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Many institutions face low deposit rates with their institutional repositories despite investing substantial resources in implementing and supporting these systems. Deposit rates are higher in IRs that offer mediated deposits; however, this can be a time and labor intensive process. This article describes a method for copying open access articles and corresponding descriptive metadata from open repositories for archiving in an institutional repository using Beautiful Soup and Selenium as web scraping tools. This method quickly added hundreds of articles to an IR without relying on faculty participation or consulting publisher policies, increasing repository downloads and usage. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to examine the effect of birth ball exercise on labor pain, delivery duration, birth comfort, and birth satisfaction. Methods: The study used a randomized controlled trial design. All 120 primiparous pregnant women were randomly assigned to the intervention (IG) and control groups (CG). After the cervical dilatation reached 4 cm, the pregnant women in the IG performed birth ball exercises, adhering to the birth ball guide created by the researcher. No intervention was made in the control group other than standard midwifery care practices. Results: The labor pain level between the groups (VAS 1-when cervical dilatation was 4 cm) was similar to each other. The labor pain level (VAS 2- when cervical dilatation was 9 cm) scores of the women in the IG were significantly lower than those in the CG (p < 0.05). The time between the active phase of labor until dilatation is complete and the time until the baby's head comes out after full dilatation was found to be statistically significantly shorter in the IG compared to the CG (p < 0.05). Childbirth comfort and satisfaction mean scores between the groups were found to be statistically insignificant (p > 0.05). Conclusion: As a result of the study, it was determined that the birth ball exercise significantly reduced labor pain and labor time. We recommend that the birth ball exercise be applied to all low-risk pregnant women because it helps fetal descent and cervical dilatation, and shortens labor pain and delivery time. [ABSTRACT FROM AUTHOR]

Female domestic workers (FDWs) experience space–time constraints and mobility challenges corresponding to their demanding daily work responsibilities. Studies have shown that FDWs' mobility and activities are primarily dictated by their employers through work tasks. It is unclear, though, how FDWs' activity and mobility patterns outside their employers' homes are shaped by individual and contextual factors, including government policies that mandate that FDWs be granted a rest day. Using an activity space approach combined with multilevel modeling, I evaluated mobility and activity patterns on work and rest days for a sample of Indonesian FDWs in Hong Kong. Data were collected using innovative online activity diaries and were triangulated with qualitative data from WhatsApp follow-up conversations. This research uncovers that FDWs' activity patterns differ significantly between work and rest days. FDWs rarely go outside on workdays except to perform work-related tasks. On the rest day, FDWs' activity spaces are much more expansive as they conduct social and personal activities that are essential for maintaining their well-being. By comparing work and rest days, this research deepens our understanding of geographical, social, and temporal aspects of FDWs' space–time constraints and (im)mobility experiences that encompass and go beyond employer-assigned tasks. Furthermore, the findings demonstrate the benefits of rest day policies for enhancing the visibility of marginalized women in public spaces, particularly in the context of FDWs' restrictive space–time constraints. [ABSTRACT FROM AUTHOR]

Here, we present a method for concentrating radiocesium in seawater using ammonium molybdophosphate-polyacrylonitrile (AMP-PAN) resin using custom-made sample-loading equipment. It was designed to reduce analytical time and labor with eight peristaltic pumps connected in parallel with eight columns, each packed with AMP-PAN. Eighty liters of seawater containing radiocesium were concentrated to 0.01 L in 6 h with the proposed method and Cs recovery was > 85%. The minimum detectable activity was 0.2 mBq L–1 at 160,000-s measurement with a high-purity germanium detector. [ABSTRACT FROM AUTHOR]

The visual modality is central to both reception and expression of human creativity. Creativity assessment paradigms, such as structured drawing tasks Barbot (2018), seek to characterize this key modality of creative ideation. However, visual creativity assessment paradigms often rely on cohorts of expert or naïve raters to gauge the level of creativity of the outputs. This comes at the cost of substantial human investment in both time and labor. To address these issues, recent work has leveraged the power of machine learning techniques to automatically extract creativity scores in the verbal domain (e.g., SemDis; Beaty & Johnson 2021). Yet, a comparably well-vetted solution for the assessment of visual creativity is missing. Here, we introduce AuDrA – an Automated Drawing Assessment platform to extract visual creativity scores from simple drawing productions. Using a collection of line drawings and human creativity ratings, we trained AuDrA and tested its generalizability to untrained drawing sets, raters, and tasks. Across four datasets, nearly 60 raters, and over 13,000 drawings, we found AuDrA scores to be highly correlated with human creativity ratings for new drawings on the same drawing task (r =.65 to.81; mean =.76). Importantly, correlations between AuDrA scores and human raters surpassed those between drawings' elaboration (i.e., ink on the page) and human creativity raters, suggesting that AuDrA is sensitive to features of drawings beyond simple degree of complexity. We discuss future directions, limitations, and link the trained AuDrA model and a tutorial (https://osf.io/kqn9v/) to enable researchers to efficiently assess new drawings. [ABSTRACT FROM AUTHOR]

To enhance the transplantation effectiveness of vegetables and promptly formulate subsequent work strategies, it is imperative to study the recognition approach for transplanted seedlings. In the natural and complex environment, factors like background and sunlight often hinder accurate target recognition. To overcome these challenges, this study explores a lightweight yet efficient algorithm for recognizing cabbage transplantation states in natural settings. Initially, FasterNet is integrated as the backbone network in the YOLOv5s model, aiming to expedite convergence speed and bolster feature extraction capabilities. Secondly, the introduction of the GAM attention mechanism enhances the algorithm's focus on cabbage seedlings. EIoU loss is incorporated to improve both network convergence speed and localization precision. Lastly, the model incorporates deformable convolution DCNV3, which further optimizes model parameters and attains a superior balance between accuracy and speed. Upon testing the refined YOLOv5s target detection algorithm, improvements were evident. When compared to the original model, the mean average precision (mAP) rose by 3.5 percentage points, recall increased by 1.7 percentage points, and detection speed witnessed an impressive boost of 52 FPS. This enhanced algorithm not only reduces model complexity but also elevates network performance. The method is expected to streamline transplantation quality measurements, minimize time and labor inputs, and elevate field transplantation quality surveys' automation levels. [ABSTRACT FROM AUTHOR]

My aim in this article is to contribute to defences of working time policies by attempting to meet an objection that comes from those who condemn these measures on the alleged grounds that they reduce economic output. What is more, as I emphasize throughout, it is possible to rebut such a concern in a fashion that is consistent with the demands of liberal anti-perfectionism. In itself, this is a philosophically striking and politically significant result. However, beyond this, much of the value of my discussion lies in the details of how to meet the relevant objection, and perhaps especially in my novel liberal defence of the ideal of the stationary state. [ABSTRACT FROM AUTHOR]

Double poverty refers to the lack of both time and income. This study analyses precarious workers' double poverty, focusing on the case of South Korea, where the characteristics of its labour market perpetuate the risk of double poverty. This study set less than two-thirds of the median free time and less than two-thirds of the median income as poverty lines. Using Korean Labour & Income Panel Study data, this article identifies the double poor, experiencing both time and income poverty in the Korean labour market. It then examines the effects of occupational class, employment type, company size, social wage, trade union membership, and gender on double poverty. It is found that double poverty impacts women workers, low-skilled service workers, and non-regular workers. This study contributes to the discussion of precarious work by analysing the double poverty of time and income of precarious workers. Time poverty limits workers' capacity to escape income poverty as they are unable to work longer and invest in household production or human capital. Consequently, the workers' lack of time deepens their precarity. [ABSTRACT FROM AUTHOR]

In the field of welding inspection, radiographic non-destructive evaluation (NDE) is a widely used technique for detecting defects in welds. However, this technique requires professionally qualified workers to manually judge radiographs to determine the presence, type, and location of defects. Recently, deep learning techniques have been developed to automate this process by using image segmentation. Despite its effectiveness, small-size targets in segmentation can have blurred boundaries, making it difficult to accurately annotate them at the pixel level. In this study, we propose an automated approach using the Point-REND Res-UNet model to improve the accuracy of detecting welding defects. Our method uses the improved Point-Rend algorithm to iteratively refine coarse segmentation results, allowing for more accurate defect detection. We evaluate our approach on a set of X-ray data and demonstrate that it achieves an improvement in model dice of 6.22%. Our proposed approach can potentially save labor time and costs while enhancing the accuracy and efficiency of welding defect detection. [ABSTRACT FROM AUTHOR]

The labor force surveys (LFS) of all EU countries underwent a substantial redesign in January 2021. To ensure coherent labor market time series for the main indicators in the Norwegian LFS, we model the impact of the redesign. We use a state-space model that takes explicit account of the rotating pattern of the LFS. We also include auxiliary variables related to employment and unemployment that are highly correlated with the LFS variables we consider. The results of a parallel run are also included in the model. The purpose of the article is to quantify the structural breaks due to the redesign. This article makes two contributions to the literature on the effects of redesign in surveys with a rotating panel, such as the LFS. First, we suggest a symmetric specification of the process of the wave-specific effects. Second, we account for substantial fluctuations in the labor force estimates due to the COVID-19 pandemic in the time around the LFS redesign by applying time-varying hyperparameters for both the LFS variables and the auxiliary variables. The specification with time-varying hyperparameters shows a better fit compared to the specification with time-invariant hyperparameters. [ABSTRACT FROM AUTHOR]

The labor is a physiological event considered to have its own circadian (diurnal) rhythm, but some of the data remain conflicting, especially for preterm births. In this retrospective study, we analyzed the circadian trends of labor onset times in the Slovenian birth cohort from 1990 to 2018 with over 550,000 cases of singleton births. The number of term and preterm labor onsets was calculated for each hour in a day and circadian trends were evaluated for each of the study groups by modeling with a generalized Poisson distribution linked with the cosinor regression model using logarithmic link function. The induced labors were taken as the control group since the timing of labor depends mostly on the working schedule of personnel and not on the intrinsic rhythmic characteristics. For induced labors, the main peak in the number of labor cases was observed in the late morning hours (around 10 AM) for all gestational ages. The prominence of this peak becomes smaller in spontaneous premature labors with gradually disrupting rhythmicity in very preterm and extremely preterm cases. Labors starting with spontaneous contractions peak between 6 and 7 AM and lose the rhythmicity at 35 weeks of gestation while labors starting with a spontaneous rupture of membranes peak at 1 AM and lose the rhythmicity at 31 weeks of gestation, suggesting differences in underlying mechanisms. According to our knowledge, this is the first study that shows differences of circadian trends between different types of spontaneous labors, i.e., labors initiated with contraction and labors initiated with a spontaneous rupture of membranes. Moreover, the obtained results represent evidence of gradual disruption of rhythmicity from mild to extreme prematurity. [ABSTRACT FROM AUTHOR]

The labor is a physiological event considered to have its own circadian (diurnal) rhythm, but some of the data remain conflicting, especially for preterm births. In this retrospective study, we analyzed the circadian trends of labor onset times in the Slovenian birth cohort from 1990 to 2018 with over 550,000 cases of singleton births. The number of term and preterm labor onsets was calculated for each hour in a day and circadian trends were evaluated for each of the study groups by modeling with a generalized Poisson distribution linked with the cosinor regression model using logarithmic link function. The induced labors were taken as the control group since the timing of labor depends mostly on the working schedule of personnel and not on the intrinsic rhythmic characteristics. For induced labors, the main peak in the number of labor cases was observed in the late morning hours (around 10 AM) for all gestational ages. The prominence of this peak becomes smaller in spontaneous premature labors with gradually disrupting rhythmicity in very preterm and extremely preterm cases. Labors starting with spontaneous contractions peak between 6 and 7 AM and lose the rhythmicity at 35 weeks of gestation while labors starting with a spontaneous rupture of membranes peak at 1 AM and lose the rhythmicity at 31 weeks of gestation, suggesting differences in underlying mechanisms. According to our knowledge, this is the first study that shows differences of circadian trends between different types of spontaneous labors, i.e., labors initiated with contraction and labors initiated with a spontaneous rupture of membranes. Moreover, the obtained results represent evidence of gradual disruption of rhythmicity from mild to extreme prematurity. [ABSTRACT FROM AUTHOR]

-Nanocarriers (NCs) functionalized with chemical agents represent a novel approach for improved priming efficiency through targeted delivery. Multifunctional priming through the combined used of different agents in novel engineered nanocarriers (NENCs) has the potential to achieve multiple benefits in plants. The application of NENCs as seed coatings has the potential to improve crop yields, while achieving maximum cost-effectiveness compared with application at the plant level as it requires less time and labor. Gene-editing techniques can be used to modify the expression of targeted genes involved in plant priming as identified by transcriptomic approaches, and can enhance the ability of plants to respond to priming treatments and improve their overall performance. Plants are exposed to multiple threats linked to climate change which can cause critical yield losses. Therefore, designing novel crop management tools is crucial. Chemical priming has recently emerged as an effective technology for improving tolerance to stress factors. Several compounds such as phytohormones, reactive species, and synthetic chimeras have been identified as promising priming agents. Following remarkable developments in nanotechnology, several unique nanocarriers (NCs) have been engineered that can act as smart delivery systems. These provide an eco-friendly, next-generation method for chemical priming, leading to increased efficiency and reduced overall chemical usage. We review novel engineered NCs (NENCs) as vehicles for chemical agents in advanced priming strategies, and address challenges and opportunities to be met towards achieving sustainable agriculture. [ABSTRACT FROM AUTHOR]

Type I hypersensitivity is triggered by mast cell degranulation, a stimulus-induced exocytosis of preformed secretory granules (SGs) containing various inflammatory mediators. The degree of degranulation is generally expressed as a percentage of secretory granule markers (such as β-hexosaminidase and histamine) released into the external solution, and considerable time and labor are required for the quantification of markers in both the supernatants and cell lysates. In this study, we developed a simple fluorimetry-based degranulation assay using rat basophilic leukemia (RBL-2H3) mast cells. During degranulation, the styryl dye FM1-43 in the external solution fluorescently labeled the newly exocytosed SGs, whose increase in intensity was successively measured using a fluorescence microplate reader. In addition to the rate of β-hexosaminidase secretion, the cellular FM1-43 intensity successfully represented the degree and kinetics of degranulation under various conditions, suggesting that this method facilitates multi-sample and/or multi-time-point analyses required for screening substances regulating mast cell degranulation. [ABSTRACT FROM AUTHOR]

We examine the impact of unconditional cash transfers (UCTs) on fertility. We develop a theoretical model that demonstrates how UCTs affect fertility decisions, time allocations for leisure, labor and childrearing, and child health through health spending. We then empirically examine the impact of UCTs on fertility in Pakistan. Our theoretical model suggests that under certain conditions, UCTs are likely to increase fertility if UCTs increase child health regardless of how they affect parental leisure, labor and childrearing time. The empirical results suggest that UCTs have a positive effect on fertility. [ABSTRACT FROM AUTHOR]

In bone fracture preoperative surgical planning, 3D fracture reduction is of great significance. However, segmenting 3D fracture bones into fragments and assembling the bone fragments to restore their original morphology are labor intensive and time consuming. Current works, however, omit their synergistic effects between reduction and segmentation, which, we envision, can significantly benefit the fracture reduction. To this end, a method is proposed to alternatively segment and assemble the fragments by incorporating the contralateral bone as template and leveraging the synergistic effect on segmentation and reduction. The 3D fracture model is initially segmented into separated outer surface of fragments. The reduction is then conducted by template matching, specifically, a whole-to-whole matching strategy through deep learning of dense features is employed. Thereafter, the segmentation is further refined with the assistance of the template. The process of reduction and segmentation is iterated until the algorithm converges. Experiments were conducted on simulated data and clinical data, the mean segmentation accuracy is 95.26%, the assembling translation error is 3.28 ± 3.01 mm, and the assembling rotation error is 1.62 ± 1.71°. Results demonstrated the superiority of our method over state-of-the-art methods, and it can be used as a feasible scheme for fracture reduction planning. Moreover, it is also proved that segmentation and reduction can promote each other. [Display omitted] • Synergistic effect is exploited between segmentation and reduction. • A novel whole-to-whole matching tactics is proposed for template-matching. • The SSM is leveraged to generate and label the training data. [ABSTRACT FROM AUTHOR]

This article focuses on the introduction of crofting tenure in the Annexed Estates (1752–1784). In 1763, the Board of Commissioners in charge of managing the estates on behalf of the British Crown launched its most ambitious 'improvement' scheme. Parcels of three acres, usually detached from principal farms, were turned into new settlements for disbanded soldiers and sailors from the Seven Years War. The scheme, this article argues, was one of the earliest crofting schemes ever implemented in the Scottish Highlands. The plan hoped to put the Highlands' natural and human resources to the service of the state by ensuring that the Crown could tap into a future recruiting pool and that the Board would benefit from a cheap workforce to reclaim unproductive grounds and develop the linen manufacture in the estates. The settlements were also a way to solve 'improvement's contradictions via spatial planning by preventing depopulation caused by the creation of contiguous farmsteads. The failure of the experiment ultimately highlighted the entrenched contractions of 'improvement' ideology and led to the emergence of an alternative geography of 'improvement' by the turn of the century. [ABSTRACT FROM AUTHOR]

Background: To evaluate the improvement of evaluation accuracy of cervical maturity for Chinese women with labor induction by adding objective ultrasound data and machine learning models to the existing traditional Bishop method. Methods: The machine learning model was trained and tested using 101 sets of data from pregnant women who were examined and had their delivery in Peking University Third Hospital in between December 2019 and January 2021. The inputs of the model included cervical length, Bishop score, angle, age, induced labor time, measurement time (MT), measurement time to induced labor time (MTILT), method of induced labor, and primiparity/multiparity. The output of the model is the predicted time from induced labor to labor. Our experiments analyzed the effectiveness of three machine learning models: XGBoost, CatBoost and RF(Random forest). we consider the root-mean-squared error (RMSE) and the mean absolute error (MAE) as the criterion to evaluate the accuracy of the model. Difference was compared using t-test on RMSE between the machine learning model and the traditional Bishop score. Results: The mean absolute error of the prediction result of Bishop scoring method was 19.45 h, and the RMSE was 24.56 h. The prediction error of machine learning model was lower than the Bishop score method. Among the three machine learning models, the MAE of the model with the best prediction effect was 13.49 h and the RMSE was 16.98 h. After selection of feature the prediction accuracy of the XGBoost and RF was slightly improved. After feature selection and artificially removing the Bishop score, the prediction accuracy of the three models decreased slightly. The best model was XGBoost (p = 0.0017). The p-value of the other two models was < 0.01. Conclusion: In the evaluation of cervical maturity, the results of machine learning method are more objective and significantly accurate compared with the traditional Bishop scoring method. The machine learning method is a better predictor of cervical maturity than the traditional Bishop method. [ABSTRACT FROM AUTHOR]

The Virginia Herpetological Society conducted a one-day herp survey at the future site of Powhatan State Park on 8 May 2010. During that survey, 15 species of amphibians and nine species of reptiles were documented. On 20 May 2023, thirteen years after the first survey, the park was revisited. During this survey, 25 species of amphibians and reptiles were documented including 15 species of amphibians and 10 species of reptiles. The most frequently found species was the Northern Cricket Frog with 63 being observed. In all 204 animals were observed during the survey period. Forty people contributed 218 person-hours of effort surveying the park during the one-day survey. [ABSTRACT FROM AUTHOR]

Reproductive domestic labor is shifting from its old norm of invisibly creating and maintaining labor power in the highly private and ostensibly non-economic zone of the household. This paper asks whether new forms of complex motherhood, and the means presented to mothers for coping with them in the digital age, should be conceived of as further unpaid labor that sits on top of old forms of exploitation. As mothers increasingly become digital reproductive laborers, the family home is becoming a public and highly economized zone: a workhouse for both standard employers and emerging parties who designate themselves as merely providing online services. In contrast to the frequently posited thesis that mothers are only indirectly drawn into the circuit of capital, this paper argues that the current situation creates the "mother commodity": a being whose social reproductive labor time is supercommodified via the normative addition of "audience commodity" labor duties. [ABSTRACT FROM AUTHOR]

Following the commodity-money system that prevailed at the time of his research, Marx assumed the monetary expression of labor time (MELT) to be fixed. This assumption cannot hold in the contemporary regime of non-commodity money. It is essential to resolve the question of how the MELT is determined in a system of non-commodity money. The expression is the ratio of the total paper money circulating in the economy, less all paper money advanced on constant capital, to the total number of socially necessary labor hours exerted in the economy. Expressed algebraically, m = (Mv − C)/L. This model differs from those proposed by Moseley; Saros; Rieu, Lee, and Ahn; and Foley. JEL Classification : B51, E11 [ABSTRACT FROM AUTHOR]

An efficient part feeding is among the top challenges of many mass producers applying mixed-model assembly lines, for instance, in the automotive industry. This paper introduces a novel part feeding policy applied by a large German assembly plant for car engines: In-line kitting. Under this policy, the first stations of the line do not execute assembly operations, but are reserved for picking parts while passing containers of stock-keeping units (SKUs) arranged along the line. In this way, the parts are collected in traveling kits moving along with each workpiece on the conveyor, so that later assembly stations have the required parts directly available and do not lose precious labor time for unproductive parts handling. A major operational challenge when applying this part feeding policy is the walking effort for the human pickers while putting the SKUs of their respective stations into the traveling kits of the passing workpieces. Due to a high product variety, a large number of comparatively bulky SKU containers have to fit into each station, so that the walking distance to be covered by a worker during a work shift exceeds multiple kilometers. We show that this physical burden can be reduced significantly by balancing the workload among stations and optimizing the storage assignment of SKU containers within each in-line kitting station. We formulate the resulting optimization problem and provide suited solution procedures. Our computational study shows that the walking distance of pickers can be reduced significantly without producing any additional costs. [ABSTRACT FROM AUTHOR]

Optimization of antenna performance is a non-linear, multi-dimensional and complex issue, which entails a significant investment of time and labor. In this paper, a hybrid algorithm of quasi-opposition grey wolf optimization (QOGWO) and Gaussian process regression (GPR) model is proposed for antenna optimization. The QOGWO is prone to global optimality, high precision for complex problems, and fast convergence rate at the later stage. The GPR model can reduce time cost of antenna samples generation. After being optimized by the proposed approach, a stepped ultrawideband monopole antenna and a dual-band MIMO antenna for WLAN can achieve wider bandwidth and higher gain or isolation at low time cost, compared to other intelligent algorithms and published literatures. [ABSTRACT FROM AUTHOR]

This paper evaluates the potential responses of international labor mobility to the recent COVID-19 health shocks, using a New Economic Geography model inspired by recent events in Central and North America. The model suggests that the restraining impact of COVID-19 on migratory flows may retain potential emigrants in Mexico and Central America, enlarge the home market in the region, attract foreign and local businesses, and increase real wages. Moreover, this prediction unveils opportunities for the future from the opening of new, regular migratory pathways between Central America and Mexico. These would concentrate population and industry in Mexico, raise the market potential in the area and boost real wages in Mexico – and possibly in Central America as well – despite the partial deindustrialization of the Central American hinterland. [ABSTRACT FROM AUTHOR]

Multi-phase computed tomography (CT) images have gained significant popularity in the diagnosis of hepatic disease. There are several challenges in the liver segmentation of multi-phase CT images. (1) Annotation: due to the distinct contrast enhancements observed in different phases (i.e., each phase is considered a different domain), annotating all phase images in multi-phase CT images for liver or tumor segmentation is a task that consumes substantial time and labor resources. (2) Poor contrast: some phase images may have poor contrast, making it difficult to distinguish the liver boundary. In this paper, we propose a boundary-enhanced liver segmentation network for multi-phase CT images with unsupervised domain adaptation. The first contribution is that we propose DD-UDA, a dual discriminator-based unsupervised domain adaptation, for liver segmentation on multi-phase images without multi-phase annotations, effectively tackling the annotation problem. To improve accuracy by reducing distribution differences between the source and target domains, we perform domain adaptation at two levels by employing two discriminators, one at the feature level and the other at the output level. The second contribution is that we introduce an additional boundary-enhanced decoder to the encoder–decoder backbone segmentation network to effectively recognize the boundary region, thereby addressing the problem of poor contrast. In our study, we employ the public LiTS dataset as the source domain and our private MPCT-FLLs dataset as the target domain. The experimental findings validate the efficacy of our proposed methods, producing substantially improved results when tested on each phase of the multi-phase CT image even without the multi-phase annotations. As evaluated on the MPCT-FLLs dataset, the existing baseline (UDA) method achieved IoU scores of 0.785, 0.796, and 0.772 for the PV, ART, and NC phases, respectively, while our proposed approach exhibited superior performance, surpassing both the baseline and other state-of-the-art methods. Notably, our method achieved remarkable IoU scores of 0.823, 0.811, and 0.800 for the PV, ART, and NC phases, respectively, emphasizing its effectiveness in achieving accurate image segmentation. [ABSTRACT FROM AUTHOR]

Agrobacterium -mediated transformation (AMT) potentially has great advantages over other DNA introduction methods: e.g., long DNA and numerous recipient strains can be dealt with at a time merely by co-cultivation with donor Agrobacterium cells. However, AMT was applied only to several laboratory yeast strains, and has never been considered as a standard gene-introduction method for yeast species. To disseminate the AMT method in yeast species, it is necessary to develop versatile AMT plasmid vectors including shuttle type ones, which have been unavailable yet for yeasts. In this study, we constructed a series of AMT plasmid vectors that consist of replicative (shuttle)- and integrative-types and harbor a gene conferring resistance to either G418 or aureobasidin A for application to prototrophic yeast strains. The vectors were successfully applied to five industrial yeast strains belonging to Saccharomyces cerevisiae after a modification of a previous AMT protocol, i.e., simply inputting a smaller number of yeast cells to the co-cultivation than that in the previous protocol. The revised protocol enabled all five yeast strains to generate recombinant colonies not only at high efficiency using replicative-type vectors, but also readily at an efficiency around 10−5 using integrative one. Further modification of the protocol demonstrated AMT for multiple yeast strains at a time with less labor. Therefore, AMT would facilitate molecular genetic approaches to many yeast strains in basic and applied sciences. [ABSTRACT FROM AUTHOR]

Many odontocetes produce whistles that feature characteristic contour shapes in spectrogram representations of their calls. Automatically extracting the time × frequency tracks of whistle contours has numerous subsequent applications, including species classification, identification, and density estimation. Deep-learning-based methods, which train models using analyst-annotated whistles, offer a promising way to reliably extract whistle contours. However, the application of such methods can be limited by the significant amount of time and labor required for analyst annotation. To overcome this challenge, a technique that learns from automatically generated pseudo-labels has been developed. These annotations are less accurate than those generated by human analysts but more cost-effective to generate. It is shown that standard training methods do not learn effective models from these pseudo-labels. An improved loss function designed to compensate for pseudo-label error that significantly increases whistle extraction performance is introduced. The experiments show that the developed technique performs well when trained with pseudo-labels generated by two different algorithms. Models trained with the generated pseudo-labels can extract whistles with an F1-score (the harmonic mean of precision and recall) of 86.31% and 87.2% for the two sets of pseudo-labels that are considered. This performance is competitive with a model trained with 12 539 expert-annotated whistles (F1-score of 87.47%). [ABSTRACT FROM AUTHOR]

Introduction: Women with gestational diabetes mellitus (GDM) have higher rates of adverse perinatal outcomes compared with women without GDM, including an increased risk for having labor induced and for cesarean section. The findings from previous studies analyzing duration of labor in women with GDM are contradictory. The aim of the study was to evaluate the impact of GDM on time in spontaneous and induced active labor. Material and methods: This was a population‐based cohort study including 247 524 primiparous women who gave birth to a singleton fetus with cephalic presentation, ≥34+0 (completed gestational weeks + additional days) between January 2014 and May 2020 in Sweden. Data was obtained from the Swedish Pregnancy Register. Time in active labor was compared between women with GDM and without GDM with a spontaneous labor onset or induction of labor using Kaplan Meier survival analysis and Cox regression analysis. Results: Women with GDM had significantly longer time in active labor, both with a spontaneous onset and induction of labor compared to women without GDM. Women with GDM had a decreased chance of vaginal delivery at a certain time‐point compared to women without GDM, with adjusted hazard ratio of 0.92 (0.88–0.96) and 0.83 (0.76–0.90) for those with spontaneous onset and induction of labor, respectively. Women with GDM had increased risk for time in active labor ≥12 h both in spontaneous labor onset (adjusted odds ratio 1.14 [1.04–1.25]) and in induction of labor (adjusted odds ratio 1.55 [1.28–1.87]). Conclusions: Women with GDM seem to spend a longer time in active labor, both in spontaneous and induced active labor compared to women without GDM. To be able to individualize care intrapartum, there is a need for more studies demonstrating the impact of hyperglycemia during pregnancy on outcomes during childbirth. [ABSTRACT FROM AUTHOR]

In recent years, the number of websites has been increasing, and with it, the number of similar services. As a result, UX is becoming more and more important to measure the differentiation of a website from its competitors, and UI plays a major role in improving UX. Website developers implement a development process called HCD to improve UI. However, in HCD, there is a gap between the perception of the evaluator and the developer, resulting in a lot of man‐hours. In this paper, we propose a method for evaluating web pages using GUI operations to solve this problem. We let the evaluator of the web page edit the web page by mouse operation from the browser, and feedback the result directly to the developer. As a result of the experiment, we were able to discover problems with the web pages that could not be obtained by the conventional questionnaire. It also made it easier to design improvement plans, leading to a reduction in man‐hours. [ABSTRACT FROM AUTHOR]

Internships have skyrocketed in popularity as they become the new entry-level position for professional careers across the country. Despite their popularity, the legality of internships falls in a gray area created by a vague statute and a flexible, factor-based judicial test. The Fair Labor Standards Act (FLSA), which regulates employment relationships and importantly mandates a minimum wage and hour requirements, was written long before internships became commonplace and provides little direction for how to regulate these positions. In this void, both the Department of Labor and federal courts have developed guidance, the ultimate culmination of which is the modern primary beneficiary test. The equestrian industry's attempt at internships is a position known as a "working student." These positions did not arise in the same Petrie dish or era as many other internships. Instead, this type of internship is an ages-old derivative of the barter economy and apprenticeships. In short, a young, developing equestrian exchanges her labor for benefits such as training and housing--but, notably, not FLSA-complaint wages--with a professional equestrian. This position is seen both as a rite of passage into a career as an equestrian but also as an opportunity to test the waters of the industry. Working students work long hours, take on physically intensive tasks, and are often fully immersed in the industry and their positions. Do these positions pass the modern primary beneficiary test? This Note applies the factors of the test to the facts of the working student position and asserts that, for many working students, the answer is 'no.' This analysis is largely based on an extensive survey and interviews with working students, which were compiled by the Author and further explained within. Finally, this Note suggests solutions that will preserve the significant benefits of the working student position while bringing the equestrian industry into compliance. [ABSTRACT FROM AUTHOR]

Based on the idea of contact instrument integration, a device which can be used to effectively detect the result of hole-forming and sediment in bored cast -in -place piles is developed and improved in order to solve the problems of cumbersome detection steps in hole-forming quality and sediment thickness of bored cast-in-place piles. The device comprises a support moving system, a power driving system and a detection system. The function of the device in measurement of borehole diameter and perpendicularity, sediment thickness and borehole depth is tested on the basis of the waterway regulation project of the Changjiang River Estuary on the Beijing-Hangzhou Grand Canal. The results show that, compared with the existing hole forming detection equipment, the improved equipment can complete the detection of hole-forming and sediment thickness atone go. The equipment has the advantages of simple operation, wide application range, high detection accuracy, and low time and labor cost. The device has the potential of large-scale application in bored cast-in-situ pile construction and can produce better economic and social benefits. [ABSTRACT FROM AUTHOR]

This explains why Flamant devotes the third part of the book to showing how prices and distribution come about - rather than taking prices as derived directly from labour value and surplus. Flamant's treatment of fixed capital highlights its two-fold character: on one hand, it is a reproducible product of labour required for production, like intermediate inputs. Profit as "surplus" is determined in the distribution of the product rather than deriving from a physical surplus product. [Extracted from the article]

Traditional identification methods for Papaver somniferum and Papaver rhoeas (PSPR) consume much time and labor, require strict experimental conditions, and usually cause damage to the plant. This work presents a novel method for fast, accurate, and nondestructive identification of PSPR. First, to fill the gap in the PSPR dataset, we construct a PSPR visible capsule image dataset. Second, we propose a modified MobileNetV3-Small network with transfer learning, and we solve the problem of low classification accuracy and slow model convergence due to the small number of PSPR capsule image samples. Experimental results demonstrate that the modified MobileNetV3-Small is effective for fast, accurate, and nondestructive PSPR classification. [ABSTRACT FROM AUTHOR]

Inbreeding depression can reduce the viability of wild populations. Detecting inbreeding depression in the wild is difficult; developing accurate estimates of inbreeding can be time and labor intensive. In this study, we used a two-step modeling procedure to incorporate uncertainty inherent in estimating individual inbreeding coefficients from multilocus genotypes into estimates of inbreeding depression in a population of Weddell seals (Leptonychotes weddellii). The two-step modeling procedure presented in this paper provides a method for estimating the magnitude of a known source of error, which is assumed absent in classic regression models, and incorporating this error into inferences about inbreeding depression. The method is essentially an errors-in-variables regression with non-normal errors in both the dependent and independent variables. These models, therefore, allow for a better evaluation of the uncertainty surrounding the biological importance of inbreeding depression in non-pedigreed wild populations. For this study we genotyped 154 adult female seals from the population in Erebus Bay, Antarctica, at 29 microsatellite loci, 12 of which are novel. We used a statistical evidence approach to inference rather than hypothesis testing because the discovery of both low and high levels of inbreeding are of scientific interest. We found evidence for an absence of inbreeding depression in lifetime reproductive success, adult survival, age at maturity, and the reproductive interval of female seals in this population. [ABSTRACT FROM AUTHOR]

In warehouse operations, stock allocation that reduces shipment-work man-hours is necessary. The existing stock allocation recommended method (i.e., Sequential Storage Location Recommendation (SSLR) method) evaluates the storage period considering lot order and the delivery frequency of each product on the storing target pallet (PL), and stores the PL with a high delivery frequency and short storage period in a high-priority area. On the other hand, in SSLR, even if the PL is stored in a low-priority area, there is a problem that picking occurs from the low-priority area when days elapse and delivery from the PL is started. Therefore, we have developed a stock movement method in which the stored PL in the warehouse is evaluated with the evaluation value that considers the delivery frequency and storage period similar to SSLR, and which moves PLs with a short remaining storage period and high delivery frequency to a high-priority area. By combining SSLR and the proposed method, it is possible to reduce the number of deliveries from low-priority areas and prevent unnecessary occupancy of PLs having a long storage period in high-priority areas. Using simulations, it was confirmed that, by combining the method with SSLR, the man-hours for shipping can be reduced when compared to the case of SSLR alone. [ABSTRACT FROM AUTHOR]

Epidural analgesia (EA) increases the risks of maternal fever during labor, which is associated with adverse maternal and neonatal outcomes, while the risk factors for epidural-associated fever and strategies for minimizing these effects remain limited. A total of 325 pregnant women were retrospectively analyzed who had attended our hospital for a vaginal in-hospital delivery, including 208 who voluntarily accepted EA and 117 who did not receive EA. During labor, 208 EA women were allocated to a fever group (n = 42, a tympanic temperature ≥37.5 °C during labor), and a no fever group (n = 166). The outcome measures included main maternal and neonatal outcomes, labor times, duration of EA and the total EA dosage administered. 42 out of 208 women given EA exhibited fever temperatures during labor, which were higher than in women who did not receive EA (20.19% vs. 0.85%). Maternal fever had an increased risks for conversion to surgery (adjusted odds ratio (AOR), 4.05; 95% CI, 1.44–11.39) and neonatal infections (5.13; 1.98–13.29) compared to the no fever group. While maternal fever did not increase the risks for assisted vaginal delivery, fetal distress or admission to the neonatal intensive care unit (NICU), it was predominantly associated with primiparity and lesser times of gravity. Frequent cervical examinations, the duration of first stage and total labor, and the duration of EA and its total dosage were positively correlated with the incidence of fever. Furthermore, after stratifying risk factors into subgroups, we found that more frequent cervical examinations (≥7 times) and longer duration of first stage (≥442.5 min), total labor time (≥490 min), EA (≥610.0 min) increased the risk for epidural-associated fever after adjustment for potential confounding factors. EA increased the risk of intrapartum epidural-associated fever, which was correlated with adverse perinatal outcomes. Nulliparity, less times of gravidity, ≥7 cervical examinations, increased volume of the EA dosage, prolonged duration of EA and total labor time were risk factors for epidural-associated fever. The findings provide clinicians with insights and strategies to prevent epidural-associated fever more safely and effectively. [ABSTRACT FROM AUTHOR]

Objectives: This was an observational study on cervical length and head perineum distance and the prediction of time of delivery. One-hundred and twenty-five nulliparous women with uncomplicated, term, singleton pregnancy were recruited when they presented to the labor ward with show or infrequent painful uterine contractions (less than three contractions in ten minutes on a 30 min cardiotocogram). Apart from digital vaginal examination to assess cervical length and dilatation, sonographic cervical length and head perineum distance were measured by two-dimensional ultrasound. We compared women who delivered within 72 h of presentation of labor symptoms, with women who did not. After excluding ten women whose labor was induced and delivered within 72 h of presentation, one hundred and fifteen women were included for final data analysis. Main findings: Forty-nine women (42.6%) delivered while sixty-six women (57.4%) remained undelivered at 72 h of presentation of symptoms of labor. There was no statistically significant difference between the two groups on age, presence of show, contractions, fetal head station and presentation and mode of delivery. For the group who had delivered within 72 h of presentation of labor symptoms, the mean sonographic cervical length was 1.87 cm ± 0.62 cm, while the head perineum distance was 6.01 cm ± 1.15 cm. For the other group, the mean sonographic cervical length was 2.10 cm ± 0.83 cm; head perineum distance was 6.03 cm ± 1.18 cm. There was no statistically significant difference between the groups for both sonographic cervical length (p = .90); and head perineum distance (p = .08). We also compared the cervical length measured by digital vaginal examination versus sonography. The median sonographic measurements were 1.47 cm, 2.11 cm and 2.79 cm at “1 cm,” “2 cm” and “3 cm” digital vaginal measurement, respectively. However, there was extensive overlap between digitally and sonographically measured cervical length. Prediction accuracy of cervical length and head perineum distance was poor. The area under curve (AUC) of receiver operating characteristic (ROC) curve were 0.433 for sonographic cervical length and 0.501 for HPD. Conclusion: Transperineal sonographical assessment of cervical length and head perineum distance before labor was not useful in predicting the time of delivery. However, it can be explored as an alternative assessment method when digital vaginal examination is not preferred. [ABSTRACT FROM AUTHOR]

Objectives To evaluate the association between ultrasound measured angle of progression (AoP) during labor and time to delivery (TTD) or second stage of labor duration (SSLD). Methods This systematic review (SR) was reported according to PRISMA statement 2020. Databases investigated were MEDLINE, CINHAL, Embase, Scopus, Web of Science. Other sources were references or related articles of included studies, Google Scholar, clinicaltrials.gov, thesis, expert groups. Main keywords: angle of progression, transperineal ultrasound, delivery, labor. Inclusion criteria were observational studies, single term pregnancy, cephalic presentation, AoP measurement during the first stage of labor or at the beginning of the second stage, without date restrictions. Language included: English, Italian, French, Spanish. Studies selection, evaluation of the risk of bias with Quality in Prognosis Studies (QUIPS) tool, and data extraction were carried out by two authors blindly and independently, with disagreement resolution by a third author. Qualitative summary of the results. This SR was registered on PROSPERO, number CDR42021232015. Results Of 428 records, 14 were included, published from 2009 to 2021, cumulatively analyzing 2498 women. All studies highlighted an inverse relationship between AoP and TTD. Some have identified an AoP cutoff, contained in a range between 110° and 129°, beyond which the duration of labor is significantly shorter. Others, a range between 137° and 160°, beyond which the duration of the expulsive period is significantly shorter. Finally, some factors influence this association: parity, epidural, and oxytocin. Conclusions This SR confirms a significant association between AoP in labor and TTD. In clinical practice, AoP could help to predict the duration of labor, facilitating decision-making. The main limitations of this SR were the low number of included studies, their heterogeneity, and the high risk of bias related to confounding factors. For future research, further studies are needed to increase the strength of the evidence, obtain stratified results according to patients’ characteristics and investigate groups of patients who have not yet been evaluated. [ABSTRACT FROM AUTHOR]

This paper advances three arguments. First, current working-time patterns are destructive of justice, especially in terms of environmental sustainability, gender equality, and personal autonomy. Second, making fundamental progress towards these goals requires secure, quality, short-time work for all. This refers to an economic system that would guarantee everyone a decent, secure, existence at roughly 30 hours or less of market work, as well as actively discouraging longer hours. This discouragement should take the form of "soft" state policies as well as new cultural norms; it should not take "hard" forms of state violence. Third, liberal proceduralists are wrong to believe that individuals should be free from state regulation to simply choose the amount of work/leisure that they see fit, since doing so creates all kinds of harms for other people. In fact, the state should actively disincentivize long work hours in order to augment social justice. [ABSTRACT FROM AUTHOR]

Based on the appearance of tomatoes, it is possible to determine whether they are diseased. Detecting diseases early can help the yield losses of tomatoes through timely treatment. However, human visual inspection is expensive in terms of the time and labor required. This paper presents an automatic tomato disease monitoring system using modular and extendable mobile robot we developed in a greenhouse. Our system automatically monitors whether tomatoes are diseased and conveys the specific locations of diseased tomatoes to users based on the location information of the image data collected by the robot, such that users can adopt timely treatment. This system consists of two main parts: a modular, extendable mobile robot that we developed and a server that runs a tomato disease detection program. Our robot is designed to be configured and extended according to the actual height of the tomato vines, thus ensuring that the monitoring range covers most tomatoes. It runs autonomously between two rows of tomato plants and collects the image data. In addition to storing the image data of tomatoes, the data server runs a program for detecting diseases. This program contains a two-level disease detection model: a detection network for detecting diseased tomatoes and a validation network for verifying the detection results. The validation network verifies the results of the detection network by classifying the outputs of the detection network, thus reducing the false positive rate of the proposed system. Experimentally, this work focuses on the blossom-end rot of tomatoes. In this paper, YOLOv5, YOLOv7, Faster R-CNN, and RetinaNet are trained and compared on datasets divided by different conditions. YOLOv5l showed the best results on the randomly divided dataset: the mAP@0.5 reached 90.4%, and the recall reached 85.2%. Through the trained YOLOv5l, a dataset was created for training the classification networks: ResNet, MobileNet, and DenseNet. MobileNetv2 achieved the best overall performance with a 96.7% accuracy and a size of 8.8 MB. The final deployment to the system included YOLOv5l and MobileNetv2. When the confidence threshold of YOLOv5l was set to 0.1, the two-level model's false positive and false negative rates were 13.3% and 15.2%, respectively. Compared to using YOLOv5l alone, the false positive rate decreased by 5.7% and the false negative rate increased by only 2.3%. The results of the actual operation of the proposed system reveal that the system can inform the user of the locations of diseased tomatoes with a low rate of false positives and false negatives, and that it is an effective and promotable approach. [ABSTRACT FROM AUTHOR]

Background: The implementation of person-centred care (PCC) is advocated worldwide. Stakeholders in charge of implementing PCC as a broad-scale change across the health care sector face two intertwined and complex challenges. First, making sense of PCC as an intervention with complex innovation characteristics and second, staging implementation of PCC by choosing appropriate implementation strategies. We aimed to explore one of these challenges by tracking, naming, specifying, and comparing which strategies and how strategies were enacted to support the implementation of more PCC in a real-world setting represented by one health care region in Sweden.Methods: A case study with seven embedded units at two organisational levels within a health care region was conducted from 2016 to 2019. Data were collected from three sources: activity logs, interviews, and written documents. Strategies were identified from all sources and triangulated deductively by name, definition, and cluster in line with the taxonomy Expert Recommendations for Implementing Change (ERIC) and specified according to recommendations by Proctor and colleagues as actor, action, action target, temporality, dose, outcome, and justification.Results: Four hundred thirteen activities were reported in logs, representing 43 discrete strategies identified in ERIC (n = 38), elsewhere (n = 1), or as emerging strategies (n = 4). The highest reported frequencies of discrete strategies were identified as belonging to two clusters: Train and educate stakeholders (40%) and Develop stakeholder interrelationships (38%). We identified a limited number of strategies belonging to the cluster Use evaluative and iterative strategies (4.6%) and an even smaller number of strategies targeting information to patients about the change initiative (0.8%). Most of the total dose of 11,076 person-hours in the 7 units was spent on strategies targeting health care professionals who provide PCC (81.5%) while the dose of strategies targeting support functions was 18.5%.Conclusions: Our findings show both challenges and merits when strategies for implementation of PCC are conducted in a real-world setting. The results can be used to support and guide both scientists and practitioners in future implementation initiatives. [ABSTRACT FROM AUTHOR]

In industrial machinery, rolling bearings are often rated as the most likely to fail in mechanical systems due to excessive working stress. Therefore, effective methods to diagnose the faults in rolling bearings are becoming necessary and required to ensure economic efficiency and manufacturing reliability. Recently, several studies tried to develop deep learning models for intelligent fault diagnosis based on traditional methods. However, creating an effective method for fault recognition is still a major obstacle due to varying operating conditions, large amount of collected data and redundant noise in measured vibration signals. Advanced signal processing techniques and traditional strategies often consist of shallow constructs that suffer from learning a huge amount of data, losing valuable fault information, yielding in low accuracy and labor time losses. In this paper, a combination method of long short-term memory with large margin nearest neighbor (LSTM-LMNN) is designed to address the above issues and effectively recognize multi-faults in mechanical rotating machines. Different from traditional LSTMs, the proposed LSTM-LMNN utilizes a powerful orthogonal weight initialization technique to memorize the critical information of faults during parameters updating and strongly organizing the samples of each condition in pattern classification process. Two experimental studies of bearing fault diagnosis demonstrate that the proposed LSTM-LMNN model outperformed other existing methods in terms of diagnostic efficiency, stability, and reliability. [ABSTRACT FROM AUTHOR]

An objective stereo video quality assessment (SVQA) strives to be consistent with human visual perception while ensuring a low time and labor cost of evaluation. The temporal–spatial characteristics of video make the data processing volume of quality evaluation surge, making an SVQA more challenging. Aiming at the effect of distortion on the stereoscopic temporal domain, a stereo video quality assessment method based on the temporal–spatial relation is proposed in this paper. Specifically, a temporal adaptive model (TAM) for a video is established to describe the space–time domain of the video from both local and global levels. This model can be easily embedded into any 2D CNN backbone network. Compared with the improved model based on 3D CNN, this model has obvious advantages in operating efficiency. Experimental results on NAMA3DS1-COSPAD1 database, WaterlooIVC 3D Video Phase I database, QI-SVQA database and SIAT depth quality database show that the model has excellent performance. [ABSTRACT FROM AUTHOR]

To determine the optimal week for labor induction in women with diet-controlled gestational diabetes mellitus by comparing differences in perinatal and neonatal outcomes of labor induction to expectant management at different gestational weeks. Methods: This was a retrospective analysis of a prospectively recruited cohort of 797 singleton pregnancies complicated by diet-controlled gestational diabetes mellitus that were diagnosed, treated, and delivered after 37 weeks in a tertiary, university-affiliated perinatal center between January 2016 and December 2021. Results: The incidence of neonatal complications was highest when delivery occurred at 37 weeks, whereas fetal macrosomia occurred mostly at 41 weeks (20.7%); the frequency of large for gestational age infants did not differ between the groups. Conversely, the best neonatal outcomes were observed at 40 weeks due to the lowest number of neonates requiring phototherapy for neonatal jaundice (1.7%) and the smallest proportion of neonates experiencing composite adverse neonatal outcomes defined as neonatal hypoglycemia, phototherapy, clavicle fracture, or umbilical artery pH < 7.15 (10.4%). Compared with expectant management, the risk for neonatal hypoglycemia was increased for induction at 39 weeks (adjusted odds ratio 12.29, 95% confidence interval 1.35–111.75, p = 0.026) and that for fetal macrosomia was decreased for induction at 40 weeks (adjusted odds ratio 0.11, 95% confidence interval 0.01–0.92, p = 0.041), after adjusting for maternal pre-pregnancy body mass index, nulliparity, and mean pregnancy A1c. Conclusions: The lowest rate of neonatal complications was observed at 40 weeks. Labor induction at 40 weeks prevented fetal macrosomia. [ABSTRACT FROM AUTHOR]

An ideal molecular diagnostic method should be sensitive, specific, low cost, rapid, portable, and easy to operate. Traditional nucleic acid detection methods based mainly on PCR technology have not only high sensitivity and specificity, but also some limitations, such as the need for expensive equipment and skilled technicians, being both time and labor intensive, and difficult to implement in some regions. However, with the continuous development of CRISPR-Cas technology and its application in molecular diagnosis, new approaches have been used for the construction of molecular diagnostic systems. In this review, we discuss recent advances in CRISPR-based molecular diagnostic technologies and highlight the revolution they bring to the field of molecular diagnostics. CRISPR-Cas-mediated diagnostics can detect various pathogens, cancer biomarkers, and SNPs with high specificity, speed, low cost, and portability. The combination of Cas proteins with biosensors, biochips, biomagnetic beads, isothermal amplification, lateral flow, protein aptamers, and other technologies has resulted in the development of new diagnostic methods. Multiplexed CRISPR nucleic acid detection systems complete the detection of 169 viruses for diagnosing different diseases in a single sample, with the help of microfluidic technology. CRISPR-mediated antibody diagnosis technology can recognize thousands of antibodies in a sample simultaneously. The potential of CRISPR-Cas biosensing technologies is inspiring researchers to develop next-generation diagnostics platforms. [ABSTRACT FROM AUTHOR]

This study aims to analyze the abuse of power exercised by institutions against the freedom of expression of workers in the labor context and the time it takes to resolve this problem. The methodology is qualitative, through content analysis of the rulings of the Inter-American Court of Human Rights on Peru and Venezuela. It is concluded that institutions abuse their power and violate freedom of expression and the right to work against the victims, who find justice after a long judicial process that lasts more than fifteen years. [ABSTRACT FROM AUTHOR]

Bio-analysis is related to the analysis of analytes (drugs, metabolites, biomarkers) in biological matrix and it involves several steps from sample collection to analysis and data reporting. Sample collection from clinical or preclinical studies; then sending the samples to laboratory for analysis, later the sample preparation will be carried. Stable sample preparation method could be achieved. The role of sample preparation is to remove interferences from the biological matrix and to extract the analyte of interest and to improve analytical system performance. Sample preparation is often labor intensive and time consuming. Final step of the analysis is the quantification of analyte by using analytical instruments. Among them, Liquid chromatography-tandem mass spectrometry (LC-MS/MS) is method of choice in bioanalytical laboratories. This is due to high selectivity and high sensitivity of the LC-MS/MS technique. Development and validation of analytical method play an important role in the discovery, development and manufacturing of pharmaceuticals. Every year, number of drugs entered into the market; hence it is mandatory to develop newer analytical methods for such drugs. After the development, it becomes necessary to validate the new analytical method. Method development is the process which proves that the analytical method is acceptable for use. Validation of analytical method gives information about various stages and parameters like accuracy, precision, linearity, Limit of Detection, Limit of Quantification, specificity, range and robustness. Validation should be done as per ICH regulatory guidelines. [ABSTRACT FROM AUTHOR]

Pathological images play an important role in the diagnosis, treatment, and prognosis of cancer. Usually, pathological images contain complex environments and cells of different shapes. Pathologists consume a lot of time and labor costs when analyzing and discriminating the cells in the images. Therefore, fully annotated pathological image data sets are not easy to obtain. In view of the problem of insufficient labeled data, we input a large number of unlabeled images into the pretrained model to generate accurate pseudo-labels. In this article, we propose two methods to improve the quality of pseudo-labels, namely, the pseudo-labeling based on adaptive threshold and the pseudo-labeling based on cell count. These two pseudo-labeling methods take into account the distribution of cells in different pathological images when removing background noise, and ensure that accurate pseudo-labels are generated for each unlabeled image. Meanwhile, when pseudo-labels are used for model retraining, we perform data distillation on the feature maps of unlabeled images through an attention mechanism, which further improves the quality of training data. In addition, we also propose a multi-task learning model, which learns the cell detection task and the cell count task simultaneously, and improves the performance of cell detection through feature sharing. We verified the above methods on three different data sets, and the results show that the detection effect of the model with a large number of unlabeled images involved in retraining is improved by 9%–13% compared with the model that only uses a small number of labeled images for pretraining. Moreover, our methods have good applicability on the three data sets. [ABSTRACT FROM AUTHOR]

Owing to the continuous increase in the damage to farms due to wild animals' destruction of crops in South Korea, various methods have been proposed to resolve these issues, such as installing electric fences and using warning lamps or ultrasonic waves. Recently, new methods have been attempted by applying deep learning-based object-detection techniques to a robot. However, for effective training of a deep learning-based object-detection model, overfitting or biased training should be avoided; furthermore, a huge number of datasets are required. In particular, establishing a training dataset for specific wild animals requires considerable time and labor. Therefore, this study proposes an Extract–Append data augmentation method where specific objects are extracted from a limited number of images via semantic segmentation and corresponding objects are appended to numerous arbitrary background images. Thus, the study aimed to improve the model's detection performance by generating a rich dataset on wild animals with various background images, particularly images of water deer and wild boar, which are currently causing the most problematic social issues. The comparison between the object detector trained using the proposed Extract–Append technique and that trained using the existing data augmentation techniques showed that the mean Average Precision (mAP) improved by ≥2.2%. Moreover, further improvement in detection performance of the deep learning-based object-detection model can be expected as the proposed technique can solve the issue of the lack of specific data that are difficult to obtain. [ABSTRACT FROM AUTHOR]