Miracle-dz/UniFAR-FTUs huggingface dataset:
Convolutional Neural Network (CNN) to reduce construction loss in JPEG compression

In recent decades, digital image processing has gained enormous popularity. Consequently, a number of data compression strategies have been put forth, with the goal of minimizing the amount of information required to represent images. Among them, JPEG compression is one of the most popular methods that has been widely applied in multimedia and digital applications. The periodic nature of DFT makes it impossible to meet the periodic condition of an image's opposing edges without producing severe artifacts, which lowers the image's perceptual visual quality. On the other hand, deep learning has recently achieved outstanding results for applications like speech recognition, image reduction, and natural language processing. Convolutional Neural Networks (CNN) have received more attention than most other types of deep neural networks. The use of convolution in feature extraction results in a less redundant feature map and a smaller dataset, both of which are crucial for image compression. In this work, an effective image compression method is purposed using autoencoders. The study's findings revealed a number of important trends that suggested better reconstruction along with good compression can be achieved using autoencoders.
Spectra of generators of Markovian evolution in the thermodynamic limit: From non-Hermitian to full evolution via tridiagonal Laurent matrices

We determine spectra of single-particle translation-invariant Lindblad operators on the infinite line. In the case where the Hamiltonian is given by the discrete Laplacian and the Lindblad operators are rank $r$, finite range and translates of each other, we obtain a representation of the Lindbladian as a direct integral of finite range bi-infinite Laurent matrices with rank-$r$-perturbations. By analyzing the direct integral we rigorously determine the spectra in the general case and calculate it explicitly for several types of dissipation e.g.\ dephasing, and coherent hopping. We further use the detailed information about the spectrum to prove gaplessness, absence of residual spectrum and a condition for convergence of finite volume spectra to their infinite volume counterparts. We finally extend the discussion to the case of the Anderson Hamiltonian, which enables us to study a Lindbladian recently associated with localization in open quantum systems.
Experiments on Metamaterials with Negative Effective Static Compressibility

The volume of ordinary materials decreases in response to a pressure increase exerted by a surrounding gas or liquid, i.e., the material volume compressibility is positive. Recently, poroelastic metamaterial architectures have been suggested theoretically that allow for an unusual negative effective static volume compressibility—which appears to be forbidden for reasons of energy conservation at first sight. The challenge in the three-dimensional (3D) fabrication of these blueprints lies in the necessary many hollow 3D crosses sealed by thin membranes, which we realize in this work by using 3D laser microlithography combined with a serendipitous mechanism. By using optical-microscopy cross-correlation analysis, we determine an extraordinarily large negative metamaterial effective volume compressibility of κeff=−0.8% bar−1=−80 GPa−1 under pressure control.
Chronic liver disease is not associated with statin prescription in a primary care cohort

Statins have historically been underutilized in patients with chronic liver disease (CLD). We sought to investigate the association between CLD and statin prescription in a primary care setting. Our retrospective cohort study identified primary care patients with a low-density lipoprotein value and more than one office visit from 2012 through 2018. Indication for statin therapy was determined using the Third Adult Treatment Panel criteria prior to November 2016 and the American College of Cardiology and American Heart Association guidelines thereafter. Indication for statin prescription and statin therapy by year was determined. Patients with CLD were identified using ICD-9/10 diagnosis codes. In total, 2119 individuals with an indication for statin therapy were identified. Of these individuals, 354 (16.7%) had CLD. Alcoholic and nonalcoholic fatty liver disease comprised 44.9% and 28.5% of the CLD population, respectively; 27.7% had cirrhosis. There was no difference in the prevalence of statin prescriptions when comparing patients with a CLD diagnosis to those without one (57.9 vs 59.9%, p = 0.48). A diagnosis of CLD was also not significantly associated with statin prescription when adjusting for other covariates (odds ratio (OR) 1.02; 95% confidence interval (CI) 0.78–1.33). An alanine aminotransferase level greater than 45 U/L significantly reduced the odds of a statin prescription (OR 0.62; 95% CI 0.44–0.87). Overall, the presence of a CLD diagnosis was not associated with attenuated statin utilization compared to those without a CLD diagnosis. Nevertheless, adherence to guideline indicated statin therapy remains suboptimal and efforts to increase statin utilization in this high-risk population remain prudent.
Hitting the mark: Localization of mRNA and biomolecular condensates in health and disease

Subcellular mRNA localization is critical to a multitude of biological processes such as development of cellular polarity, embryogenesis, tissue differentiation, protein complex formation, cell migration, and rapid responses to environmental stimuli and synaptic depolarization. Our understanding of the mechanisms of mRNA localization must now be revised to include formation and trafficking of biomolecular condensates, as several biomolecular condensates that transport and localize mRNA have recently been discovered. Disruptions in mRNA localization can have catastrophic effects on developmental processes and biomolecular condensate biology and have been shown to contribute to diverse diseases. A fundamental understanding of mRNA localization is essential to understanding how aberrations in this biology contribute the etiology of numerous cancers though support of cancer cell migration and biomolecular condensate dysregulation, as well as many neurodegenerative diseases, through misregulation of mRNA localization and biomolecular condensate biology.
Research progress of field-induced soft smart materials

The field-induced soft smart materials are a kind of soft matter whose macroscopic properties (mechanical, or optical) can be significantly and actively controlled and manipulated by external fields such as magnetic field, electric field, temperature or light. In this paper, we briefly review the research and application progress of the field-induced soft smart materials in recent years and discuss the development problems and trend in this research area. In particular, we focus on three typical field-induced soft materials of smart materials: magnetorheological fluid, electrorheological fluid, and temperature and light sensitive polymer gel.
Detection and classification of hepatocytes and hepatoma cells using atomic force microscopy and machine learning algorithms

Hepatocellular carcinoma is a high‐risk malignant tumor. Hepatoma cells are transformed from normal cells and have unique surface nanofeatures in addition to the characteristics of the original cells. In this paper, atomic force microscopy was used to extract the three‐dimensional morphology and mechanical information of HL‐7702 human hepatocytes and SMMC‐7721 and HepG2 hepatoma cells in culture, such as the elastic modulus and viscoelasticity. The characteristics of different cells were compared and analyzed. Finally, the cell morphology and mechanics information were used for training machine learning algorithms. With the trained model, the detection of cells was realized. The classification accuracy was as high as 94.54%, and the area under the receiver operating characteristic (ROC) curve (AUC) was 0.99. Thus, hepatocytes and hepatoma cells were accurately identified and assessed. We also compared the classification effects of other machine learning algorithms, such as support vector machine and logistic regression. Our method extracts cellular nanofeatures directly from the surface of cells of unknown type for cell classification. Compared with microscope image‐based analysis and other methods, this approach can avoid the misjudgment that may occur when different doctors have different levels of experience. Thus, the proposed method provides an objective basis for the early diagnosis of hepatocellular carcinoma.
Farm operations and slips, trips, and falls among corn farm workers in Thailand

Slips, trips, and falls (STFs) represent a main source of injury among farm workers. The purpose of this study was to evaluate the association between farm operations and STFs among corn farm workers. We conducted a cross-sectional study using a self-administered questionnaire among corn farm workers in Nan and Saraburi provinces, Thailand from July 5 to 23, 2022. Poisson regression analysis was used. Among 338 participants, 122 (36.1%) had experienced an STF in the previous 6 months. Conducting very frequent, frequent, or occasional pest management was associated with a higher incidence rate ratio (IRR) of STFs than never or rarely pest management (adjusted IRR 1.93, 95% confidence interval [CI]=1.23 to 3.04, p=0.004). People with marginal or unsatisfactory work break lengths had a higher incidence rate of STFs than those with satisfactory work breaks (adjusted IRR 1.40, 95% CI=1.03 to 1.89, p=0.030). We found that corn farm workers in our study often experienced STFs, which was associated with a high frequency of pest management practices and inadequate work breaks. Reducing the physical burden of pest management may be effective as an STF prevention strategy.
Comparison of the effects of transcutaneous electrical nerve stimulation and interferential current therapies in central sensitization in patients with knee osteoarthritis

Background This study is primarily aimed to determine whether transcutaneous electrical nerve stimulation (TENS) and interferential current (IFC) treatments have any effect on central sensitization (CS) in patients with knee osteoarthritis (OA) and to investigate which treatment is more effective. Methods In this randomized controlled trial, 80 patients were randomized into four treatment groups TENS, Plasebo-TENS, IFC, and Plasebo-IFC. All interventions were applied 5 times a week for 2 weeks. Primary outcome was pressure pain threshold (PPT), which is accepted as the objective indicator of CS, at the painful knee and at the shoulder as a painless distant point. Other outcome measures were the visual analog scale (VAS), Western Ontario and McMaster Universities Osteoarthritis Index, Timed Up and Go Test, pain catastrophizing scale, Beck Depression Inventory, and Tampa Scale of Kinesiophobia. Results All assessment parameters were improved, without a significant difference among the groups except PPT. PPT scores were significantly improved in TENS and IFC groups when compared with the sham groups at 2 weeks and 3 months. In addition, this improvement was even more pronounced in the TENS group. Multivariable logistic regression analysis showed that the patient’s inclusion in the TENS group, an initial high PPT, and an initial low VAS score were independent risk factors for improvement in the PPT. Conclusions This study shows that TENS and IFC reduced pain sensitivity as compared to placebo groups in patients with knee OA. This effect was more pronounced in the TENS group.
TOWARDS ROBUST SELF-CALIBRATION FOR HANDHELD 3D LINE LASERSCANNING

Abstract. This paper studies self-calibration of a structured light system, which reconstructs 3D information using video from a static consumer camera and a handheld cross line laser projector. Intersections between the individual laser curves and geometric constraints on the relative position of the laser planes are exploited to achieve dense 3D reconstruction. This is possible without any prior knowledge of the movement of the projector. However, inaccurrately extracted laser lines introduce noise in the detected intersection positions and therefore distort the reconstruction result. Furthermore, when scanning objects with specular reflections, such as glossy painted or metalic surfaces, the reflections are often extracted from the camera image as erroneous laser curves. In this paper we investiagte how robust estimates of the parameters of the laser planes can be obtained despite of noisy detections.
Transformation of immunosuppressive mtKRAS tumors into immunostimulatory tumors by Nerofe and Doxorubicin

Members of the rat sarcoma viral oncogene (RAS) subfamily KRAS are frequently mutated oncogenes in human cancers and have been identified in pancreatic ductal, colorectal, and lung adenocarcinomas. In this study, we show that a derivative of the hormone peptide Tumor Cell Apoptosis Factor (TCApF), Nerofe™ (dTCApFs), in combination with Doxorubicin (DOX) substantially reduces viability of tumor cells. It was observed that the combination of Nerofe and DOX downregulated KRAS signaling via miR217 upregulation, resulting in enhanced apoptosis of tumor cells. In addition, the combination of Nerofe and DOX also resulted in activation of the immune system against tumor cells, manifested by an increase in the immunostimulatory cytokines IL-2 and IFN-γ as well as the recruitment of NK cells and M1 macrophages to the tumor site.
Predicting Remaining Life Using Damage Mechanics Principles

Continuum damage principles have been used to characterize damage occurring in pressurized components operating under creep conditions. Following a review of the concepts of damage and its measurement, analysis has been presented to show how damage can be estimated using continuum damage concepts and how the remaining life can be estimated in terms of the current creep rate of a component. It is shown how such damage can be estimated using measurements of the local creep rate.Paper published with permission.Compilation Copyright © 2014 ASME
Maximum and mean standardized uptake values of medication-related osteonecrosis of the jaw with bone SPECT/CT: comparison of mandibular pathologies, control and temporomandibular joints.

OBJECTIVE Recently, single-photon emission CT/CT (SPECT/CT) plays an important role in assessing patients with medication-related osteonecrosis of the jaw (MRONJ). The aim of this study was to investigate maximum and mean standardized uptake values (SUVs) of MRONJ with bone SPECT/CT, especially comparison of mandibular pathologies, control and temporomandibular joints. METHODS 61 mandibular patients with MRONJ who underwent bone SPECT/CT were included in this study. The maximum and mean SUVs of the lesion, right and left sides of the lesion, opposite side of the lesion as control, right and left temporomandibular joints were analyzed using a workstation and software. The SUVs of MRONJ were analyzed using one-way analysis of variance with Tukey's honestly significant difference test. Patient characteristics with MRONJ and SUVs were analyzed using Mann-Whitney U test. P-values less than 0.05 were considered to indicate statistical significance. RESULTS The maximum and mean SUVs for opposite side of the lesions (4.4 ± 2.0 and 1.8 ± 0.7) were significantly lower than those for mandibular lesions (18.3 ± 8.1 and 6.3 ± 2.8), right side of the lesions (8.1 ± 3.9 and 2.9 ± 1.3) and left side of the lesions (8.1 ± 3.9 and 2.8 ± 1.4), respectively. The maximum and mean SUVs for right and left sides of the lesions, and opposite side of the lesions, right and left temporomandibular joints were not significant difference. Furthermore, the maximum SUVs of the mandibular lesions were a significant difference for age and staging. CONCLUSIONS The maximum and mean SUVs with SPECT/CT can be useful in the quantitative management of MRONJ patients.
Optimized variable selection via repeated data splitting

Model selection in high‐dimensional settings has received substantial attention in recent years, however, similar advancements in the low‐dimensional setting have been lacking. In this article, we introduce a new variable selection procedure for low to moderate scale regressions (n>p). This method repeatedly splits the data into two sets, one for estimation and one for validation, to obtain an empirically optimized threshold which is then used to screen for variables to include in the final model. In an extensive simulation study, we show that the proposed variable selection technique enjoys superior performance compared with candidate methods (backward elimination via repeated data splitting, univariate screening at 0.05 level, adaptive LASSO, SCAD), being amongst those with the lowest inclusion of noisy predictors while having the highest power to detect the correct model and being unaffected by correlations among the predictors. We illustrate the methods by applying them to a cohort of patients undergoing hepatectomy at our institution.
Salvianolic Acid C Inhibits the Epithelial-Mesenchymal Transition and Ameliorates Renal Tubulointerstitial Fibrosis.

BACKGROUND Salvianolic acid C (SAC) is a natural compound derived from Salvia miltiorrhiza that can protect against renal diseases. The aims of this work were to explore the effect of SAC on kidney tubulointerstitial fibrosis and study the associated mechanism. METHODS Models for unilateral ureteral obstruction (UUO) and aristolochic acid I (AAI) were established in mice to study renal tubulointerstitial fibrosis. Rat kidney fibroblasts (NRK-49F) and human kidney epithelial cells (HK2) were used as cellular models to evaluate the effects of SAC on kidney fibrosis. RESULTS Treatment with SAC for two weeks reduced the level of renal tubulointerstitial fibrosis in UUO- and AAI-induced fibrotic kidneys, as demonstrated by Masson's staining and Western blot. SAC inhibited extracellular matrix protein expression in NRK-49F cells and TGF-β-stimulated HK2 cells in dose-dependent fashion. Moreover, SAC inhibited the expression of epithelial-mesenchymal transition (EMT) factors in animal and cellular models of kidney fibrosis, as well as the EMT-related transcription factor snail. Furthermore, SAC inhibited the fibrosis-related signaling pathway Smad3 in the fibrotic kidneys of two mouse models and in renal cells. CONCLUSIONS We conclude that SAC inhibits EMT and ameliorates tubulointerstitial fibrosis through involvement of the signaling pathway for transforming growth factor-β (TGF-β)/Smad.
QRS complex detection based on continuous density hidden Markov models using univariate observations

In the electrocardiogram (ECG), the detection of QRS complexes is a fundamental step in the ECG signal processing chain since it allows the determination of other characteristics waves of the ECG and provides information about heart rate variability. In this work, an automatic QRS complex detector based on continuous density hidden Markov models (HMM) is proposed. HMM were trained using univariate observation sequences taken either from QRS complexes or their derivatives. The detection approach is based on the log-likelihood comparison of the observation sequence with a fixed threshold. A sliding window was used to obtain the observation sequence to be evaluated by the model. The threshold was optimized by receiver operating characteristic curves. Sensitivity (Sen), specificity (Spc) and F1 score were used to evaluate the detection performance. The approach was validated using ECG recordings from the MIT-BIH Arrhythmia database. A 6-fold cross-validation shows that the best detection performance was achieved with 2 states HMM trained with QRS complexes sequences (Sen = 0.668, Spc = 0.360 and F1 = 0.309). We concluded that these univariate sequences provide enough information to characterize the QRS complex dynamics from HMM. Future works are directed to the use of multivariate observations to increase the detection performance.
Immune-based therapies in diffuse large B-cell lymphoma

ABSTRACT Introduction Diffuse large B-cell lymphoma (DLBCL) is an aggressive and clinically heterogeneous malignancy originating from B-cells with up to 40% of patients experiencing primary refractory disease or relapse after first-line treatment. However, the past 5 years have seen a flurry of new drug approvals for DLBCL anchored upon new immune therapies, including chimeric antigen receptor (CAR) T-cells and antibody-based therapies. Areas covered This article summarizes recent advances in the treatment of DLBCL, including in the first line and relapsed and refractory setting (second-line and beyond). A literature search was conducted for publications relevant to the immunotherapeutic approach to DLBCL from 2000 through March 2023 within PubMed and articles were reviewed. The search terms were immunotherapy, monoclonal antibodies, chimeric antigen receptor modified T-cell (CAR-T), and classification of DLBCL. Relevant clinical trials and pre-clinical studies exploring the strengths and weaknesses of current immune therapies against DLBCL were chosen. We additionally explored how intrinsic differences amongst DLBCL subtype biology and endogenous host immune recruitment contribute to variable therapeutic efficacy. Expert Opinion Future treatments will minimize chemotherapy exposure and be chosen by underlying tumor biology, paving the way for the promise of chemotherapeutic free regimens and improved outcomes for poor-risk subgroups.
Variable selection and chemometric models for discriminating symptomatic gout based on a metabolic target analysis

In clinical practice, uric acid is frequently used as a diagnostic criterion in gout. However, gout is commonly confused with other diseases, including rheumatoid arthritis, soft tissue joint injury, and hyperuricosuric calcium oxalate urolithiasis. Two new strategies—graphical index of separation and subwindow permutation analysis—were applied to understand the metabolic changes induced by gout. Metabolic target analysis was performed using high performance liquid chromatography with a diode array detector. Compared with the nongout samples, the concentrations of uric acid, uracil, inosine, adenosine, and tryptophan are different in gout samples, and these metabolites could be used as important diagnostic markers. However, the uric acid, uracil, phenylalanine, tryptophan, and adenine concentrations differed between acute and chronic gout. We confirmed the metabolic disorder of uracil during the basic development of gout. In the gout and nongout groups, the recognition rate of the model reached 0.98, whereas the value of recognition ability was only 0.79 when uric acid was used as a single variable. In the acute and chronic class of gout, the recognition rate of the model was 0.90 and that of uric acid was only 0.62. Variable selection combined with chemometric models can be used as a supplementary method for the diagnosis and prognosis of gout in clinical practice.