Dual Sampling Research Articles

Ultrafast continuous flow-dialysis for nanoparticle-based drug delivery systems via microfluidic-multiple buffer injector

Nanoparticle-based drug delivery systems (NP-DDS) have emerged as promising carriers for bioactive organic molecules due to their potential in enhancing therapeutic effects. However, traditional purification methods like batch dialysis and diafiltration can alter NP-DDS bio-physicochemical properties due to the lengthy process, prolonged coexistence with organic solvents, and external forces. To address this challenge, we developed an ultrafast flow-dialysis microfluidic module with dual channels separated by a membrane layer. The module leverages multiple buffer injectors (MBIs) to accelerate dialysis by injecting fresh buffer into multiple dialysis zones of bottom channel, refreshing the concentration gradients over the mixture sample in the upper channel to maximize mass transfer efficiency. Using this method for a dual drug-loaded liposome sample containing doxorubicin and curcumin, impurities (such as ethanol and un-trapped drugs) removal and buffer exchange were rapidly terminated within 15 min, continuously operating for ∼ 6 hrs with sequential membrane regeneration process. Importantly, unlike traditional methods, the MBI process maintains the initial uniformity in the size and distribution of liposomes with no leakage of the encapsulated drugs. In vitro HeLa cell tests reveal that the liposomes purified by MBI exhibited significantly higher cellular uptake (1.13 ∼ 1.67 fold), presumably due to the small and uniform size of liposomes, leading to improved anti-tumor effects. Notably, the MBI platform’s versatility was further verified by purifying a mixture of laccase enzyme and by removing the used organic solvents from various carriers (e.g., lipid-based, polymeric, and protein nanoparticles). It is envisioned that the outstanding performance of ultrafast dialysis will enables a continuous-flow downstream process for diverse nano-carriers by intensifying with extra steps in the manufacturing of nanomedicnes, including targeted drug delivery and cancer therapy.

Asymmetric patch sampling for contrastive learning

Asymmetric appearance between positive pair effectively reduces the risk of representation degradation in contrastive learning. However, there are still a mass of appearance similarities between positive pair constructed by the existing methods, thus inhibiting the further representation improvement. To address the above issue, we propose a novel asymmetric patch sampling strategy, which significantly reduces the appearance similarities but retains the image semantics. Specifically, dual patch sampling strategies are respectively applied to the given image. First, sparse patch sampling is conducted to obtain the first view, which reduces spatial redundancy of image and allows a more asymmetric view. Second, a selective patch sampling is proposed to construct another view with large appearance discrepancy relative to the first one. Due to the inappreciable appearance similarities between positive pair, the trained model is encouraged to capture the similarities on semantics, instead of low-level ones.Experimental results demonstrate that our method significantly outperforms the existing self-supervised learning methods on ImageNet-1K and CIFAR datasets, e.g., 2.5% finetuning accuracy improvement on CIFAR100. Furthermore, our method achieves state-of-the-art performance on downstream tasks, object detection and instance segmentation on COCO. Additionally, compared to other self-supervised methods, our method is more efficient on both memory and computation during pretraining. The source code and the trained weights are available at https://github.com/visresearch/aps.

Histopathological changes in testicular lesions in cats.

The aim of this retrospective study was to describe the neoplastic and non-neoplastic lesions seen on histopathological examination of cat testes in Hong Kong between 2018 and 2024. A total of 26 single or dual testes samples were collected from 18 cats by veterinarians at 14 veterinary clinics and submitted for histopathological examination. Laboratory records, including signalment, lesion location, age, breed and histopathological findings, were reviewed for each cat. Neoplastic testicular lesions were seen in three older cats (median age 8.5 years; range 3-17) compared with 18 non-neoplastic lesions in 15 cats (median age 1 year; range 0.5-3). The most common non-neoplastic lesions included inflammation (in the testes, epididymis, tunics and ductus deferens), cryptorchidism, and one case each of polyorchidism and epididymal cyst formation. Two of the testes with inflammation were identified on immunohistochemical staining as feline coronavirus-infected and one pair of testes was associated with the presence of extracellular Gram-negative bacteria at the lesion site. Three different neoplastic lesions were identified, one each of Sertoli cell tumour, leiomyoma and fibrosarcoma. Non-neoplastic testicular lesions were most common, including inflammation, cryptorchidism, polyorchidism and epididymal cysts. To our knowledge, leiomyoma and fibrosarcoma have not been reported in cat testes before and represent important differential diagnoses for testicular lesions.

Electrical conductivity profiling for rapid contamination assessment in unsaturated zones: A case study of an MSW landfill

This study investigates the potential of using bulk soil electrical conductivity (ECbulk) to predict pore water conductivity (ECpw) for assessing the contamination in the unsaturated zone of an old municipal solid waste (MSW) landfill. ECbulk, ECpw, and water content were evaluated with depth at an old MSW landfill in Bhalswa, Delhi, using the Hydraulic Profiling Tool (HPT) and a dual tube soil sampling system. This data was also supplemented by a cone penetration test (CPTu) for high-resolution soil type identification. The correlation of ECbulk with ECpw was primarily influenced by volumetric water content and mineral conductivity with the latter being negligible at this site due to the high conductivity of the leachate. A reasonable linear correlation between normalized EC (ECbulk/ECpw) was observed with volumetric water content, except at low water contents. ECbulk and ECpw profiles with depth indicated attenuation of contaminants in clay layers, while sand layers exhibited constant profile with depth. ECpw was contributed by macro ions generally found in the leachate, including Na+, Mg2+, K+, Ca2+, NH4+, Cl−, SO42−, and HCO3−, as demonstrated by a strong correlation with their cumulative ionic strength. The results indicate that ECbulk profile can be used as a rapid semi-quantitative method for assessing contaminant migration in the unsaturated soil zone, supporting the remediation or control strategies at old landfills.

Adaptive bagging-based dynamic ensemble selection in nonstationary environments

The classification of nonstationary data streams presents a substantial challenge mainly due to the simultaneous presence of class imbalance and concept drift. Ensemble learning is a widely acknowledged approach to address these two problems. Nevertheless, most of the existing methods establish independent strategies for each, ignoring their relationship and interactions, which prevents the corresponding strategies from performing as expected. This paper presents a novel algorithm AB-DES (Adaptive Bagging-based Dynamic Ensemble Selection), which employs bagging technique and dynamic ensemble selection system. In AB-DES, instances are stored to balance subsequent data chunks instead of relying solely on resampling methods. Then, all base classifiers are updated using a new dual adaptive sampling bagging strategy, which can help to reduce the classification inaccuracies involving by class imbalance. In the prediction phase, DES system constructs different ensemble models for different instances. The inclusion of a sliding window-based drift detector makes the above two strategies adapt to concept drift. Experimental results show that AB-DES achieves higher classification accuracy and exhibits enhanced robustness compared to 8 state-of-the-art methods on 10 synthetic datasets and 5 real world datasets with different types of concept drift.

Relationship between vertical jump performance and playing time and efficiency in professional male basketball players.

With innovative force plate technology being available to many sports organizations worldwide that allow for time-efficient in-depth neuromuscular performance assessment, the purpose of the present study was to examine the relationship between some of the most commonly analyzed countermovement vertical jump (CVJ) force-time metrics and basketball playing time and efficiency. Twenty-four professional male basketball players volunteered to participate in the present study. The CVJ testing procedures were conducted within the first quarter of the competitive season span. Following a standardized warm-up protocol, each athlete stepped on a dual uni-axial force plate system sampling at 1,000 Hz and performed three maximum-effort CVJs with no arm swing. To minimize the possible influence of fatigue, each jump trial was separated by a 10-15 s rest interval and the average value across three jumps was used for performance analysis purposes. Basketball playing efficiency and average playing time were obtained at the end of the regular season competitive period from the coaching staff records and the official team records. Pearson product-moment correlation coefficients (r) were used to examine the strength of the relationships between force-time metrics and basketball playing time and efficiency, separately for each dependent variable (p < 0.05). A significant positive association was observed between playing efficiency and eccentric mean force and eccentric mean and peak power (r = 0.406-0.552). Similarly, an increase in eccentric mean power was positively correlated with the number of minutes played during the competitive season (r = 0.464). Moreover, the aforementioned relationship remained present even when eccentric mean power was expressed relative to the player's body mass (r = 0.406). Thus, the findings of the present study indicate that, at the professional level of men's basketball competition, CVJ eccentric strength and power have a positive impact on both playing time and efficiency.

Dynamic Matching of Reconstruction and Anti-Aliasing Filters in Adaptive Active Noise Control

Constrained by the computing power, adaptive active noise control systems often have a low sampling rate. Therefore, reconstruction filters and anti-aliasing filters with fixed parameters are generally adopted to eliminate the mirror noise and aliasing noise, respectively; however, they may boost the group delay of the system. A dynamic matching method based on dual sampling rates is proposed to dynamically adjust the parameters of the reconstruction and anti-aliasing filters, according to the characteristics of the primary sound source, for a compromise between high-frequency noise and group delay. In digital high-sampling-rate regions, data that include high-frequency information are analyzed regularly, following which the parameters of the reconstruction filters and those of the anti-aliasing filters are dynamically matched. In digital low-sampling-rate regions, the estimation of the secondary path transfer function is updated. The results of laboratory experiments show that the proposed method not only can suppress the mirror and aliasing noise for primary sound sources with different spectra, but can also effectively reduce the group delay and improve the noise reduction performance of a system.

Time-Resolved Electromagnetic Near-Field Scanning: Dual Sparse Sampling in Time and Space

Time-Resolved Electromagnetic Near-Field Scanning: Dual Sparse Sampling in Time and Space

Applying machine learning to reveal the microscopic heat transfer mechanism of nanofluids as coolants

Nanofluids are considered as excellent coolants to optimize thermal management of electronic devices, where the nanoparticle morphology and the addition of surfactants can affect the thermal transport performance of nanofluids. Due to the limitations of high economic and computational cost in previous experimental and numerical simulation methods, the design of nanofluids urges for more efficient approaches. In this work, a novel machine learning framework coupled with molecular dynamics methods was proposed to model the multi-component mixing nanofluidic systems and explore the deep heat transfer mechanisms. Multi-input attribute point cloud dataset, dual channel sampling network and multi-nanoscale optimization scheme were used to improve the prediction performance of machine learning. The computational cost of the machine learning method is shortened by 36000 times compared with simulation methods. Moreover, our work can achieve up to 90 % prediction accuracy for surfactant adsorption properties. Furthermore, algorithm optimization strategy can improve the prediction accuracy of nanofluidic heat transfer performance by 40 %. The proposed framework has the potential to shorten the development cycle of nanofluidic design.

Influence of salinity gradients on the diffusion of water and ionic species in dual porosity clay samples

Most of the available data on diffusion in natural clayey rocks consider tracer diffusion in the absence of a salinity gradient despite the fact that such gradients are frequently found in natural and engineered subsurface environments. To assess the role of such gradients on the diffusion properties of clayey materials, through-diffusion experiments were carried out in the presence and absence of a salinity gradient using salt-diffusion and radioisotope tracer techniques. The experiments were carried out with vermiculite samples that contained equal proportions of interparticle and interlayer porosities so as to assess also the role played by the two types of porosities on the diffusion of water and ions. Data were interpreted using both a classical Fickian diffusion model and with a reactive transport code, CrunchClay that can handle multi-porosity diffusion processes in the presence of charged surfaces. By combining experimental and simulated data, we demonstrated that (i) the flux of water diffusing through vermiculite interlayer porosity was minor compared to that diffusing through the interparticle porosity, and (ii) a model considering at least three types of porous volumes (interlayer, interparticle diffuse layer, and bulk interparticle) was necessary to reproduce consistently the variations of neutral and charged species diffusion as a function of salinity gradient conditions.

Within-individual reproducibility of a dual sample oral cholate challenge test (DuO) and simplified versions of the HepQuant SHUNT test.

Current noninvasive liver tests measure fibrosis, inflammation, or steatosis and do not measure function. The HepQuant platform of noninvasive tests uniquely assesses both liver function and physiology through the hepatic uptake of stable isotopes of cholate. However, the prototypical HepQuant SHUNT test (SHUNT V1.0) is cumbersome to administer, requiring intravenous and oral administration of cholate and six peripheral venous blood samples over 90 min. To alleviate the burden of test administration, we explored whether an oral only (DuO) version, and other simplified versions, of the test could provide reproducible measurements of liver function. DuO requires only oral dosing and two blood samples over 60 min. The simplified SHUNT test versions were SHUNT V1.1 (oral and IV dosing but four blood samples) and SHUNT V2.0 (oral and IV dosing but only two blood samples over 60 min). In this paper, we describe the reproducibility of DuO and the simplified SHUNT tests relative to that of SHUNT V1.0; equivalency is described in a separate paper. Data from two studies comprising 236 SHUNT tests in 94 subjects were analyzed retrospectively by each method. All simplified methods were highly reproducible across test parameters with intraclass correlation coefficients >0.93 for test parameters Disease Severity Index (DSI) and Hepatic Reserve. DuO and SHUNT V2.0 improved reproducibility in measuring portal-systemic shunting (SHUNT%). These simplified tests, particularly DuO and SHUNT V2.0, are easier to administer and less invasive, thus, having the potential to be more widely accepted by care providers administering the test and by patients receiving the test.

Does financial literacy contribute to facilitating residents in safeguarding their rights as financial consumers?A three-stage study based on the perspective of “fraud” phenomenon

Utilizing microdata from six provinces in East China, this study centers on the phenomenon of “fraud," employing a three-stage Probit model with dual sample selectivity to explore the impact of financial knowledge on residents' safeguarding of financial consumer rights and interests. This methodological approach effectively addresses estimation bias arising from concerns related to dual sample selectivity. The process of residents safeguarding their rights and interests when confronted with fraud unfolds in three sequential stages: “pre-fraud prevention, during fraud loss avoidance, and post-fraud rights protection." Key findings indicate that, on the whole, higher levels of financial knowledge foster residents' protection of financial consumer rights and interests. Specifically, heightened financial literacy is associated with an increased likelihood of encountering fraud, a reduced probability of incurring losses post-fraud, and an enhanced propensity for pursuing rights protection thereafter. Moreover, heterogeneity analysis reveals that the impact of financial knowledge is more pronounced among middle-aged and elderly individuals, rural inhabitants, and women. Furthermore, concerning various types of fraud, the amplification effect of financial knowledge is particularly evident in cases of telecom fraud and online fraud, though not in traditional fraud cases. Additionally, moderation effect analysis underscores that, overall, heightened attention to information, improved digital literacy, and increased social interaction can reinforce the positive influence of financial knowledge. This paper provides valuable insights for strengthening the protection of residents' financial rights and ensuring the security of their assets.

Augmented photovoltaic performance of Cu/Ce-(Sn:Cd)/n-Si Schottky barrier diode utilizing dual-doped Ce-(Sn:Cd) thin films

In the current investigation, we are fabricated the Schottky barrier diode (SBDs) formed on dual doped Ce-(Sn:Cd) (1, 3 and 5 wt%) thin films. The film was prepared by spray pyrolysis of transparent glass and silicon substrates using a low-cost nebulizer, ideal substrate temperature is 450 °C and the structure, optics, morphology & electrical properties of the films were characterized by X-Ray Diffractometer, Atomic Force Microscope and Ultra Violet - Visible spectral, electrical and I–V properties of diodes. All dual doped thin films are the cubic structure, as revealed by the XRD pattern. Then the roughness and smoothness of the film were then revealed by atomic force microscopy (AFM). Ultraviolet–vis spectroscopy is formed on optical absorption and band gap energy (3.91 eV) also electrical conductivity increases Cd concentration of films corresponding activation energy diminish. Current-voltage properties [I–V] and photodiode parameters of Cu/Ce-(Sn:Cd)/n-Si diodes were evaluated in the dark and light. The barrier height (ФB) for the diode fabricated was initiate to be 0.69 eV, as well as ideality factors (n) 2.57 of the diode parameters. As a consequence, the 5 wt% of Cd parade greater device performance for the photodiode applications, the present study is first combination of dual doped samples and low cost JNSP technique.

Credit rating, repayment willingness and farmer credit default

This study, grounded in survey data collected from farmers in three northeastern provinces of China-specifically Heilongjiang, Jilin, and Liaoning in 2019-investigates the relationships among credit ratings, repayment willingness, and credit default among farmers. To address the dual sample selection issue stemming from both credit demand and credit accessibility, a three-stage Prohibit model is employed. The research empirically examines the impact of both traditional credit ratings and digital credit ratings on farmer credit default while delving into the interplay between the two. Furthermore, a mediation effect model is utilized to explore how credit ratings influence credit default through their effect on farmers' willingness to repay. The main findings as follows: Firstly, both traditional and digital credit ratings serve to deter farmers' credit defaults. Specifically, as a farmer attains a high-credit status in the traditional sense or achieves a higher digital credit score, the likelihood of credit default diminishes. Secondly, the inhibitory impact of both traditional and digital credit ratings on farmers' credit defaults is mutually reinforcing and complementary. Lastly, the mechanistic analysis reveals that both traditional and digital credit ratings effectively mitigate credit defaults by enhancing farmers' repayment willingness. In this regard, traditional credit ratings operate through the reputation and punishment mechanisms, while the supervision mechanism is not implicated. On the other hand, digital credit ratings operate through the reputation, punishment, and supervision mechanisms. Consequently, a comprehensive approach to reducing rural financial risks involves bolstering the cultivation of a robust reputation atmosphere and credit system within rural financial markets, along with the systematic enhancement of the efficacy of credit rating supervision mechanisms.

Forensic pilot application of rehydrating solutions on human cadaveric skin: what are the effects on hemorrhagic infiltrates?

The microscopic evaluation of hemorrhagic infiltrates is crucial in forensic diagnostics, but it proves challenging in corificated and mummified cadavers. In these cases, pre-treatment with rehydrating solutions is recommended, although their effects on the hemorrhagic infiltrate are not well understood. In this pilot study, we microscopically investigated the effect of two different rehydrating solutions-Sandison's solution and fabric softener-on well-preserved human cadaveric skin samples taken from areas affected by an ecchymotic lesion, comparing them with direct fixation in formalin. Specifically, we examined the topographic distribution of the hemorrhagic infiltrate in each layer of the skin by assigning a semi-quantitative score, conducted mutual comparisons, and performed statistical analysis. Histologically, compared to direct fixation in formalin, a slight and statistically non-significant reduction in the hemorrhagic infiltrate was observed in samples pre-treated with fabric softener. On the other hand, a more pronounced and statistically significant decrease in scores was observed in samples pre-treated with Sandison's solution. This effect is likely due to the fact that Sandison's solution, due to its components, exerts an osmotic effect, partially inducing osmotic lysis of red blood cells. Overall, extensive areas of hemorrhagic infiltrates were preserved, although to a lesser extent, while smaller foci were markedly reduced, sometimes even disappearing. The findings suggest that Sandison's solution has a detrimental effect on cutaneous hemorrhagic infiltrates, emphasizing the importance of being cautious and conducting dual sampling, using both formalin and a rehydrating solution, for forensic examination of mummified or corificated skin samples.

A 2-2 MASH ΔΣ ADC with fast-charge CLS input buffer and dual double sampling achieving 103.3-dB SNDR and ±2.5-ppm/FSR INL

This paper presents a 2-2 multi-stage-noise-shaping (MASH) ΔΣ analog-to-digital converter (ADC), in which an integrator with dual double sampling (DDS) technique and stability compensation is proposed to save the area of capacitors without increasing the thermal noise. In addition, a fast-charge correlated-level-shifting (CLS) input buffer is also proposed to improve the linearity with acceptable power consumption. The buffer and the ADC are fabricated in a 0.18-μm CMOS process with an active area of 2.41 mm2, with 3∼5V supply voltage for the input buffer and 1.8-V power supply for the ADC, the overall ADC chip achieves a signal-to-noise-and-distortion ratio (SNDR) of 103.3 dB, a spurious-free dynamic range (SFDR) of 113.2 dB and an integral nonlinearity (INL) of ±2.5 ppm/full-scale range (FSR). The overall power consumption is 14.88 mW.

Dual Sampling Based Causal Intervention for Face Anti-Spoofing With Identity Debiasing

Dual Sampling Based Causal Intervention for Face Anti-Spoofing With Identity Debiasing

Combustion synthesized La2O3: Er3+/Yb3+ phosphor for simultaneous upconversion emission and photo-thermal signal generation

The Er3+/Yb3+ doped La2O3 phosphor is prepared through combustion synthesis route and then studied using frequency upconversion (UC) and photoacoustic spectroscopic techniques. Prepared phosphor sample was annealed at high temperature ∼2100°C for short time and then structural and optical characterizations were performed. A photoacoustic cell was fabricated to record photoacoustic signal generation. Samples have shown strong upconversion emission at 409 nm, 523 nm, 548 nm, and 672 nm due to the 2H9/2 →4I15/2, 2H11/2 →4I15/2, 4S3/2 → 4I15/2 and 4F9/2→ 4I15/2 transitions, respectively. The photoacoustic measurement has revealed that heat generation in the sample increases in line with the increase in upconversion emission although both properties are opponent to each other. Studies show that prepared phosphor is efficient for generating strong upconversion emission as well as strong photoacoustic signal (also photo-thermal signal) and hence present dual functional sample seems useful for upconversion imaging as well as photo-thermal therapy.

Dual sampling linear regression ensemble to predict wheat yield across growing seasons with hyperspectral sensing

In the domain of crop yield assessment, the combination of remote sensing and advanced regression techniques has gained significant attention. This study focused on predicting wheat yield across growing seasons using hyperspectral reflectance data. The performance of two decision tree-based algorithms, deep forest (DF) and random forest (RF), as well as a novel ensemble method called dual sampling linear regression ensemble (DSLRE), was evaluated. Canopy hyperspectral reflectance data were collected at two stages of wheat growth: early grain filling (EGF) and mid-grain filling (MGF), in three distinct growing environments. Prediction accuracy was assessed using the Pearson correlation coefficient (PCC) and mean absolute error (MAE). The results showed that the DF algorithm outperformed the RF algorithm in most scenarios. In modeling framework A, DF achieved the highest accuracy at the MGF stage using truncated reflectance (PCC = 0.60, MAE = 0.82 t/ha). In modeling framework B, DF performed better than RF in three out of four conditions, while RF exhibited higher prediction accuracy during the EGF stage using raw reflectance (PCC = 0.59, MAE = 1.48 t/ha). Moreover, the DSLRE algorithm outperformed DF and RF in six of the eight modeling scenarios and demonstrated robustness in coping with noisy features. The heritability analysis indicated that DSLRE predictions effectively captured the effects of genetic factors on yield variation. These findings illustrate the significance of the proposed DSLRE algorithm in improving yield prediction, providing valuable guidance for effective crop yield management.

Impact of improper sample handling on Cobas CT/NG testing platform with dual swab sample collection kit for detecting Chlamydia trachomatis and Neisseria gonorrhoeae.

The importance of this observation lies in its potential to directly impact testing outcomes and patient care. By identifying improper sample handling as a contributing factor to a substantial number of invalid results, we emphasize the need for meticulous adherence to recommended protocols during sample collection. Laboratories that overlook or are unaware of such deviations may inadvertently compromise the reliability and efficacy of their diagnostic processes, leading to misdiagnoses, delayed treatment, and patient dissatisfaction.