Small Amount Of Sample Research Articles

Versatility of Raman spectroscopy for studies on the back-end of the nuclear fuel cycle

AbstractIn recent years, Raman spectroscopy has been proven to be a highly versatile characterization technique for nuclear materials research. This sensitive technique possesses, among others, two relevant features that comply with the safety conditions required when handling nuclear materials: its flexibility allows for remote, in situ and ex situ analysis, and its relative ease of use implies small sample quantities and limited effort for sample preparation. In this work, we present the acquisition protocol and data processing necessary for obtaining important information within the back-end of the nuclear fuel cycle. Specifically, we focus on research studies on the advanced characterization of nuclear fuels and the development of hydrometallurgical separation processes. The results described here were obtained by using different nuclear fuels analogs, but the acquisition protocol and data processing described can be applied to the real nuclear fuel cycle. Graphical abstract

Predicting the productivity of fractured horizontal wells using few-shot learning

Predicting the productivity of multistage fractured horizontal wells plays an important role in exploiting unconventional resources. In recent years, machine learning (ML) models have emerged as a new approach for such studies. However, the scarcity of sufficient real data for model training often leads to imprecise predictions, even though the models trained with real data better characterize geological and engineering features. To tackle this issue, we propose an ML model that can obtain reliable results even with a small amount of data samples. Our model integrates the synthetic minority oversampling technique (SMOTE) to expand the data volume, the support vector machine (SVM) for model training, and the particle swarm optimization (PSO) algorithm for optimizing hyperparameters. To enhance the model performance, we conduct feature fusion and dimensionality reduction. Additionally, we examine the influences of different sample sizes and ML models for training. The proposed model demonstrates higher prediction accuracy and generalization ability, achieving a predicted R2 value of up to 0.9 for the test set, compared to the traditional ML techniques with an R2 of 0.13. This model accurately predicts the production of fractured horizontal wells even with limited samples, supplying an efficient tool for optimizing the production of unconventional resources. Importantly, the model holds the potential applicability to address similar challenges in other fields constrained by scarce data samples.

Is Floppy Eyelid Syndrome predictive of Intraoperative Floppy Iris Syndrome? A prospective and translational study

Intraoperative floppy iris syndrome (IFIS) is defined as an excessive billowing of the iris during cataract surgery. Floppy eyelid syndrome is defined as an excessive hyperlaxity of the eyelids. Based in our daily experience, we suspected FES to be associated with IFIS. This association has been investigated. The goal of the study was to explore whether FES was predictive of IFIS. We conducted a prospective observational single-center study at the University Hospital of Nice. IFIS and FES were investigated in patients undergoing cataract surgery from November 2019 to May 2021. In addition, tarsus and iris samples were harvested in 2 fresh cadavers, and Verhoeff staining was used to identify elastin fibers. We included 452 eyes (n=312 patients, 50.9% male) with a mean age of 71.7years (±11.4). IFIS was diagnosed in 88 (19.5%) patients, including 20 (4.4%) grade 1, 34 (7.5%) grade 2, and 33 (7.3%) grade 3. FES was diagnosed in 35 (7.7%) patients. PEX was found in 23 (5.1%) patients. On multivariate analysis, FES (P<0.001), pseudo exfoliation (P=0.017), intracameral dilatation (P<0.004), senior surgeons (P=0.009) and α1-ARA (P<0.001) were associated with IFIS. Elastin fibers were identified in small amounts in the tarsus samples but not in the iris samples. FES is predictive of IFIS. Surgeons should be aware of this association to prevent intraoperative complications.

Leveraging the potential of 1.0-mm i.d. columns in UHPLC-HRMS-based untargeted metabolomics.

Untargeted metabolomics UHPLC-HRMS workflows typically employ narrowbore 2.1-mm inner diameter (i.d.) columns. However, the wide concentration range of the metabolome and the need to often analyze small sample amounts poses challenges to these approaches. Reducing the column diameter could be a potential solution. Herein, we evaluated the performance of a microbore 1.0-mm i.d. setup compared to the 2.1-mm i.d. benchmark for untargeted metabolomics. The 1.0-mm i.d. setup was implemented on a micro-UHPLC system, while the 2.1-mm i.d. on a standard UHPLC, both coupled to quadrupole-orbitrap HRMS. On polar standard metabolites, a sensitivity gain with an average 3.8-fold increase over the 2.1-mm i.d., along with lower LOD (LODavg 1.48ng/mL vs. 6.18ng/mL) and LOQ (LOQavg 4.94ng/mL vs. 20.60ng/mL), was observed. The microbore method detected and quantified all metabolites at LLOQ with respect to 2.1, also demonstrating good repeatability with lower CV% for retention times (0.29% vs. 0.63%) and peak areas (4.65% vs. 7.27%). The analysis of various samples, in both RP and HILIC modes, including different plasma volumes, dried blood spots (DBS), and colorectal cancer (CRC) patient-derived organoids (PDOs), in full scan-data dependent mode (FS-DDA) reported a significant increase in MS1 and MS2 features, as well as MS/MS spectral matches by 38.95%, 39.26%, and 18.23%, respectively. These findings demonstrate that 1.0-mm i.d. columns in UHPLC-HRMS could be a potential strategy to enhance coverage for low-amount samples while maintaining the same analytical throughput and robustness of 2.1-mm i.d. formats, with reduced solvent consumption.

6-Methoxy-2-Naphthoate as a Standard Chromophore for Chiroptical Studies by Fluorescence-Detected Exciton-Coupled Circular Dichroism.

This study investigated the applicability of fluorescent chromophores for exciton-coupled circular dichroism (ECCD) exploiting fluorescence-detected circular dichroism (FDCD). FDCD had been previously reported useful in allowing the sensitive detection of ECCD in favorable conditions. However, fluorescence detection may prevent applications of the combined method especially when solutions are polarized in emission. Even without polarization of emission, FDCD deviates from circular dichroism (CD) in some cases when the fluorophore of interest interacts with nonfluorescent chromophore. Herein, it was confirmed that employing 6-methoxy-2-naphthoate always yielded interpretable exciton-coupled FDCD spectra even when coupling with nonfluorescent p-substituted benzoates. The 6-methoxy-2-naphthoate chromophore (6-MN) is prescribed in special cases when only a small amount of sample is available for determining the absolute stereochemistry by the CD exciton chirality method observed by FDCD.

Spectroscopic techniques and chemometrics for ink analysis: Document analysis application

This study represents a methodology to determine the falsified documents via a combined method of spectroscopic techniques and chemometrics. The techniques of UV–Vis and FTIR-ATR spectroscopies and principal component analysis methods have been applied to black, blue, and red ballpoint pens available in the Türkiye market. The analysis results of the applied spectroscopic techniques were found to be consistent with each other for the examined eleven ink samples from three different brands, and it was observed that FTIR-ATR spectroscopy had higher discriminative power. A dried sample preparation technique developed for small amounts of samples for FTIR-ATR measurements and the increased the sensitivity of FTIR-ATR technique was associated with this sample preparation method. Statistical techniques showed that the UV–Vis technique proves useful outcomes in distinguishing inks according to their colors, whereas the FTIR-ATR technique is valuable for identifying ink brands. Additional analysis of the sub-brand of black inks and falsified old-dated check sample analysis validated that our methodology has the potential to classify and identify ballpoint inks in forensic applications. Due to the limited sample quantity available for analysis in real samples, only FTIR-ATR analysis was possible, and the results demonstrated that document forgery could be detected from small parts of samples in the document. When we look at the overall outcome of this study, a comprehensive methodology enriched with statistical calculations has been proposed that can be applied even in a laboratory with limited resources, having only UV–Vis and FTIR-ATR capabilities.

Mask-guided BERT for few-shot text classification

Transformer-based language models have achieved significant success in various domains. However, the data-intensive nature of the transformer architecture requires much labeled data, which is challenging in low-resource scenarios (i.e., few-shot learning (FSL)). The main challenge of FSL is the difficulty of training robust models on small amounts of samples, which frequently leads to overfitting. Here we present Mask-BERT, a simple and modular framework to help BERT-based architectures tackle FSL. The proposed approach fundamentally differs from existing FSL strategies such as prompt tuning and meta-learning. The core idea is to selectively apply masks on text inputs and filter out irrelevant information, which guides the model to focus on discriminative tokens that influence prediction results. In addition, to make the text representations from different categories more separable and the text representations from the same category more compact, we introduce a contrastive learning loss function. Experimental results on open-domain and medical-domain datasets demonstrate the effectiveness of Mask-BERT. Code and data are available at: github.com/WenxiongLiao/mask-bert

A Synergistic Overview between Microfluidics and Numerical Research for Vascular Flow and Pathological Investigations.

Vascular diseases are widespread, and sometimes such life-threatening medical disorders cause abnormal blood flow, blood particle damage, changes to flow dynamics, restricted blood flow, and other adverse effects. The study of vascular flow is crucial in clinical practice because it can shed light on the causes of stenosis, aneurysm, blood cancer, and many other such diseases, and guide the development of novel treatments and interventions. Microfluidics and computational fluid dynamics (CFDs) are two of the most promising new tools for investigating these phenomena. When compared to conventional experimental methods, microfluidics offers many benefits, including lower costs, smaller sample quantities, and increased control over fluid flow and parameters. In this paper, we address the strengths and weaknesses of computational and experimental approaches utilizing microfluidic devices to investigate the rheological properties of blood, the forces of action causing diseases related to cardiology, provide an overview of the models and methodologies of experiments, and the fabrication of devices utilized in these types of research, and portray the results achieved and their applications. We also discuss how these results can inform clinical practice and where future research should go. Overall, it provides insights into why a combination of both CFDs, and experimental methods can give even more detailed information on disease mechanisms recreated on a microfluidic platform, replicating the original biological system and aiding in developing the device or chip itself.

Clinical metabolomics: current state and prospects in Russia.

Using analytical technologies it is possible now to measure the entire diversity of molecules even in a small amount of biological samples. Metabolomic technologies simultaneously analyze thousands of low-molecular substances in a single drop of blood. Such analytical performance opens new possibilities for clinical laboratory diagnostics, still relying on the measurement of only a limited number of clinically significant substances. However, there are objective difficulties hampering introduction of metabolomics into clinical practice. The Institute of Biomedical Chemistry (IBMC), consolidating the efforts of leading scientific and medical organizations, has achieved success in this area by developing a clinical blood metabogram (CBM). CBM opens opportunities to obtain overview on the state of the body with the detailed individual metabolic characteristics of the patient. A number of scientific studies have shown that the CBM is an effective tool for monitoring the state of the body, and based on the CBM patterns (signatures), it is possible to diagnose and monitor the treatment of many diseases. Today, the CBM creation determines the current state and prospects of clinical metabolomics in Russia. This article, dedicated to the 80th anniversary of IBMC, is a review of these achievements focused on a discussion of their implementation in clinical practice.

Using long columns to quantify over 9200 unique protein groups from brain tissue in a single injection on an Orbitrap Exploris 480 mass spectrometer

The most exciting advancement in LC-MS/MS-based bottom-up proteomics has centered around enhancing mass spectrometers. Among these, the latest and most advanced mass spectrometer for bottom-up proteomics is the Orbitrap Astral that has the highest scan rate to accelerate throughput and the highest sensitivity to handle a very small amount of peptide samples and to achieve deeper proteomics. However, its affordability remains a challenge for most laboratories. While significant strides have been made in improving mass spectrometry, advancing liquid chromatography (LC) to achieve deeper proteomics has not achieved significant successes since the innovation of Multidimensional Protein Identification Technology (MudPIT) in 2001. To achieve deeper proteomics in a less labor-intensive and more reproducible approach while using a more cost-effective mass spectrometer, such as the Orbitrap Exploris 480, we evaluated trap columns as long as 40 cm and analytical column as long as 600 cm besides sample loading amount, gradient time, and analytical column particle size to enable a fractionation-free method for a single injection to obtain deeper proteomics. The length of trap and analytic columns is the key factor. Using a 30 cm trap column and 250 cm analytical column with other optimized LC conditions, we quantified over 9200 unique protein groups from brain tissue in a single injection using a 24-h gradient on an Orbitrap Exploris 480 mass spectrometer.

Next-generation sequencing has diagnostic utility in challenging small/flat urothelial lesions

Small/flat urothelial lesions are challenging and currently available ancillary immunohistochemistry testing often cannot reliably distinguish between reactive lesions and urothelial carcinoma (UCa). UCa has a characteristic molecular profile, but small/flat urothelial lesions are typically considered too small to perform next generation sequencing (NGS). Herein, we present our institution's experience with utilizing comprehensive DNA-based NGS to evaluate small/flat urothelial lesions (n = 13 cases). NGS was ordered on 7/13 small/flat urothelial lesions initially diagnosed as urothelial atypia, ordered by the pathologist to aid in further diagnosis; the remaining 6/13 cases were diagnosed as urothelial carcinoma in situ (uCIS), ordered by a treating oncologist. The test was considered as adding value if it yielded pathogenic or likely pathogenic alterations previously associated with urothelial carcinoma in the literature. Macroscopic dissection was determined necessary in all cases and obtained either by scraping (7), punch biopsy (5) or scooping (1) of paraffin tissue blocks. In 4/13 cases, tumor content was considered low (<25%); in 2/13 cases, DNA quantity yield was considered below optimal (<250 ng); all cases met required DNA quantity for testing (>50 ng). Mean target coverage ranged: 498 to 985 (optimal >500 reads). NGS testing identified mutations compatible with urothelial carcinoma in all 7 cases initially diagnosed as atypical; and in one case, the tumor recurred as a lung metastasis. All 6 uCIS had NGS testing results concordant with UCa. In conclusion, despite small sample quantity with low tumor content and DNA concentration yield, NGS testing with appropriate methodology can be considered in the setting of small/flat urothelial lesions to aid in diagnosis or per oncologist request and yield interpretable results.

Direct measurement of magnetocaloric effect (MCE) in frustrated Gd-based molecular complexes

AbstractGeneration of low temperatures below 1 K has been required for applications and fundamental research, given this, development of new materials utilized for demagnetization cooling has extensively been performed in recent years. Here, we studied two polynuclear Gd3+-based molecular compounds of Gd0.33[Gd4(OH)4(OAc)3][Rh4Zn4(L-cys)12]·32H2O (1Gd) and Gd0.33[Gd4(OH)4(OAc)3][Ir4Zn4(L-cys)12]·28H2O (2Gd) (L-cys = L-cysteinate) which show paramagnetic even at low temperatures due to their frustrated arrangement of Gd3+ ions. We discuss the magnitude of the magnetocaloric effect (MCE) in them inferred from the isothermal magnetic entropy change ($${\Delta S}_{\text{M}}$$ Δ S M ) from isothermal magnetization data. The − $$\Delta S_{{\text{M}}}^{{{\text{max}}}}$$ Δ S M max of 1Gd and 2Gd are 15.15 J kg−1 K−1 and 17.49 J kg−1 K−1 occur at 2.0 K under an applied field from 0 to 7 T, respectively. We also discussed the results of heat capacity measurement under magnetic fields to confirm the validity of the entropy change for 1Gd. Furthermore, with an aim of detecting their MCE directly, we have developed a new non-magnetic and metal-free magnetocaloric measurement cell. The adiabatic temperature change ($$\Delta T_{{{\text{ad}}}}$$ Δ T ad ) occurs in a small amount of sample on an order of 102-microgram with the application and removal of various magnitude magnetic fields starting from several initial temperatures were detected directly, to evaluate the potential of them to be a refrigerant for an adiabatic demagnetization refrigerator. The instrumental design for direct measurements of MCE is described along with the construction details.

Fluorescence microfluidic system for real-time monitoring of PS and PVC sub-micron microplastics under flowing conditions

Plastics, recognized for their convenience, disposability, and recyclability, have emerged as a significant ecological challenge, particularly with the prevalence of microplastics (MPs, 1 μm – 5 mm) and sub-micron MPs (100 – 1000 nm) in natural environments. While extensive research has focused on their occurrence and environmental impacts, quantification methods developed for MPs exhibit limitations when applied to sub-micron MPs due to their smaller size. This study addresses these limitations by introducing a novel monitoring system that integrates fluorescence labeling with a microfluidic device and particle tracking software, enabling automated quantification and size measurement of both spherical and fragmented MPs of size in the sub-micrometer range. Results showed that the developed system enabled fast quantification and size measurement of 500- and 1000-nm polystyrene (PS) sub-micron MP beads and fragmented PS and polyvinyl chloride (PVC) sub-micron MPs. Additionally, fluorescence labeling enabled the real-time discrimination of PS and PVC sub-micron MPs. Lastly, the microfluidic system allowed the monitoring of sub-micron MPs within a small quantity of water samples. This automated system has a high potential for swift and real-time monitoring of sub-micron MPs in the environment. By enhancing our ability to detect and quantify sub-micron MPs, this study contributes to a more comprehensive understanding of their presence and distribution in environmental systems.

Miniaturized Sniffing Device based on an Array of Fluorescent Carbon Quantum Dots and Metallic Nanoclusters Efficiently Identifies Hematologic Malignancy in Adults.

The study demonstrates the potential of an optical nose made by depositing an array of fluorescent nanomaterials on a paper substrate for the early detection of leukemia in adults. This is based on the fact that blood volatile organic compounds (VOCs) are useful leukemia biomarkers. The integrated design was miniaturized and comprised both sensing zones and a sample holding zone, which were installed on a small sheet of paper within a miniature cubic reaction chamber fabricated by using 3D printing technology. The sensing device, comprising seven fluorescent sensing elements, namely, metal nanoclusters, quantum dots, and carbon dots was capable of detecting VOCs in the blood headspace and providing a colorimetric signature that could discriminate between blood samples from healthy and cancerous individuals. A total of 70 new leukemia cases and 51 healthy controls aged 20-50 years were studied. The device required a 60 μL portion of the blood sample and reacted to blood VOCs after 3 h when kept at 50 °C. The imaging data from the device was processed by linear discriminant analysis, and the results confirmed efficient identification of patient samples from healthy samples with 100% accuracy. Overall, the array system is noninvasive (or minimally invasive), portable, fast, inexpensive, and requires only a small amount of blood sample.

Seabed characterization based on the statistical classification using the seabed reflection amplitudes of sub-bottom profiler data

The seabed reflection amplitudes (SRAs) extracted from the sub-bottom profile have a strong correlation with the types and physical properties of the seabed sediments. In this paper, the SRAs distribution of classified seabed sediments is statistically obtained by calibration with seabed sampling results, discovering that SRAs on different seafloor sediment types exhibit Rayleigh distributions with varying parameters. Firstly, SRAs are compensated and enhanced, to improve their identification. Then, a novel classification method based on K–S test was proposed. This method measures the maximum distance between the cumulative distribution functions (CDF) of the unknown seabed and the calibrated sediment SRAs to check whether unknown samples belong to any of the known types. This proposed method only requires a small amount of seabed samples to automatically classify the seabed with high accuracy, and the model is simple, robust, and provides classification confidence.

Improving the triphenylphosphine/triphenylphosphine oxide (TPP/TPPO)‐based method for the absolute and accurate quantification by FTIR‐ATR of hydroperoxides in oils or lipid extracts

AbstractResearch on natural sources of polyunsaturated fatty acids (PUFAs) for both food and nutraceutical prospects has significantly grown in recent years. Some plant oils and lipid extracts contain carotenoids, xanthophylls, sterols, and/or phenolic compounds that can provoke a lipid hydroperoxides (LOOHs) overestimation when quantifying them using nonselective colorimetric assays. Herein, we have optimized a mid‐infrared method using Fourier‐transform infrared spectroscopy coupled with attenuated total reflectance (ATR) to quantify LOOHs in oils or lipid extracts. This method is based on the conversion of triphenylphosphine (TPP) to triphenylphosphine oxide (TPPO) in the presence of hydroperoxides, with a direct assessment of TPPO levels following the formation of an oil film on the ATR crystal's surface, allowing for a low detection limit of 0.5 mmol of LOOH kg−1. The concentration of oil and TPP, as well as the reaction time, were optimized. It was demonstrated that the presence of pigments, unsaponifiable compounds, phenolics, and/or PUFAs on oils, do not disrupt the analysis. Furthermore, the stoichiometry of the TPP/LOOH reaction was examined, confirming the reliability of the method in detecting various forms of hydroperoxides. An accelerated oxidation study was carried out and the hydroperoxide contents measured using TPP/TPPO were found to be comparable to those obtained using the ferric thiocyanate method. Our method offers a fast, simple, robust, and sensitive approach to accurately quantify hydroperoxides, regardless of the chemical composition of oil or lipid extracts.Practical Application: The hydroperoxide assay method outlined in this study allows for the rapid and straightforward detection of hydroperoxides in pure oil matrices. The method's elevated sensitivity facilitates the early identification of oxidation indicators in oils, especially those with significant carotenoid or xanthophyll contents since these compounds may affect the results when using methods based on colorimetric quantification of hydroperoxides. This accurate, precise, and reproducible approach requires only small quantities of test samples and chemical products, making it well suited to routine application in laboratories and industrial environments.

A method for detecting gene doping in horse sports without DNA extraction

AbstractGene doping is prohibited in horse sports and can involve the administration of exogenous genes, called transgenes, to postnatal animals. Quantitative polymerase chain reaction (qPCR) methods have been developed to detect gene doping; however, these generally require DNA extraction from the plasma prior to qPCR. In this study, we developed two methods, direct droplet digital PCR (ddPCR) and nested ddPCR, to detect the equine erythropoietin (EPO) transgene without DNA extraction. Direct ddPCR used pretreated plasma and PCR to detect the EPO transgene spiked at 10 copies/μL. Nested ddPCR utilised pre‐amplification using nontreated plasma, purification of PCR products and PCR to detect the EPO transgene spiked at 1 copy/μL in plasma. These methods successfully detected the EPO transgene after intramuscular injection into horses. Since each method has different detection sensitivity, the combined use of direct ddPCR for screening and nested ddPCR for confirmation may complement each other and prevent the occurrence of false positives, allowing the reliable detection of gene‐doped substances. One advantage of these methods is the small amount of sample required, approximately 2.2–5.0 μl, owing to the lack of a DNA extraction step. Therefore, these tests could be applied to small volume samples as an alternative to conventional gene doping tests.

Accessing self-diffusion on nanosecond time and nanometre length scales with minute kinetic resolution.

Neutron spectroscopy uniquely and non-destructively accesses diffusive dynamics in soft and biological matter, including for instance proteins in hydrated powders or in solution, and more generally dynamic properties of condensed matter on the molecular level. Given the limited neutron flux resulting in long counting times, it is important to optimize data acquisition for the specific question, in particular for time-resolved (kinetic) studies. The required acquisition time was recently significantly reduced by measurements of discrete energy transfers rather than quasi-continuous neutron scattering spectra on neutron backscattering spectrometers. Besides this reduction in acquisition times, smaller amounts of samples can be measured with better statistics, and most importantly, kinetically changing samples, such as aggregating or crystallizing samples, can be followed. However, given the small number of discrete energy transfers probed in this mode, established analysis frameworks for full spectra can break down. Presented here are new approaches to analyze measurements of diffusive dynamics recorded within fixed windows in energy transfer, and these are compared with the analysis of full spectra. The new approaches are tested by both modeled scattering functions and a comparative analysis of fixed energy window data and full spectra on well understood reference samples. This new approach can be employed successfully for kinetic studies of the dynamics focusing on the short-time apparent center-of-mass diffusion.

Bead-based spontaneous Raman codes for multiplex immunoassay

In the immunoassay process, for fulfilling the need to identify multiple analytes in a small amount of complex sample matrix, it is desirable to develop highly efficient and specific multiplex suspension array technology. Raman coding strategy offers an attractive solution to code the suspension arrays by simply combing narrow spectral bands with stable signal intensities through solid-phase synthesis on the resin beads. Based on this strategy, we report the bead-based spontaneous Raman codes for multiplex immunoassay. The study resulted in superior selectivity of the Raman-encoded beads for binding with single and multiple analytes, respectively. With the use of mixed types of Raman-encoded immunoassay beads, multiple targets in small amounts of samples were identified rapidly and accurately. By confirming the feasibility of bead-based spontaneous Raman codes for multiplex immunoassay, we anticipate this novel technology to be widely applied in the near future.

Boosting active domain adaptation with exploration of samples

Nowadays, the idea of active learning is gradually adopted to assist domain adaptation. However, due to the existence of domain shift, the traditional active learning methods originating from semi-supervised scenarios can not be directly applied to domain adaptation. To solve the problem, active domain adaptation is proposed as a new domain adaptation paradigm, which aims to improve the performance of the model by annotating a small amount of target domain samples. In this regard, we propose an active domain adaptation method named Boosting Active Domain Adaptation with Exploration of Samples (BADA), dividing Active DA into two related issues: sample selection and sample utilization. We design the instability selection criterion based on predictive consistency and the diversity selection criterion. For the remaining unlabeled samples, we design a self-training framework, which screens out reliable samples and unreliable samples through the sample screening mechanism similar to selection criteria. And we adopt respective loss functions for reliable samples and unreliable samples. Experiments show that BADA remarkably outperforms previous active learning methods and Active DA methods on several domain adaptation datasets.