Miracle-dz/UniFAR-FTUs huggingface dataset:
Development, efficacy and side effects of antibody‑drug conjugates for cancer therapy (Review)

Antibody-drug conjugates (ADCs) are anticancer drugs that combine cytotoxic small-molecule drugs (payloads) with monoclonal antibodies through a chemical linker and that transfer toxic payloads to tumor cells expressing target antigens. All ADCs are based on human IgG. In 2009, the Food and Drug Administration (FDA) approved gemtuzumab ozogamicin as the initial first-generation ADC. Since then, at least 100 ADC-related projects have been initiated, and 14 ADCs are currently being tested in clinical trials. The limited success of gemtuzumab ozogamicin has led to the development of optimization strategies for the next generation of drugs. Subsequently, experts have improved the first-generation ADCs and have developed second-generation ADCs such as ado-trastuzumab emtansine. Second-generation ADCs have higher specific antigen levels, more stable linkers and longer half-lives and show great potential to transform cancer treatment models. Since the first two generations of ADCs have served as a good foundation, the development of ADCs is accelerating, and third-generation ADCs, represented by trastuzumab deruxtecan, are ready for wide application. Third-generation ADCs are characterized by strong pharmacokinetics and high pharmaceutical activity, and their drug-to-antibody ratio mainly ranges from 2 to 4. In the past decade, the research prospects of ADCs have broadened, and an increasing number of specific antigen targets and mechanisms of cytotoxic drug release have been discovered and studied. To date, seven ADCs have been approved by the FDA for lymphoma, and three have been approved to treat breast cancer. The present review explores the function and development of ADCs and their clinical use in cancer treatment.
ESTIMATION OF RATE PARAMETER AND ITS RELATIONSHIP WITH LATENT AND INFECTIOUS PERIODS IN PLANT DISEASE EPIDEMICS

This paper estimates the logistic rate parameter (R) for three identifiable stages of a plant disease epidemic. Equations are obtained that give R when considering infected, infectious, and removed tissues. The estimations are illustrated using field data on disease progress in a susceptible cultivar of a tropical pasture legume. The importance of such assessments in developing models with higher biological realism is discussed.
Hydrophilic molecularly imprinted chitosan microspheres based on deep eutectic solvents for micro-solid phase extraction of catechin

Abstract Hydrophilic molecularly imprinted chitosan microspheres (HMICS) were synthesized using deep eutectic solvents (DESs)-(3-aminopropyl) triethoxysilane (APTES) as co-functional monomer for the extraction of catechin from green tea with micro-solid phase extraction (micro-SPE). Various factors were studied to optimize the extraction condition during extraction process. The actual extraction amount under the optimal conditions (amount of adsorbent (20 mg), type and volume of washing (acetone, 1.2 mL) and eluting solvent (acetone/acetic acid, 1.0 mL), extraction time (30 min), extraction temperature (40 °C), and sample pH (4)) were obtained at 97.06 mg·g−1. The catechin recovery ranged with ranged with limit of detection (LOD) within 0.09–0.24 µg·mL−1, and limit of quantification (LOQ) within 0.18–0.28 µg·mL−1. From the experimental results in this system, the HMICS was proved to have higher extraction capacity, improving as a promising adsorbent for the extraction of catechin. GRAPHICAL ABSTRACT
Blind light field image quality assessment combining disparity compensation with 3D data processing

： Compared with traditional 2D images ， light field images （ LFIs ） can record the intensity and di⁃ rectional information of light in scenes. Accordingly ， LFIs occupy an important position in multimedia technology applications. However ， during the generation and transmission of LFIs ， distortions are inevita⁃ bly introduced that affect the user ’ s visual experience. Therefore ， building an effective and accurate LFI quality assessment method to evaluate LFIs is necessary. Based on the two representations of LFIs ， namely ， pseudo - videos （ PVs ） and e - bipolar plane images （ EPIs ）， a blind LFI quality assessment method that combines disparity compensation and 3D data processing is proposed. First ， a disparity compensation module is used to process the PV sequences of an LFI ， and then the PV sequences following disparity compensation are processed using 3D - discrete wavelet transform and 3D - mean subtracted contrast normal⁃ ized. The frequency and spatial features are then extracted. In addition ， the features of a histogram of ori⁃
Development of a Dispersion Relation Equation - Preserving Pure Advection Scheme for Solving the Navier-Stokes Equations with/Without Free Surface

In this article we develop a dispersively more accurate pure advection scheme and apply it to properly simulate incompressible free surface flow equations. According to Clebsch velocity decomposition, the incompressible flow equations are decomposed into the equations accounting respectively for the flow potential, rotation, and dissipation. For the Euler equation, the midpoint implicit symplectic time integrator is applied to approximate the temporal derivative term. For the sake of reducing numerical dispersion error, the upwinding scheme is developed to minimize the difference between the numerical and exact dispersion relation equations for the time-dependent pure advection equation in wavenumber space.
Pattern of Antibiotic Use among Hospitalized Patients at a Level One Multidisciplinary Care Hospital

Background: Antimicrobial resistance is one of the world’s most serious health issues. Antibiotic resistance, excessive drug expense, and an increased risk of adverse reactions are all common outcomes of incorrect antibiotic prescribing. The goal of this study was to evaluate the prevalence of antibiotic prescriptions for inpatients to find areas for improvement. Methods: A retrospective study at Emergency Clinical County Hospital of Oradea, Romania was performed for five years between 2017 and 2021. Data was collected using medical records of the patients and reports from the pharmacy. Antibiotic consumption was expressed as DDD/100 BD according to the World Health Organization (WHO) by antibiotics, classes, and AWaRe classification. Results: The prevalence of antibiotic prescription was 53.8% during five years evaluated with a significant increase in 2021. A total of 13,677.42 DDD/100 BD antibiotics were prescribed, especially for surgical and medical prophylaxes. The most prescribed antibiotics were ceftriaxone, followed by metronidazole, and cefuroxime but there were some differences between years and wards. The most frequent antibiotic classes prescribed were cephalosporins (43.73%). The use of Watch Group antibiotics was high in all wards (59.69%). Conclusions: The prevalence of antibiotic use was high with cephalosporins being the most prescribed antibiotics. As a result, interventions are required.
Quantum Spectroscopy of the Low-Field Oscillations in the Surface Impedance

We present here a detailed theory of electronic surface quantum states in a low magnetic field, as well as of their effects on the microwave surface impedance. A marked oscillatory structure in the microwave absorption as a function of magnetic field has been carefully observed by Khaikin and by Koch et al. The quantized magnetic surface levels are bound states of electrons trapped against the surface by the magnetic field. Even though these levels are somewhat analogous to Landau levels, they have considerably different properties. Resonant transitions between these levels give rise to a series of spectral lines in the surface impedance, just as cyclotron resonance is a result of transitions between Landau levels. The present effect is essentially quantum in nature, however. A considerable amount of quantitative information can be extracted from the experimental data. The Fermi velocity, radius of curvature of the Fermi surface, and mean free time at certain points on the Fermi surface can be obtained. Most novel, however, is the fact that one can extract information on the scattering of electrons by the surface, as a function of impact angle.
Technologies and applications of single-cell DNA methylation sequencing

DNA methylation is the most stable epigenetic modification. In mammals, it usually occurs at the cytosine of CpG dinucleotides. DNA methylation is essential for many physiological and pathological processes. Aberrant DNA methylation has been observed in human diseases, particularly cancer. Notably, conventional DNA methylation profiling technologies require a large amount of DNA, often from a heterogeneous cell population, and provide an average methylation level of many cells. It is often not realistic to collect sufficient numbers of cells, such as rare cells and circulating tumor cells in peripheral blood, for bulk sequencing assays. It is therefore essential to develop sequencing technologies that can accurately profile DNA methylation using small numbers of cells or even single cells. Excitingly, many single-cell DNA methylation sequencing and single-cell omics sequencing technologies have been developed, and applications of these methods have greatly expanded our understanding of the molecular mechanism of DNA methylation. Here, we summaries single-cell DNA methylation and multi-omics sequencing methods, delineate their applications in biomedical sciences, discuss technical challenges, and present our perspective on future research directions.
Cloudlet Based Computing Optimization Using Variable-Length Whale Optimization and Differential Evolution

Cloudlet-based optimization involves deploying a set of cloudlets in an environment and assigning user tasks to optimize various metrics, including energy consumption, quality of service (QoS), and cost. Typically, approaches deal with them separately, which might cause sub-optimality. Furthermore, assuming the fixed location of the cloudlets will limit the dynamic adaptability of the problem. Enabling more optimality and adaptability to the dynamic nature of cloudlet-based computing, we propose a novel Variable-Length multi-objective Whale optimization Integrated with Differential Evolution designated as VL-WIDE. Unlike the existing optimization algorithm, VL-WIDE features the capability of searching different lengths of solutions to cover the variable number of cloudlets for deployment. Furthermore, it enables a non-dominated evaluation of solutions based on four objectives using crowding distance for selection. It provides an application-oriented solutions repair operator for repairing non-valid solutions and assuring that all solutions are generated in the feasible region. The proposed algorithm enables moving the cloudlets among pre-defined locations to increase the quality of service according to the change in the user density caused by user mobility. Comparing this developed algorithm with other algorithms shows its superiority in multi-objective optimization (MOO) evaluation metrics. VL-WIDE has provided the best in a number of non-dominated solutions and delta metrics and was competitive in other metrics.
Greenhouse-Grown Tomatoes: Microbial Diseases and their Control Methods: A Review

The cultivation of tomatoes in greenhouse structures is becoming increasingly common as a crop production system. However, the environmental conditions inside a greenhouse favour the development of microbial diseases. These diseases have an adverse effect on the tomato yield and can lead to serious economic losses. This review will give an insight into the major diseases affecting greenhouse-grown tomatoes, the respective causal agents and recommended control strategies. Some of the major diseases are of a bacterial, fungal, viral or nematode origin and include bacterial spot and speck, bacterial canker, early blight, gray mold, leaf mold, powdery mildew, tomato mosaic virus, tomato big bug and root knot. For each disease, the symptoms and risk factors responsible for disease development are described. In addition, the different structural designs and set-ups of tomato greenhouses are covered along with their advantages and limitations, especially any adverse effects on yield and susceptibility to disease. Although conventional control measures are discussed, greater emphasis is laid on the use of alternative biocontrol measures that include Effective Microorganisms, natural antimicrobials and nanobiopesticides. Moreover, information gathered in this review is based on a combination of available literature and expert guidance. This compilation is hoped to be instructive for tomato growers opting for greenhouse farming and assist them in the application of timely and more effective control measures
Image super-resolution reconstruction based on residual compensation combined attention network

: For image reconstruction, the residual network ignores part of the residual information when extracting features. We propose an image super-resolution reconstruction based on residual compensation joint attention network (RCCN). Firstly, we construct a three-way residual network for compensating the feature information of the standard residual network; secondly, we design a joint attention module to complement the pixel-level image attention information by 3D attention while the channel attention learns the channel weight information; finally, our method has clearer results compared with other advanced methods, and the objective evaluation indexes are all greatly improved.
2.19 Nonlinear and Adaptive Control

This section discusses the conceptual approaches and tools of adaptive control and their applications to nonlinear processes. Adaptive control can be thought of as a system that automatically designs a control system. This technique has considerable potential for applications where the processes being controlled are not well understood or have significant nonlinearities or time-varying parameters. Adaptive control utilizes the natural steps of control system design. These include process modeling and identification (Section 2.16), relative gain calculations (Section 2.25), controller design (for example, self-tuning controllers, Section 2.29), and optimization (Section 2.20). At present, these approaches and ideas are being extended to include such new tools as artificial intelligence and as expert systems (Section 2.8), neural networks (Section 2.18), fuzzy logic (Section 2.31), and genetic algorithms (Section 2.10), among others. Therefore, it is suggested that all of these sections be studied if a thorough understanding of the subject matter is desired.
Unsupervised Seismic Random Noise Suppression Based on Local Similarity and Replacement Strategy

Improving the signal-to-noise ratio and suppressing random noise in seismic data is critical for high-precision processing. Although deep learning-based algorithms have gained popularity as denoising methods, they suffer from poor generalization ability, resulting in high training set construction cost and computation cost. To address this problem, we propose an unsupervised learning-based denoising method that includes an improved denoising strategy based on local similarity and replacement, a corresponding training method, and an improved network based on UNet. Our training method takes advantage of network convergence and allows direct training on the test region, effectively solving the problems associated with denoising methods using generalization ability while improving training performance. In addition, our network is specifically designed for the training method and incorporates various improvements that could further enhance the training effectiveness. Our method outperforms traditional denoising methods, as demonstrated by tests on synthetic and field data, with superior performance in random noise attenuation and reflection event reconstruction.
Poor Treatment Response in Panic Disorder Patients with Suicide Attempts and Their Symptom Network Characteristics

Background. Panic disorder (PD) is associated with suicidality. Depression has been suggested as a link between PD and suicide; however, this remains controversial. Comprehensive research on the history of suicide attempt (SA) in patients with PD is scarce. We investigated the clinical characteristics of SA in patients with PD using PD-related assessments and network approaches. Methods. A total of 1151 participants were enrolled, including 755 patients with PD (97 with SA (PD+SA) and 658 without SA (PD-SA)) and 396 healthy controls. The Scale for Suicide Ideation and Panic Disorder Severity, Anxiety Sensitivity Inventory, and other PD-related measures were also administered. We compared symptom severity and analyzed the pharmacological treatment response in patients with PD with and without SA. Network analysis was used to estimate the centrality, stability, and network structures of the nodes. Results. Our results revealed that the scores for panic and depressive symptoms, pathological worry, anxiety sensitivity, and the frequency of early trauma were significantly higher in the PD+SA group than in the PD-SA group. Multiple linear regression analysis revealed that short- and long-term pharmacological treatment responses were significantly poorer in the PD+SA group. Network analysis showed that fear of cognitive dyscontrol (FCD), as a cognitive aspect of anxiety sensitivity, was the central symptom through strength, expected influence (one and two steps), randomized shortest path betweenness, and eigenvector centrality measures in the PD+SA group. In contrast, depression was the central symptom of patients with PD-SA. Conclusion. Our study suggests that a history of SA could be associated with high panic-symptom severity and poor pharmacological treatment response in patients with PD and that FCD is the most central symptom in the PD+SA network. Central symptoms, such as cognitive aspects of AS in patients with PD+SA, may be clinically effective as potential targets for intervention in patients with PD at risk of or suffering from suicidality.
Modeling and Simulation of Polarization Mode Dispersion and Polarization Dependent Loss

Novel theoretical formulations and efficient simulation methods for polarization-mode dispersion (PMD) and polarization-dependent loss (PDL) that are directly applicable to optical network design are developed. In particular, a formalism based upon the Magnus expansion is advanced for the determination of the frequency evolution of the Mueller matrix in terms of increasing orders of PMD and PDL. Several previous models of polarization evolution are shown to be specializations of this more general formalism. A least-squares algorithm that extracts PMD and PDL coefficients from repeated measurements of the output Stokes vector of an optical system for a random set of input polarization states is introduced and subsequently applied to the rapid experimental determination of the probability density of the differential group delay of a fiber-squeezer based PMD emulator. The applicability of Clifford algebra and Pade -approximant techniques to the efficient simulation of the wavelength-dependence of PMD and PDL is also discussed.
MELHORIA DO PROCESSO DE CORREÇÃO GEOMÉTRICA DE IMAGENS CBERS-CCD PELO USO DE AMOSTRAS GEORREFERENCIADAS CLASSIFICADAS

As imagens da serie de satelites CBERS sao distribuidas gratuitamente, mas para que seja possivel utiliza-las, e necessario aplicar um metodo de correcao geometrica. E proposta uma melhoria do processo de correcao automatica de forma a selecionar as melhores amostras de referencia a partir das quais e possivel definir pontos de controle usados para o calculo dos parâmetros do modelo usado na correcao. Para demonstrar a eficacia, o metodo proposto e aplicado em um conjunto de imagens CBERS usando as amostras de imagens selecionadas.
Effect of UV-B irradiated vitamin D enriched yeast supplementation on milk performance and blood chemical profiles in dairy cows

Objective The objective was to evaluate the effects of UV-B irradiated vitamin D-enriched yeast supplementation on milk yield, milk composition, vitamin D in milk, milk fatty acids, blood chemistry, and 25(OH)D status in dairy cows. Methods Six Thai Friesian cows (milk production, 11.2±2.0 kg/d; body weight, 415.0±20.0 kg; and days in milk, 90.0±6.0) were allocated to each treatment in a 3×3 Latin square design, with three treatments and three periods. Each period of the Latin square lasted 49 days consisting of 14 days for diet adaptation and 35 days for sample collection. Dairy cows were randomly assigned to one of three treatments: i) feeding a basal diet without yeast (CON); ii) basal diet + 5 g of live yeast (75 IU/head/d of vitamin D2; LY); and iii) basal diet + 5 g of UV-B irradiated vitamin D enriched yeast (150,000 IU/head/d of vitamin D2; VDY). Feed intake and milk production were recorded daily, milk sample collection occurred on days 14 and 35 of each collection period, and blood plasma was collected on days 0, 7, 14, 21, 28, and 35 of each collection period. Results The results show that after a trial period of 14 and 35 days, the VDY group had significantly higher vitamin D content in milk than the LY and CON groups (376.41 vs 305.15, 302.14 ng/L and 413.46 vs 306.76, 301.12 ng/L, respectively). At days 7, 14, 21, 28, and 35 of the experiment, cows fed the VDY group had significantly higher 25(OH)D2 status in blood than the CON and LY groups (51.07 vs 47.16, 48.05 ng/mL; 54.96 vs 45.43, 46.91 ng/mL; 56.16 vs 46.87, 47.16 ng/mL; 60.67 vs 44.39, 46.17 ng/mL and 63.91 vs 45.88, 46.88 ng/mL), respectively. Conclusion In conclusion, UV-B irradiated vitamin D-enriched yeast supplementation could improve vitamin D content in the milk and 25(OH)D status in dairy cows during the lactation period.
Development of a Gas-Liquid Equilibrator for Estimating CO2 Flux at the Ocean Surface

Abstract A system for measuring partial pressure of CO2 in seawater (pCO2) has been developed as a part of a missing-sink elucidation study. The most important part of this system is the multistage bubbling gas–liquid equilibrator. This equilibrator has four independent equilibrate cells in parallel. Seawater flows into each cell in parallel, while the bubbled carrier gas stream passes through every cell in series. The carrier gas circuit of a nondispersive infrared gas analyzer is opened to the atmosphere to keep the pressure of carrier gas at a barometric pressure. The present system can measure pCO2 continuity with sample water of 24 L min−1. Furthermore, a performance test was carried out to examine the degree of equilibrium achieved. The results showed an 83% equilibrium per cell. This indicates that the uncertainty of this equilibrator is 1 μatm. The correlation coefficient between the deviation of pH and that of pCO2 observed with this system was −0.96.