Mixed Block Research Articles

Stress assignment in reading aloud in Spanish

AbstractCorrect stress assignment is a requirement for fluent reading in alphabetic languages. This study focuses on two nonlexical mechanisms at the core of stress assignment. In particular, the use of a default stress pattern (e.g., penultimate stress) and the Spanish stress mark. In Experiment 1, participants read aloud words and pseudowords with different stress types (on the antepenultimate or the penultimate syllable), and with or without a stress mark. Results showed longer reaction times (RTs) for words and pseudowords with antepenultimate stress. However, as words with antepenultimate stress always have a stress mark, it could be argued that stress type differences could be due to the presence of the stress mark. In Experiment 2, using a priming procedure participants read aloud words and pseudowords in pure versus mixed stress blocks. Again, words and pseudowords with antepenultimate stress were read slower (longer RTs), suggesting that previous differences were due to stress mark rather than stress type. These results indicate that processing stress marks is cognitively demanding when reading in Spanish.

The computer desktop image compression based on clustering algorithm

SummaryWith the rapid development of computer software and hardware technology and network technology, aiming at the limitations of the traditional image compression standards and the deficiencies of the existing computer desktop image compression methods. By analyzing the characteristics of computer desktop image, according to the characteristics of desktop compression, a compression scheme based on high efficiency video coding (HEVC) and color clustering is proposed, which divides blocks into text/graphics blocks, natural image blocks and mixed blocks based on the features of histogram information and texture information of blocks. In block division and classification, an adaptive dynamic block classification algorithm is proposed which is different from the traditional block partitioning. Compared with the traditional method, the new block classification algorithm can save the code stream and improve the classification accuracy.

Mixed slip-trip perturbation training for improving reactive responses in people with chronic stroke.

This study determined the effect of mixed (slip- and trip-like stance perturbation) training on reactive responses in people with chronic stroke (PwCS) and examined modulation of their reactive responses on higher intensity perturbations posttraining (scaling). Twelve PwCS were exposed to consecutive blocks of treadmill-based slip-like and trip-like perturbations and mixed-stance perturbations. A higher intensity trial was provided postblock and postmixed training. Postural stability [center-of-mass position (CoMP) and velocity (CoMV)], compensatory step length, step count, and trunk angle were examined. PwCS demonstrated an anterior positioning of the CoM, increased step length, and reduced compensatory step count with slip-like block training (P < 0.05). Trip-like block training resulted in reductions in step count, step length, and trunk angle (P < 0.05); however, CoMP remained unchanged (P > 0.05). With mixed training, there was a decrease rather than an increase in step length for slip-like perturbations but a continued decrease in step length and trunk angle was seen on trip-like perturbations (P < 0.05); however, CoMP and step count remained unchanged for both. For both perturbations, the higher intensity trials demonstrated no change from the last block trial. Postmixed block, the higher intensity trial demonstrated an increase only in step count on trip-like perturbation. Between postblock and postmixed higher intensity trials, an increase in step count and decrease in step length was noted only for slip-like perturbations. Block training with slip- and trip-like stance perturbations can enhance reactive responses among PwCS. Although mixed perturbation training continued to improve trip-induced adaptation, prior slip-induced adaptive changes were not maintained and further slip-adaptation was not seen. PwCS demonstrated partial scaling of reactive responses postblock and postmixed training.NEW & NOTEWORTHY Block perturbation training led to development of favorable reactive responses to counteract treadmill-based, slip-like and trip-like stance perturbations among people with chronic stroke. During mixed block, previously acquired adaptive changes in reactive responses from slip-block training were not maintained, probably due to interference offered by trip block. Instead, on trip-like perturbations, trip block-induced adaptation was maintained and continued to show further improvement. Our findings might provide future direction for designing effective mixed perturbation training paradigms to counteract both opposing perturbation types.

Preparation and Characterization of Photoactive Anatase TiO2 from Algae Bloomed Surface Water

The purpose of the study was to effectively treat algae bloomed water while using a Ti-based coagulant (TiCl4) and recover photoactive novel anatase TiO2 from the flocculated sludge. Conventional jar tests were conducted in order to evaluate the coagulation efficiency, and TiCl4 was found superior compared to commercially available poly aluminum chloride (PAC). At a dose of 0.3 g Ti/L, the removal rate of turbidity, chemical oxygen demand (COD), and total phosphorus (TP) were measured as 99.8%, 66.7%, and 96.9%, respectively. Besides, TiO2 nanoparticles (NPs) were recovered from the flocculated sludge and scanning electron microscope (SEM), energy dispersive X-ray spectroscope (EDX), and X-ray diffraction (XRD) analysis confirmed the presence of only anatase phase. The recovered TiO2 was found to be effective in removing gaseous CH3CHO and NOx under UV-A lamp at a light intensity of 10 W/m2. Additionally, the TiO2 mixed mortar blocks that were prepared in this study successfully removed atmospheric nitrogen oxide (NOx) under UV irradiance. This study is one of the first to prepare anatase TiO2 from flocculated algal sludge and it showed promising results. Further research on this novel TiO2 concerning internal chemical bonds and shift in the absorbance spectrum could explore several practical implications.

Automatic Fabric Defect Detection Using Cascaded Mixed Feature Pyramid with Guided Localization.

Generic object detection algorithms for natural images have been proven to have excellent performance. In this paper, fabric defect detection on optical image datasets is systematically studied. In contrast to generic datasets, defect images are multi-scale, noise-filled, and blurred. Back-light intensity would also be sensitive for visual perception. Large-scale fabric defect datasets are collected, selected, and employed to fulfill the requirements of detection in industrial practice in order to address these imbalanced issues. An improved two-stage defect detector is constructed for achieving better generalization. Stacked feature pyramid networks are set up to aggregate cross-scale defect patterns on interpolating mixed depth-wise block in stage one. By sharing feature maps, center-ness and shape branches merges cascaded modules with deformable convolution to filter and refine the proposed guided anchors. After balanced sampling, the proposals are down-sampled by position-sensitive pooling for region of interest, in order to characterize interactions among fabric defect images in stage two. The experiments show that the end-to-end architecture improves the occluded defect performance of region-based object detectors as compared with the current detectors.

Desinging Analog Mixed Signal Circuits Using Graphene Nano Ribbon Field Effect Transistors

Graphene is a 2D material formed by planar honeycomb placement of Carbon atoms. Besides its many superior physical properties it has superior electronic properties foremost of which is the high mobility it possesses. Due to this high mobility many Graphene based transistors have been designed. Graphene nano ribbons exhibit a band gap property, which is crucial for implementing transistors as switches. Moreover there exist models for these Graphene Nano Ribbon devices. In this work we designed and simulated analog mixed signal blocks using Graphene Nano Ribbon transistors. The particular blocks that we used included telescopic amplifiers and StrongARM latches. Next we compared these blocks’ performances against the same blocks implemented in 14nm high performance Silicon CMOS transistors. As a result we observed that the graphene transistors could attain comparable performances to circuits designed in 14nm CMOS. Specifically Graphene blocks can reach up to 80% of the bandwidth of Silicon devices. However Graphene devices have greater power consumption as a result of higher leakage current.

Segmentation of Cell Images Based on Improved Deep Learning Approach

The improved U_net algorithm based on mixed convolution blocks (McbUnet), which combines the advantages of U-Net and residual learning, is proposed for cell image segmentation in this paper. The network is mainly composed of two kinds of mixed convolution blocks. There are three main benefits to this algorithm. First, the convolution block can utilize different size kernels to overcome the limitation of a single size convolution kernel in traditional deep convolution. Second, in the mixed convolution blocks, two hyperparameters (Width multiplier and Resolution multiplier) are used to quickly adjust the model to fit a specific environment. Third, the residual paths are improved. We test the proposed network and compare it with other recent segmentation methods based on deep learning. The proposed method is superior to comparison methods, which shows its effectiveness.

Mixed Precision Block Fused Multiply-Add: Error Analysis and Application to GPU Tensor Cores

Computing units that carry out a fused multiply-add (FMA) operation with matrix arguments, referred to as tensor units by some vendors, have great potential for use in scientific computing. However, these units are inherently mixed precision, and existing rounding error analyses do not support them. We consider a mixed precision block FMA that generalizes both the usual scalar FMA and existing tensor units. We describe how to exploit such a block FMA in the numerical linear algebra kernels of matrix multiplication and LU factorization and give detailed rounding error analyses of both kernels. An important application is to GMRES-based iterative refinement with block FMAs, about which our analysis provides new insight. Our framework is applicable to the tensor core units in the NVIDIA Volta and Turing GPUs. For these we compare matrix multiplication and LU factorization with TC16 and TC32 forms of FMA, which differ in the precision used for the output of the tensor cores. Our experiments on an NVDIA V100 GPU confirm the predictions of the analysis that the TC32 variant is much more accurate than the TC16 one, and they show that the accuracy boost is obtained with almost no performance loss.

Scalable Graph Convolutional Networks With Fast Localized Spectral Filter for Directed Graphs

Graph convolutional neural netwoks (GCNNs) have been emerged to handle graph-structured data in recent years. Most existing GCNNs are either spatial approaches working on neighborhood of each node, or spectral approaches based on graph Laplacian. Compared with spatial-based GCNNs, spectral-based GCNNs are capable of highly exploiting graph structure information, but always regard graphs undiredcted. Actually, there are many scenarios where the graph structures are directed, such as social networks, citation networks, etc. Treating graphs undirected may lose important information, which is helpful for graph learning tasks. This motivate us to construct a spectral-based GCNN for directed graphs. In this paper, we propose a scalable graph convolutional neural network with fast localized convolution operators derived from directed graph Laplacian, which is called fast directed graph convolutional network (FDGCN). FDGCN can directly work on directed graphs and can scale to large graphs as the convolution operation is linear with the number of edges. Furthermore, we find that FDGCN can unify the graph convolutional network (GCN), which is a classic spectral-based GCNN. The mechanism of FDGCN is thoroughly analyzed from spatial aggregation point of view. Since previous work has confirmed that considering uncertainty of graph could promote GCN a lot, the proposed FDGCN is further enhanced through extra training epochs on random graphs generated by mixed membership stochastic block model (MMSBM). Experiments are conducted for semi-supervised node classification tasks to evaluate the performance of FDGCN. Results show that our model can outperform or match state-of-the-art models in most cases.

A new experimental study on fly ash, lime and dredged sediment mixed block as an alternative eco-friendly building materials

A new experimental study on fly ash, lime and dredged sediment mixed block as an alternative eco-friendly building materials

Effect of Cognitive Behavioral Therapy for Insomnia on Insomnia Symptoms for Individuals With Type 2 Diabetes: Protocol for a Pilot Randomized Controlled Trial.

BackgroundInsomnia symptoms are a common form of sleep difficulty among people with type 2 diabetes (T2D) affecting sleep quality and health outcomes. Several interventional approaches have been used to improve sleep outcomes in people with T2D. Nonpharmacological approaches, such as cognitive behavioral therapy for insomnia (CBT-I), show promising results regarding safety and sustainability of improvements, although CBT-I has not been examined in people with T2D. Promoting sleep for people with insomnia and T2D could improve insomnia severity and diabetes outcomes.ObjectiveThe objective of this study is to establish a protocol for a pilot randomized controlled trial (RCT) to examine the effect of 6 sessions of CBT-I on insomnia severity (primary outcome), sleep variability, and other health-related outcomes in individuals with T2D and insomnia symptoms.MethodsThis RCT will use random mixed block size randomization with stratification to assign 28 participants with T2D and insomnia symptoms to either a CBT-I group or a health education group. Outcomes including insomnia severity; sleep variability; diabetes self-care behavior (DSCB); glycemic control (A1c); glucose level; sleep quality; daytime sleepiness; and symptoms of depression, anxiety, and pain will be gathered before and after the 6-week intervention. Chi-square and independent t tests will be used to test for between-group differences at baseline. Independent t tests will be used to examine the effect of the CBT-I intervention on change score means for insomnia severity, sleep variability, DSCB, A1c, fatigue, sleep quality, daytime sleepiness, and severity of depression, anxiety, and pain. For all analyses, alpha level will be set at .05.ResultsThis study recruitment began in February 2019 and was completed in September 2019.ConclusionsThe intervention, including 6 sessions of CBT-I, will provide insight about its effect in improving insomnia symptoms, sleep variability, fatigue, and diabetes-related health outcomes in people with T2D and those with insomnia symptoms when compared with control.Trial RegistrationClinicalTrials.gov NCT03713996; https://clinicaltrials.gov/ct2/show/NCT03713996International Registered Report Identifier (IRRID)DERR1-10.2196/14647

First Report of Watermelon Green Mottle Mosaic Virus in North America

In 2013, cucumber green mottle mosaic virus (CGMMV), a seed-transmitted cucurbit-infecting member of the genus Tobamovirus, was detected in California (Tian et al. 2014). CGMMV is a quarantined pathogen for which the California Department of Food and Agriculture monitors. Diagnostic samples suspected of CGMMV infection led to the identification of a different virus, watermelon green mottle mosaic virus (WGMMV), of the genus Tobamovirus, in November 2017. WGMMV was recently described by Cheng et al. (2018) infecting watermelon in Taiwan. In November 2017, two opo gourd fruits exhibiting CGMMV-like symptoms collected from a Santa Clara County farmer’s market, and 25 leaf samples from a mixed cucurbit production block from a Fresno County farm were tested for CGMMV by ELISA (Agdia, Elkhart, IN) and transmission electron microscopy. Most samples were CGMMV positive. However, rigid rod-shaped particles (∼18 × 300 nm) were detected from several CGMMV-negative samples. These samples tested positive by ELISA against tobacco mosaic virus (Agdia), indicating the presence of a serologically related virus. Initial nucleic acid analysis of the 2017 isolate by reverse-transcription polymerase chain reaction (RT-PCR) from total plant RNA using tobamovirus primers, as previously described by Dovas et al. (2004), resulted in a 497-nucleotide (nt) amplicon whose sequence aligned with other tobamovirus RNA-dependent RNA-polymerase sequences in GenBank. Sanger sequencing of this amplicon and 5′ and 3′ rapid amplification of cDNA ends (RACE) of genomic RNA (FirstChoice RLM-RACE kit, Thermo Fisher Scientific, Waltham, MA) with primer walking resulted in assembling the full 6,482-nt genome, which was deposited in GenBank (accession MK070867). An NCBI BLAST search indicates the isolate shares 98% sequence identity with WGMMV (accession MH837097) and 82% with cucumber mottle virus (accession AB261167) (Altshul et al. 1990; Orita et al. 2007). WGMMV-positive samples came from opo gourd (Lagenaria siceraria), fuzzy gourd (Benincasa hispida), Asian pumpkin (Cucurbita pepo), Japanese cucumber (Cucumis sativus), and bitter melon (Momordica charantia). Many plants were coinfected with CGMMV and WGMMV, but single infections were identified by RT-PCR from bitter melon and used for mechanical transmission. Detection primers were CGMMV_CP_F, CTTACAATCCGATCACACCTAG; CGMMV_CP_R, CTAAGCTTTCGAGGTGGTAGC; WGMMV4F, CTGCTAAGAGGGTTTATG; and WGMMV4R, CTTGGAAATCCGGTAAG. Transmission studies using Nicotiana benthamiana, sugar pumpkin, cucumber, watermelon, and Chenopodium amaranticolor were carried out as previously described (Ciuffo et al. 2016). Control plants were mock inoculated with buffer. At 10 days postinoculation, plants inoculated with infected leaf tissue, except C. amaranticolor, had slightly distorted leaves, mild mottling, and a crinkled appearance on new growth. Distal leaves of inoculated plants, except C. amaranticolor, tested positive for WGMMV by RT-PCR, and mock-inoculated plants were negative. C. amaranticolor developed local lesions on inoculated leaves. All plants were CGMMV negative by RT-PCR. During this work a second WGMMV detection occurred in June 2018 in Fresno County, also from a mixed cucurbit field. Both detections represent the first time WGMMV has been identified in California and North America and the second detection of the virus in cucurbit crops. The economic impact, means of transmission, and spread of this virus are currently unknown and merit further study.

Rewards Enhance Proactive and Reactive Control in Adolescence and Adulthood.

Cognitive control allows the coordination of cognitive processes to achieve goals. Control may be sustained in anticipation of goal-relevant cues (proactive control) or transient in response to the cues themselves (reactive control). Adolescents typically exhibit a more reactive pattern than adults in the absence of incentives. We investigated how reward modulates cognitive control engagement in a letter-array working memory (WM) task in 30 adolescents (12–17 years) and 20 adults (23–30 years) using a mixed block- and event-related functional magnetic resonance imaging design. After a Baseline run without rewards, participants performed a Reward run where 50% trials were monetarily rewarded. Accuracy and reaction time (RT) differences between Reward and Baseline runs indicated engagement of proactive control, which was associated with increased sustained activity in the bilateral anterior insula (AI), right dorsolateral prefrontal cortex (PFC) and right posterior parietal cortex (PPC). RT differences between Reward and No reward trials of the Reward run suggested additional reactive engagement of cognitive control, accompanied with transient activation in bilateral AI, lateral PFC, PPC, supplementary motor area, anterior cingulate cortex, putamen and caudate. Despite behavioural and neural differences during Baseline WM task performance, adolescents and adults showed similar modulations of proactive and reactive control by reward.

Structural and functional aspects of mannuronic acid–specific PL6 alginate lyase from the human gut microbe Bacteroides cellulosilyticus

Alginate is a linear polysaccharide from brown algae consisting of 1,4-linked β-d-mannuronic acid (M) and α-l-guluronic acid (G) arranged in M, G, and mixed MG blocks. Alginate was assumed to be indigestible in humans, but bacteria isolated from fecal samples can utilize alginate. Moreover, genomes of some human gut microbiome–associated bacteria encode putative alginate-degrading enzymes. Here, we genome-mined a polysaccharide lyase family 6 alginate lyase from the gut bacterium Bacteroides cellulosilyticus (BcelPL6). The structure of recombinant BcelPL6 was solved by X-ray crystallography to 1.3 Å resolution, revealing a single-domain, monomeric parallel β-helix containing a 10-step asparagine ladder characteristic of alginate-converting parallel β-helix enzymes. Substitutions of the conserved catalytic site residues Lys-249, Arg-270, and His-271 resulted in activity loss. However, imidazole restored the activity of BcelPL6-H271N to 2.5% that of the native enzyme. Molecular docking oriented tetra-mannuronic acid for syn attack correlated with M specificity. Using biochemical analyses, we found that BcelPL6 initially releases unsaturated oligosaccharides of a degree of polymerization of 2–7 from alginate and polyM, which were further degraded to di- and trisaccharides. Unlike other PL6 members, BcelPL6 had low activity on polyMG and none on polyG. Surprisingly, polyG increased BcelPL6 activity on alginate 7-fold. LC–electrospray ionization–MS quantification of products and lack of activity on NaBH4-reduced octa-mannuronic acid indicated that BcelPL6 is an endolyase that further degrades the oligosaccharide products with an intact reducing end. We anticipate that our results advance predictions of the specificity and mode of action of PL6 enzymes.

Influence of Periodizing Dietary Carbohydrate on Iron Regulation and Immune Function in Elite Triathletes.

Sleeping with low carbohydrate (CHO) availability is a dietary strategy that may enhance training adaptation. However, the impact on an athlete's health is unclear. This study quantified the effect of a short-term "sleep-low" dietary intervention on markers of iron regulation and immune function in athletes. In a randomized, repeated-measures design, 11 elite triathletes completed two 4-day mixed cycle run training blocks. Key training sessions were structured such that a high-intensity training session was performed in the field on the afternoon of Days 1 and 3, and a low-intensity training (LIT) session was performed on the following morning in the laboratory (Days 2 and 4). The ingestion of CHO was either divided evenly across the day (HIGH) or restricted between the high-intensity training and LIT sessions, so that the LIT session was performed with low CHO availability (LOW). Venous blood and saliva samples were collected prior to and following each LIT session and analyzed for interleukin-6, hepcidin 25, and salivary immunoglobulin-A. Concentrations of interleukin-6 increased acutely after exercise (p < .001), but did not differ between dietary conditions or days. Hepcidin 25 increased 3-hr postexercise (p < .001), with the greatest increase evident after the LOW trial on Day 2 (2.5 ± 0.9 fold increase ±90% confidence limit). The salivary immunoglobulin-A secretion rate did not change in response to exercise; however, it was highest during the LOW condition on Day 4 (p = .046). There appears to be minimal impact to markers of immune function and iron regulation when acute exposure to low CHO availability is undertaken with expert nutrition and coaching input.

Task switching and bilingualism in young and older adults: A behavioral and electrophysiological investigation

The current study investigated behavioral and electrophysiological (event-related potential; ERP) differences associated with task switching in a sample of young and older monolingual and bilingual adults. ERPs associated with task preparation (switch and mixing positivity) and task execution processes (N2 and P3b) were investigated. Participants performed a cued letter-number task switching paradigm that included single task and mixed task blocks, while their electroencephalography was recorded. Behavioral results revealed smaller switch and mixing costs in bilinguals relative to monolinguals, in both young and older participants. There were no ERP differences in the effect size of the cue-locked mixing and switch positivities, nor the target-locked mixing and switch N2 and P3b components. However, overall larger target-locked N2 amplitudes were observed in bilinguals relative to monolinguals. In addition, bilingual older adults exhibited smaller P3b amplitudes than monolingual older adults. The smaller behavioral mixing and switch costs observed in bilinguals suggest that bilinguals exhibit superior sustained attention and faster task-set reconfiguration processes compared to monolinguals. The ERP measures provide evidence for differences in brain processes between monolinguals and bilinguals and a reliance on different processing strategies in bilingual compared to monolingual older adults.

A Pipelined 2D Transform Architecture Supporting Mixed Block Sizes for the VVC Standard

For the next-generation video coding standard Versatile Video Coding (VVC), several new contributions have been proposed to improve the coding efficiency, especially in the transformation operations. This paper proposes a unified $32\times 32$ block-based transform architecture for the VVC standard that enables 2D Discrete Sine Transform-VII (DST-VII) and Discrete Cosine Transform-VIII (DCT-VIII) of all sizes. It mainly gives three contributions: 1) The N-Dimensional Reduced Adder Graph (RAG-n) algorithm is adopted to design the minimal adder-oriented computational units. 2) The storage of the asymmetric transform units can be realized in the dual-port SRAM-based transpose memory. 3) The pipelined 2D transformations of mixed block sizes are achieved with the throughput rate of 32 samples per cycle. The synthesis results indicate that this architecture can reduce area by up to 73.1% compared with other state-of-the-art works. Moreover, power saving ranging from 4.9% to 9.9% can be achieved. Regarding the transpose memory, at least 21.9% of the area can be saved by using SRAM.

CPU-accelerated explicit discontinuous deformation analysis and its application to landslide analysis

• Proposed explicit DDA in two-dimensional case. • Verified the accuracy of explicit DDA by comparing with analytical solution. • Simulated failure process of a mixed block slope in an experiment. • Reproduced the failure process of the Donghekou landslide. • Accelerated explicit DDA based on OpenMP and showed computing efficiency. An explicit discontinuous deformation analysis (DDA) that uses an explicit time integration procedure and an explicit calculation of interaction forces between blocks is proposed to overcome the limitations of conventional implicit DDA in simulating large-scale problems. The advantages of the explicit DDA are that (1) the global equilibrium equations are unnecessary to be assembled and the solving for unknowns of every block can be performed independently and conveniently, thereby reducing the computational effort and memory requirement; (2) the open-close iteration process is avoided because the interaction forces between blocks are calculated explicitly according to the initial information at the start of the current time step. The efficient parallel computing is very appropriate for the explicit DDA. To further improve its computational efficiency, the explicit DDA is paralleled based on OpenMP. The accuracy of the explicit DDA is verified through several numerical examples with analytical solutions, experimental data or field observation. Further, the computational efficiency is demonstrated by a series of models and the parallel speedup factor on 6 OpenMP threads is approximately 4.2. Conclusively, the explicit DDA is promising for analyzing blocky systems in large scale.

Surface Characterization, Antimicrobial Effectiveness, and Human Cell Response for a Biomedical Grade Polyurethane Blended with a Mixed Soft Block PTMO-Quat/PEG Copolyoxetane Polyurethane.

Infection is a serious medical complication associated with health care environments. Despite advances, the 5-10% incidence of infections for hospital patients is well documented. Sources of pathogenic organisms include medical devices such as catheters and endotracheal tubes. Offering guidance for curbing the spread of such infections, a model antimicrobial coating is described herein that kills bacteria on contact but is compatible with human cells. To achieve these characteristics, a novel blend of a conventional biomedical grade polyurethane (Tecoflex) with mixed soft block polyurethane is described. The functional polyurethane (UP-C12-50-T) has a copolyoxetane soft block P-C12-50 with quaternary ammonium (C12) and PEG-like side chains and a conventional poly(tetramethylene oxide) (PTMO, T) soft block. DSC and DMA data point to limited miscibility of UP-C12-50-T with Tecoflex. The blend of Tecoflex with 10 wt % UP-C12-50-T designated UP-C12-50-T-10 radically changed surface properties. Evidence for surface concentration of the P-C12-50 soft block was obtained by atomic force microscopy (AFM), dynamic contact angles (DCAs), zeta potentials (ζ), and X-ray photoelectron spectroscopy (XPS). The antimicrobial effectiveness of the blend coatings was established by the ASTM E2149 "shake flask" test for challenges of E. coli and a methicillin resistant strain of S. epidermidis. Cytocompatibility was demonstrated with an in vitro test designed for direct contact (ISO 10993-5). Growth of human mesenchymal stem cells (MSCs) beside and under UP-C12-50-T-10 indicated remarkable biocompatibility for a composition that is also strongly antimicrobial. Overall, the results point to a model coating with a level of P-C12-50 that combines high antimicrobial effectiveness and low toxicity to human cells.

Immobilization possibility of tannery wastewater contaminants in the tiles fixing mortars for eco-friendly land disposal

The Hazaribagh tannery area of Bangladesh is currently facing an enormous problem regarding the harmful impacts of wastewater produced from leather industries on the surrounding environment due to the presence of contaminants at a toxic level. As such, the current study aims to analyze the entrapment of tannery wastewater's pollutants inside the mortar specimens for sustainability. Two types of binding agents such as Portland Composite Cement (PCC) and Ready Mixed Dry Mortar (RMDM) were employed to prepare separate mortar pastes in which the collected tannery wastewater was used as mixing liquid. Also, five types of samples including brick walls made with only the PCC, where tiles walls and blocks constructed with both types of binding agents were built. Analytical results show that the surrogate contaminated water mixed mortar blocks possessed about 6–14% lower compressive strength than that of the blocks prepared with drinking water. Moreover, the examined heavy metals were observed below the limit of detection in the curing liquid of studied tiles walls during the whole test protocol of 360 days period. The explicit outcomes of this study might be a promising solution to minimize the effects of tannery wastewater contaminants on the environment by utilizing this wastewater as a mixing component in the tiles fixing mortar of walls and floors.