure of a Recently Introduced Invasive Marine Species

Simple Summary The genetic pool of invasive species greatly influences their ability to establish and spread. The blue mussels Mytilus galloprovincialis, originating from the Mediterranean, are major invaders worldwide. Our study examined their genetic diversity and structure in Chile, comparing them with native populations. We used mitochondrial DNA to analyze the genetic traits and origins of invasive populations. Two lineages of M. galloprovincialis were identified, i.e., NW Atlantic and Mediterranean. Although recently introduced, no genetic structure was found in Chilean populations. However, a mixture of lineages increased the genetic diversity along the coast. The invasion coastal extent remains small (~100 km), suggesting their recent introduction. The expansion of these populations may encounter natural barriers; nevertheless, it is advisable to monitor these species’ distribution. Abstract The genetic characteristics of invasive species have a significant impact on their ability to establish and spread. The blue mussel (Mytilus galloprovincialis), native to the Mediterranean Sea, is a leading invasive species of intertidal coasts throughout much of the world. Here, we used mitochondrial DNA sequence data to investigate the genetic diversity and phylogeographic structure of invasive (M. galloprovincialis) versus native (Mytilus chilensis) populations of blue mussels in Chile. We evaluated whether genetic diversity in invasive populations could be explained by the genetic characteristics of the native sources from which they might be derived. A phylogenetic analysis confirmed two lineages of the invasive M. galloprovincialis, i.e., the NW Atlantic and the Mediterranean lineages. We found no evidence of genetic structure in the invasive range of M. galloprovincialis in Chile, most probably because of its recent arrival. We did, however, detect a spatial mixture of both M. galloprovincialis lineages at sampling locations along the Chilean coast, giving rise to higher levels of genetic diversity in some areas compared to the population of native M. chilensis. The coastal area of the invasion is still small in extent (~100 km on either side of two large ports), which supports the hypothesis of a recent introduction. Further expansion of the distribution range of M. galloprovincialis may be limited to the north by increasing water temperatures and to the south by a natural biogeographic break that may slow or perhaps stop its spread. The use of internal borders as a tool to minimise or prevent M. galloprovincialis spread is therefore a genuine management option in Chile but needs to be implemented rapidly.
Deciphering Hydrogen Embrittlement Mechanisms in Ti6Al4V Alloy: Role of Solute Hydrogen and Hydride Phase

Ti6Al4V (Ti64) is a versatile material, finding applications in a wide range of industries due to its unique properties. However, hydrogen embrittlement (HE) poses a challenge in hydrogen-rich environments, leading to a notable reduction in strength and ductility. This study investigates the complex interplay of solute hydrogen (SH) and hydride phase (HP) formation in Ti64 by employing two different current densities during the charging process. Nanoindentation measurements reveal distinct micro-mechanical behavior in base metal, SH, and HP, providing crucial insights into HE mechanisms affecting macro-mechanical behavior. The fractography and microstructural analysis elucidate the role of SH and HP in hydrogen-assisted cracking behaviors. The presence of SH heightens intergranular cracking tendencies. In contrast, the increased volume of HP provides sites for crack initiation and propagation, resulting in a two-layer brittle fracture pattern. The current study contributes to a comprehensive understanding of HE in Ti6Al4V, essential for developing hydrogen-resistant materials.
A Tiny Object Detection Method Based on Explicit Semantic Guidance for Remote Sensing Images

In the field of remote sensing, the detection of tiny objects has always been an interesting and highly regarded issue. Although many researchers have dedicated their efforts to study this problem, it still presents numerous challenges due to the complexity of the environment, in which tiny objects are presented in remote sensing images. To this end, we propose a remote sensing image tiny objects detection method based on explicit semantic guidance, with a specific focus on regions containing tiny objects. Specifically, we incorporate supervision of the tiny object regions during the training process. This supervision allowed us to extract tiny object regions, thereby forming an explicit attention map. This explicit attention map is employed to semantically modulate the feature map for detecting tiny objects, thus enhancing the regions containing tiny objects while suppressing the background. Extensive experiments are conducted on the AI-TODv2 dataset, and the proposed method can achieve an AP of 24.6%. The experimental results demonstrate the effectiveness of the proposed tiny object detection method based on explicit semantic guidance. The code will be released soon on the site of https://github.com/dyl96/ESG_TODNet.
A User-Centric Approach for Deep Residual-Echo Suppression in Double-Talk

We introduce a user-centric residual-echo suppression (URES) framework in double-talk. This framework receives a user operating point (UOP) that consists of two metric values: the residual echo suppression level (RESL) and the desired speech-maintained level (DSML) that the user expects from the RES outcome. Then, the URES pipeline undergoes three stages. Firstly, we consider a deep RES model with a tunable design parameter that balances between the RESL and DSML and utilizes 101 pre-trained instances of this model, each with a different design parameter value. Thus, an identical input is expected to generate a different pair of RESL and DSML values in the prediction of every instance. Second, every prediction is separately fed to a subsequent pre-trained deep model instance that estimates the RESL and DSML of the prediction since these metrics depend on unavailable information in practice. Lastly, each pair of RESL and DSML estimates is compared with the UOP. The pairs that match the UOP up to a given tolerance threshold are narrowed down to the prediction with the maximal acoustic-echo cancellation mean-opinion score (AECMOS), which is the output of the URES system. This suggested framework holds three prominent advantages introduced in this study: it generates an RES output with RESL and DSML that match a UOP, supports near-real-time tracking of UOP changes, and applies AECMOS maximization. Experimental results consider 60 h of varied real and synthetic data. Average results can achieve an AECMOS subjectively considered excellent with RESL and DSML deviations of roughly 2 dB from the UOP. Any UOP adjustment can be tracked in less than 40 ms with a real-time factor of 1.92, but due to the high computational resources demanded by the framework, this is enabled on-edge only with high-end dedicated hardware, which limits general availability.
Exploring the in vitro antimicrobial, antioxidant, and anticancer potentials of Spinifex littoreus Burm f. Merr. against human cervical cancer

Spinifex littoreus Burm f. Merr. is considered as a pharmaceutically important coastal weed whereas, therapeutical applications of this plant are least studied. The current study aimed to identify the antibacterial, antioxidant, and anticancer properties in the chloroform extract of Spinifex littoreus. Six bacterial and 4 fungal human infections were tested for antibacterial activity in the chloroform extract of S. littoreus (SL-CH). The antioxidant ability of SL-CH was screened using the DPPH, ABTS, and H2O2 assays. MTT assay was used to investigate the anticancer activity of SL-CH and ROS, Annexin V, PI, and cell cycle analysis were used to determine its efficacy. The bacterial strain Propionibacterium acnes and the fungal strain Sporothrix schenckii were found to have the largest zones of clearance when the SL-CH extract was used at a concentration of 500 µg/ml. The antioxidant potentials of SL-CH extract showed the maximum radical scavenging activity against ABTS (83.98%), H2O2 (63.73%), and DPPH (52.02%) and their IC50 value was 31.74 ? g/ml, 53.93 ? g/ml, and 139.6 ? g/ml respectively. The IC50 concentration for the chloroform extract of Spinifex littoreus was determined to be 117.5 µg/ml and it showed concentration-dependent anticancer activity against HeLa cells. The ROS fluorescence staining result of SL-CH demonstrated the production of reactive oxygen species, which caused HeLa cells to undergo apoptosis. It was demonstrated by annexin V staining, PI staining technique, and cell cycle analysis that SL-CH extracts caused apoptosis in HeLa cells, preventing their growth. Taken together, these results showed that Spinifex littoreus chloroform extract is rich in antimicrobial, antioxidant, and anticancer potentials. Therefore, Spinifex littoreus extract can treat and prevent various ailments.
VALUE OF DUAL-ENERGY COMPUTED TOMOGRAPHY IN THE ASSESSMENT OF PRIMARY LUNG CANCER

Objective: This study aims to observe the value of the dual-energy computed tomography (DECT) technique in the assessment of primary lung cancer. Compare the difference in density of lung tumors on the true non-contrast (TNC) and virtual non-contrast (VNC) images. Investigate the iodine concentration value of lung tumors in differentiating malignant and benign lesions as well as adenocarcinoma and squamous carcinoma in lung cancer. Methods: We conducted a cross-sectional descriptive study in 42 patients with solitary pulmonary nodules proved by pathology underwent doublephase enhanced CT scan at the Diagnostic Imaging Center of K Hospital, Hanoi. Process dual-energy CT data into virtual monoenergetic and virtual non-contrast images, comparing with true non-contrast images. Compare the iodine concentration of malignant and benign lesions, adenocarcinoma, and squamous cell carcinoma lung cancer. The slope rate was calculated from the spectral curve. Patients were divided into an inflammatory group, a malignant group, and a tuberculosis group. The Kruskal–Wallis test and Nemenyi test were performed to compare quantitative parameters among the three groups. Results: The study comprised 42 patients (34 males). The mean age of patients was 56 ±11. 23/42 right lung tumors (accounted for about 55%), 13/33 left lung tumors (about 40%). Pathological results showed that 73.8% (31/42) of the lesions were malignant, and 26.2% were benign. The density of lung tumors on the true non-contrast (TNC) and virtual noncontrast (VNC) images is 43,81 ± 10,90 and 43,32 ± 11,15 HU (p=0,147). The contrast-noise ratio of lung tumors has the highest value in the virtual monochrome image at 65 keV. The iodine concentration of malignant tumors was 0,37±0,15mg/ml, higher than benign lesions. The normalized iodine concentration (nIC) of lung tumors can differentiate malignant from benign lesions with an area under the curve of 0,748, with a best cut-off point of 0,27 mg/ml having a sensitivity is 74,2%, specificity of 81,8%. The normalized iodine concentration (nIC) of lung tumors can also differentiate adenocarcinoma from squamous cell carcinoma with an area under the curve of 0,835, with a best cut-off point of 0,36 mg/ml having a sensitivity is 76,5%, specificity of 100%. The mean slope rate for the inflammatory group was 2,51 ± 0,25, significantly higher than these parameters for the malignant group (p < 0.05), and the parameters for the malignant group were significantly higher than the tuberculosis group (p < 0.05). Conclusion: Virtual non-contrast images can replace the role of true non-contrast images. In virtual monoenergetic, the 65 keV sequence has the best Contrast to Noise Ratio (CNR). Quantitative analysis of iodine concentration in lung tumors can help differentiate malignant and benign lung lesions, adenocarcinoma, and squamous cell carcinoma. HU slope rate showed statistically significant differences, which is helpful in the differential diagnosis among inflammatory, malignant, and tuberculosis lesions.