bluuebunny/crossref_metadata_2025_split huggingface dataset:
High-capacity adsorbents from stainless steel slag for the control of dye pollutants in water
Authors: Plaza Lorenzo , Castellote Marta , Nevshupa Roman , Jimenez-Relinque Eva 
Published: January 2021

AbstractAdsorbent materials for the control of dye pollutants in water were synthetized from stainless steel slag (SSS) using different acid-base treatments. Using HCl (SS-Cl) and HNO3 (SS-NO3) produced high-capacity adsorbents, with BET areas of 232 m2/g and 110 m2/g respectively. Specifically, the SS-Cl had a structure of amorphous silica sponge. Treatment with H2SO4 (SS-SO4) did not enhance the adsorption capabilities with respect to the raw sample (SSS). Activated carbon (AC) was also tested as reference. The materials were characterized by X-ray diffraction (XRD), X-ray fluorescence (XRF), N2 adsorption-desorption isotherms, scanning electron microscopy (SEM), energy dispersive X-ray analysis (EDX) zeta potential, and infrared spectroscopy (FTIR). Batch adsorption experiments with methylene blue (MB) showed that the maximum sorption capacities were 9.35 mg/g and 8.97 mg/g for SS-Cl and SS-NO3 at 240 h, respectively. These values, even at slower rate, were close to the adsorption capacity of the AC (9.72 mg/g). This behavior has been attributed to the high porosity in the range of nanopores (0.6–300 nm) and the high-surface area for both samples. Preferential involvement of certain functional groups in the adsorption of dye ions on their surface indicative of chemisorption has been found. Although optimization, repeatability, and reproducibility of the process and environmental assessment have to be done before practical applications, these preliminary results indicate that application of these cost-effective adsorbents from raw SSS may be used in water pollution treatment and contribute to the sustainable development of the steel manufacturing industry.
Whole-liver transcatheter arterial chemoinfusion and bland embolization with fine-powder cisplatin and trisacryl gelatin microspheres for treating unresectable multiple hepatocellular carcinoma
Authors: Imamura Akihiro , Taguchi Hidetoshi , Takano Hideyuki , Funatsu Hiroyuki , Nakamura Kazuyoshi , Arimitsu Hidehito , Chiba Satoshi 
Published: January 2021

Abstract
Purpose
To evaluate the safety and effectiveness of whole-liver transcatheter arterial chemoinfusion and bland embolization (TACBE) with fine-powder cisplatin and trisacryl gelatin microspheres for the treating unresectable multinodular hepatocellular carcinoma (HCC).

Materials and methods
The medical records of all patients who underwent TACBE sessions were retrospectively reviewed. 15 patients (11 men, 4 women; mean age, 72.5 years) and 22 procedures (BCLC B;17 C;5) were included in the analysis. The cisplatin resulting solution and microspheres were infused through a microcatheter placed nonselectively. Overall survival (OS) was defined as the time from commencement of initial TACBE until any cause of death. Toxicity was assessed by the CTCAE version 5.0, and the tumor response was evaluated by the mRECIST. Liver function was assessed by the albumin–bilirubin (ALBI) score.

Results
The 1-year OS rate was 64.6% (95% CI 0.438–0.955). Severe adverse effects were not observed except for grade 3 increase in the ALT, ALT, vasovagal episode. The objective response and disease control rare were 54.5% and 68.2%, respectively. The ALBI scores from pre-treatment to the follow-up ranged from − 2.39 to − 2.26 (p = 0.38).

Conclusion
Whole-liver TABCE with fine-powder cisplatin and trisacryl gelatin microspheres was well tolerated and effective in patients with multinodular HCC.
The Role of Endoscopic Ultrasound (EUS) in the Management of Gastric Varices
Authors: Thiruvengadam Sushrut Sujan , Sedarat Alireza 
Published: January 2021

Abstract
Purpose of Review
Gastric varices (GV) are an important complication of portal hypertension, and the current recommendation for management is beta-blocker therapy for primary prophylaxis and transjugular intrahepatic portosystemic shunt (TIPS) for active bleeding or secondary prophylaxis. Direct endoscopic injection of cyanoacrylate (CYA) glue has been investigated but has drawbacks including limited endoscopic characterization of GV and possible distal glue embolism. To this end, endoscopic ultrasound (EUS) has been pursued to help in characterization of GV, visualization of treatment in real time, and confirmation of obliteration with Doppler.

Recent Findings
In this paper, we review treatments for GV involving EUS, including EUS-guided injection of CYA and coils, either alone or in combination. We also discuss less common methods, including EUS-guided injection of thrombin and absorbable gelatin sponge. We then review literature comparing EUS-guided methods with direct endoscopic therapy and comparing individual EUS-guided methods with one another. We conclude by highlighting drawbacks of EUS in this field, including the unproven benefit over conventional therapy, lack of a standardized approach, and limited availability of expertise and necessary materials.

Summary
Novel EUS-based methods offer a unique opportunity to directly visualize and access gastric varices for treatment and obliteration. This may provide key advantages over current endoscopic or angiographic treatments. Comparative studies investigating the benefit of EUS over conventional therapy are needed.
Changes in Circulating Stem and Progenitor Cell Numbers Following Acute Exercise in Healthy Human Subjects: a Systematic Review and Meta-analysis
Authors: Schmid M. , Kröpfl J. M. , Spengler C. M. 
Published: January 2021

AbstractDespite of the increasing number of investigations on the effects of acute exercise on circulating stem and progenitor cell (SC) numbers, and in particular on respective subgroups, i.e. endothelial (ESC), hematopoietic (HSC), and mesenchymal (MSC) stem and progenitor cells, a consensus regarding mechanisms and extent of these effects is still missing. The aim of this meta-analysis was to systematically evaluate the overall-effects of acute exercise on the different SC-subgroups and investigate possible subject- and intervention-dependent factors affecting the extent of SC-mobilization in healthy humans. Trials assessing SC numbers before and at least one timepoint after acute exercise, were identified in a systematic computerized search. Compared to baseline, numbers were significantly increased for early and non-specified SCs (enSCs) until up to 0.5 h after exercise (0–5 min: +0.64 [Standardized difference in means], p < 0.001; 6–20 min: +0.42, p < 0.001; 0.5 h: +0.29, p = 0.049), for ESCs until 12–48 h after exercise (0–5 min: +0.66, p < 0.001; 6–20 min: +0.43 p < 0.001; 0.5 h: +0.43, p = 0.002; 1 h: +0.58, p = 0.001; 2 h: +0.50, p = 0.002; 3–8 h: +0.70, p < 0.001; 12–48 h: +0.38, p = 0.003) and for HSCs at 0–5 min (+ 0.47, p < 0.001) and at 3 h after exercise (+ 0.68, p < 0.001). Sex, intensity and duration of the intervention had generally no influence. The extent and kinetics of the exercise-induced mobilization of SCs differ between SC-subpopulations. However, also definitions of SC-subpopulations are non-uniform. Therefore, finding a consensus with a clear definition of cell surface markers defining ESCs, HSCs and MSCs is a first prerequisite for understanding this important topic.
Graphical Abstract
Automated survey of selected common plant species in Thai homegardens using Google Street View imagery and a deep neural network
Authors: Ringland John , Bohm Martha , Baek So-Ra , Eichhorn Matthew 
Published: January 2021

AbstractMost previous studies of homegardens have used labor-intensive boots-on-the-ground plant surveys, owner questionnaires, and interviews, limiting them to at most a few hundred homegardens. We show that automated analysis of publicly available imagery can enable surveys of much greater scale that can augment these traditional data sources. Specifically, we demonstrate the feasibility of using the high-resolution street-level photographs in Google Street View and an object-detection network (RetinaNet) to create a large-scale high-resolution survey of the prevalence of at least six plant species widely grown in road-facing homegardens in Thailand. Our research team examined 4000 images facing perpendicular to the street and located within 10 m of a homestead, and manually outlined all perceived instances of eleven common plant species. A neural network trained on these tagged images was used to detect instances of these species in approximately 150,000 images constituting views of roughly one in every ten homesteads in five provinces of northern Thailand. The results for six of the plant species were visualized as heatmaps of both the average number of target species detected in each image and individual species prevalence, with spatial averaging performed at scales of 500 m and 2.5 km. Urban-rural contrasts in the average number of target species in each image are quantified, and large variations are observed even among neighboring villages. Spatial heterogeneity is seen to be more pronounced for banana and coconut than for other species. Star gooseberry and papaya are more frequently present immediately outside of towns while dracaena and mango persist into the cores of towns.
Simultaneous Brg1 Knockout and MYCN Overexpression in Cerebellar Granule Neuron Precursors Is Insufficient to Drive Tumor Formation but Temporarily Enhances their Proliferation and Delays their Migration
Authors: Holdhof Dörthe , On Ji Hoon , Schoof Melanie , Göbel Carolin , Schüller Ulrich 
Published: January 2021

AbstractMedulloblastoma (MB) is the most common malignant brain tumor in childhood. According to the World Health Organization (WHO) classification of central nervous system (CNS) tumors, this embryonal tumor is divided into a wingless (WNT)-activated, Sonic hedgehog (SHH)-activated, and non-WNT/non-SHH entity. The latter is poorly defined but frequently carries mutations in Brahma-related gene 1 (BRG1) or amplifications of MYCN. Here, we investigated whether a combination of a Brg1 knockout and an overexpression of MYCN in cerebellar granule neuron precursors or multipotent neural stem cells is sufficient to drive brain tumor formation in mice. To this end, we generated Math1-creERT2::Brg1fl/fl::lslMYCN and hGFAP-cre::Brg1fl/fl::lslMYCN mice, respectively. We did not observe brain tumor formation in any of these models. hGFAP-cre::Brg1fl/fl::lslMYCN mice revealed severe CNS abnormalities with short survival, similar to the situation with a sole loss of Brg1, as we previously described. Investigation of Math1-creERT2::Brg1fl/fl::lslMYCN mice with a tamoxifen induction at postnatal day 3 revealed a regular survival but significant increase in cerebellar granule neuron precursor proliferation, followed by a delayed inward migration of these cells. This is in stark contrast to the hypoplastic cerebellum that we previously observed after embryonic deletion of Brg1 in Math1 positive cerebellar granule neurons. Our results indicate a time-specific function of Brg1 in cerebellar granule neuron precursors. Yet, the exact temporal and spatial origin of non-WNT/non-SHH MB remains unclear.
Institutional approaches for plant health provision as a collective action problem
Authors: Garcia-Figuera Sara , Grafton-Cardwell Elizabeth E. , Babcock Bruce A. , Lubell Mark N. , McRoberts Neil 
Published: January 2021

AbstractThe provision of plant health has public good attributes when nobody can be excluded from enjoying its benefits and individual benefits do not reduce the ability of others to also benefit. These attributes increase risk of free-riding on plant health services provided by others, giving rise to a collective action problem when trying to ensure plant health in a region threatened by an emerging plant disease. This problem has traditionally been addressed by government intervention, but top-down approaches to plant health are often insufficient and are increasingly combined with bottom-up approaches that promote self-organization by affected individuals. The challenge is how to design plant health institutions that effectively deal with the spatial and temporal dynamics of plant diseases, while staying aligned with the preferences, values and needs of affected societies. Here, we illustrate how Ostrom’s design principles for collective action can be used to guide the incorporation of bottom-up approaches to plant health governance in order to improve institutional fit. Using the ongoing epidemic of huanglongbing (HLB) as a case study, we examine existing institutions designed to ensure citrus health under HLB in Brazil, Mexico, the United States and Argentina, and discuss potential implications of Ostrom’s design principles for the collective provision of plant health under HLB and other plant diseases that are threatening food security worldwide. The discussion leads to an outline for the interdisciplinary research agenda that would be needed to establish the link between institutional approaches and plant health outcomes in the context of global food security.
Context-aware incremental learning-based method for personalized human activity recognition
Authors: Siirtola Pekka , Röning Juha 
Published: January 2021

AbstractThis study introduces an ensemble-based personalized human activity recognition method relying on incremental learning, which is a method for continuous learning, that can not only learn from streaming data but also adapt to different contexts and changes in context. This adaptation is based on a novel weighting approach which gives bigger weight to those base models of the ensemble which are the most suitable to the current context. In this article, contexts are different body positions for inertial sensors. The experiments are performed in two scenarios: (S1) adapting model to a known context, and (S2) adapting model to a previously unknown context. In both scenarios, the models had to also adapt to the data of previously unknown person, as the initial user-independent dataset did not include any data from the studied user. In the experiments, the proposed ensemble-based approach is compared to non-weighted personalization method relying on ensemble-based classifier and to static user-independent model. Both ensemble models are experimented using three different base classifiers (linear discriminant analysis, quadratic discriminant analysis, and classification and regression tree). The results show that the proposed ensemble method performs much better than non-weighted ensemble model for personalization in both scenarios no matter which base classifier is used. Moreover, the proposed method outperforms user-independent models. In scenario 1, the error rate of balanced accuracy using user-independent model was 13.3%, using non-weighted personalization method 13.8%, and using the proposed method 6.4%. The difference is even bigger in scenario 2, where the error rate using user-independent model is 36.6%, using non-weighted personalization method 36.9%, and using the proposed method 14.1%. In addition, F1 scores also show that the proposed method performs much better in both scenarios that the rival methods. Moreover, as a side result, it was noted that the presented method can also be used to recognize body position of the sensor.
Ensemble machine learning approach for classification of IoT devices in smart home
Authors: Cvitić Ivan , Peraković Dragan , Periša Marko , Gupta Brij 
Published: January 2021

AbstractThe emergence of the Internet of Things (IoT) concept as a new direction of technological development raises new problems such as valid and timely identification of such devices, security vulnerabilities that can be exploited for malicious activities, and management of such devices. The communication of IoT devices generates traffic that has specific features and differences with respect to conventional devices. This research seeks to analyze the possibilities of applying such features for classifying devices, regardless of their functionality or purpose. This kind of classification is necessary for a dynamic and heterogeneous environment, such as a smart home where the number and types of devices grow daily. This research uses a total of 41 IoT devices. The logistic regression method enhanced by the concept of supervised machine learning (logitboost) was used for developing a classification model. Multiclass classification model was developed using 13 network traffic features generated by IoT devices. Research has shown that it is possible to classify devices into four previously defined classes with high performances and accuracy (99.79%) based on the traffic flow features of such devices. Model performance measures such as precision, F-measure, True Positive Ratio, False Positive Ratio and Kappa coefficient all show high results (0.997–0.999, 0.997–0.999, 0.997–0.999, 0–0.001 and 0.9973, respectively). Such a developed model can have its application as a foundation for monitoring and managing solutions of large and heterogeneous IoT environments such as Industrial IoT, smart home, and similar.
Shear strength testing of consolidated claystones: breakpoint detection of shear stress versus shear displacement curves, a statistical approach
Authors: Rozgonyi-Boissinot Nikoletta , Buocz Ildikó , Hatvani István Gábor , Török Ákos 
Published: January 2021

AbstractThe evaluation of shear stress versus shear displacement curves is in the main focus of geotechnical engineering. Such curves, depending on the rock assessed, consist of a quasi-linear section, followed by a “kick” representing the peak shear strength, and a residual part, mostly parallel to the abscissa. The aim of the present study is to facilitate the future automatic detection of these crucial characteristics to take a step towards replacing their visual/analogue determination via modern statistical tools. Breakpoint detection methods (Cross-Entropy, Change Point Model) were applied to curves obtained from laboratory shear tests describing the shearing along discontinuities of nine Mont Terri Opalinus Claystone samples. Smooth and moderately rough claystone surfaces were studied. Results indicated that the end of the rising section and the kick observed on the shear strength curves was effectively approximated with the Change Point Model framework. An additional practical advantage of applying statistical tools such as breakpoint detection to shear strength determination is that it ensures the comparability of the obtained results.
Evaluation of water quality and potential metal contamination in ecologically important Bhindawas bird sanctuary, India
Authors: Shan Vandana , Singh S. K. , Haritash A. K. 
Published: January 2021

AbstractConsidering the environmental, agricultural, and ecological significance of Bhindawas wetland, the present study is the first comprehensive investigation to assess the water quality, determine the suitability of water for aquatic life in the wetland; and its suitability for irrigation in areas around the wetland. Twenty samples of water from Bhindawas wetland were analyzed and spatial variations of dissolved oxygen (DO), dissolved phosphate, nitrate, and biological oxygen demand (BOD5) were observed. The concentration of DO was higher in areas with shallow depth and rich growth of submerged vegetation compared to deeper areas with no vegetation. Spatial variations of phosphate, nitrate, and heavy metals correlated with nesting zone of birds, runoff from agricultural fields, and wastewater from adjoining villages, respectively. Values of heavy metal pollution index (HPI), heavy metal evaluation index (HEI), and degree of contamination (Cd) in water confirmed high level of metal contamination of the medium. Based on the water quality index (WQI), the water was unsuitable for aquatic life and use in agricultural utilization. It can be concluded that water quality of Bhindawas wetland was adversely affected by heavy metals, which is a cause of concern since this wetland is a temporary resort of migratory birds. Immediate intervention is required to improve the water quality, especially scrutiny and inspection of the added wastewater from surrounding villages, and runoff from adjoining agricultural fields.
Applicability of gypsum in selective removal of anionic dye molecules from aqueous medium
Authors: Hassan Mohammad Jobaer , Islam Md. Fahamidul , Akter Nahida , Uddin Md. Nizam , Abir Abrar Yasir , Aoun Sami Ben , Hasnat Mohammad A. 
Published: January 2021

AbstractThis article describes how selectively anionic organic molecules could be removed from aqueous medium using naturally available gypsum (GS) adsorbent. Gypsum (CaSO4.2H2O) shows strong interactions with anionic dye molecules while it dos not show any affinity towards cationic dye molecules. We have shown the removal efficiency of gypsum taking chlorazole yellow (anionic dye) and methylene blue (cationic dye) as examples of adsorbates. The GS has been to be even more effective than activated carbon in attaining chlorazole yellow (CY) removal. Three well-known kinetic equations e.g. pseudo-first-order, pseudo-second order and intraparticle diffusion were exploited to interpret the experimental data. Results show best fitting with second order kinetic process with excellent regression coefficient (r2 = 0.99) for the adsorption process. The equilibrium data were analyzed exploiting some adsorption isotherm models. It was apparent that the Freundlich isotherm model superbly fitted for CY dye adsorption process. And the maximum adsorption capacity, Qm, was obtained as 12.85 mg g−1 at room temperature. The negative values of Gibb’s free energy change (ΔGo) suggests that the CY dye molecule adsorption process is spontaneous in nature. Moreover, negative enthalpy change (ΔHo) indicates the exothermic nature of the adsorption process. The outcome could be exploited where anionic organic molecules are required to be separated, selectively.
Abrasiveness evaluation of complex strata based on PDC special energy consumption
Authors: Shengliang Zhang , Changhao Wang , Qiang Liu , Shibin Li 
Published: January 2021

AbstractThe rock abrasiveness is determined with various methods, which results in no uniform standard formed. In order to predict the PDC bit wear and the abrasiveness of complex strata, the force analysis of the PDC broken rock was carried out, and the bit axial load and torque were obtained, respectively. Then, the calculation model of PDC special energy consumption is deduced. Combining the typical distribution patterns of different strata, the specific energy prediction model of complex strata is established. The wear coefficient of PDC is obtained by the relationship between the triaxial compressive strength of rock and the specific energy of rock breaking, and the grading coefficient and grading standard of abrasiveness of the composite formation are derived, which led to the grading coefficient and grading standard of complex strata abrasiveness. The field test of a well in the north of Songliao Basin verified the rationality and effectiveness of the abrasiveness grading standards and provided the basis for the selection and design of the bit.