Miracle-dz/UniFAR-FTUs huggingface dataset:
Polyaromatic Carboxylate Ligands Based Zn(II) Coordination Polymers for Ultrasound-Assisted One-Pot Tandem Deacetalization–Knoevenagel Reactions

Solvothermal reactions between the polyaromatic group containing carboxylic acid pro-ligands 5-{(pyren-1-ylmethyl)amino}isophthalic acid (H2L1) and 5-{(anthracen-9-ylmethyl)amino}isophthalic acid (H2L2) with Zn(NO3)2·6H2O led to the formation of the new 1D coordination polymer [Zn(L1)(NMF)]n (1) and four other coordination polymers, [Zn(L1)(DMF)]n (2), [Zn(L1)(4,4′-Bipy)]n (3), [Zn(L2)(DMF)(H2O)2]n·n(H2O) (4) and [Zn2(L2)2(DMF)(CH3OH)]n (5), which were previously reported by our group. Single crystal X-ray diffraction analyses revealed that the CP 1 has a one-dimensional (1D) double-chain-type structure similar to that of CP 2. For CP 3, the assembly of the Zn(II) ion with a deprotonated L12− ligand and 4,4′-bipyridine produces a 3D network. CP 4 and 5 exhibit 1D linear and 2D layered-type structures. The ultrasound-assisted tandem reactions promoted by CPs have not yet been well studied. Thus, in the present work, we have investigated the catalytic activities of the newly synthesized CP 1, as well as of the other CPs 2–5, towards the tandem deacetalization–Knoevenagel condensation reactions of various acetals under ultrasonic irradiation. They proved to be highly efficient, with special emphasis on catalyst 1, which completely converted the substrate (benzaldehyde dimethyl acetal) into the desired product (2-benzylidenemalononitrile) after 2 h. The stability of the catalysts, namely regarding the action of ultrasonic radiation, was demonstrated by their reuse, where only a slight loss of activity was observed after four cycles. Heterogeneity was also demonstrated, and no leaching was detected over the various cycles.
Predicting Interest in Orthodontic Aligners: A Google Trends Data Analysis

Aligners are an example of how advances in dentistry can develop from innovative combinations of 3D technologies in imaging, planning and printing to provide new treatment modalities. With increasing demand for esthetic orthodontic treatment, aligners have grown in popularity because they are esthetically more pleasing and less obstructive to oral hygiene and other oral functions compared to fixed orthodontic appliances. To observe and estimate aligner treatment interest among Google Search users, Google Trends data were obtained and analyzed for the search term, “Invisalign”. A prediction of interest for the year 2022 for three European Union countries with the highest GDP was developed. “Invisalign” was chosen to represent all orthodontic aligners as the most searched term in Google Trends for aligners. This is the first study to predict interest in the query “Invisalign” in a Google search engine. The Prophet algorithm, which depends on advanced statistical analysis methods, positions itself as an automatic prediction procedure and was used to predict Google Trends data. Seasonality modeling was based on the standard Fourier series to provide a flexible model of periodic effects. The results predict an increase in “Invisalign” in Google Trends queries in the coming year, increasing by around 6%, 9% and 13% by the end of 2022 compared to 2021 for France, Italy and Germany, respectively. Forecasting allows practitioners to plan for growing demand for particular treatments, consider taking continuing education, specifically, aligner certification courses, or introduce modern scanning technology into offices. The oral health community can use similar prediction tools and methods to remain alert to future changes in patient demand to improve the responses of professional organizations as a whole, work more effectively with governments if needed, and provide better coordination of care for patients.
Debonding in bi-layer material systems under moisture effect : a multiscale approach

Bi-layer material systems are found in various engineering applications ranging from nano-scale components, such as thin films in circuit boards, to macro-scale structures such as adhesive bonding in aerospace and civil infrastructure applications. They are also found in many natural and biological materials such as nacre or bone. One of the most human-related applications of bi-layer material systems is the artificial tooth involving the bonding between the natural tooth and the metal cap glued with a polymer based material. The structural integrity of a bi-layer system depends on properties of both the interface and the constitutive materials. In particular, interfacial delamination has been observed as a major integrity issue. In this research, a comprehensive investigation on the interfacial debonding mechanism has been conducted both computationally and experimentally using an epoxy-silica system. In the computational approach, a multiscale model which can predict the intrinsic strength between organic and inorganic materials, based on a molecular dynamics simulation approach, is presented. The intrinsic strength between epoxy and silica derived from the molecular level can be used to predict the structural behavior of epoxy-silica interface at the macroscopic length-scale by invoking a finite element approach using a cohesive zone model developed in this research. In order to understand the moisture effect in a more comprehensive way, the free energy profile of the epoxy-silica bonded system describing the debonding process has been reconstructed for both dry and wet conditions and it is found that the adhesion between epoxy and silica, which is dominated by the van der Waals force and Coulombic interaction, can be weakened significantly (more than 68% reduction) in the presence of water. Experimental work involving two different approaches, namely "nanoindentation" and "superlayer" approaches, in characterizing the interfacial fracture toughness are presented and the advantages and disadvantages of these two approaches are discussed. The morphology of material in the vicinity of the interface has also been captured using the scanning electronic microscope (SEM). Experimental results show that the interface fracture energy decreases significantly after 4 weeks of moisture conditioning. Both the experimental and computational results show that water plays a main role in the interfacial deterioration. The mechanism of interfacial deterioration is explained using molecular dynamics simulation and a multiscale model of the epoxy-silica bonded system which is capable of predicting the macro-scale structural behavior based on the reconstructed free energy profile of the bonded system at the nano-scale. The multiscale modeling used in this research provides a powerful new approach to link nano-level to macro-level for complex material behavior.
Study on the physical and mechanical property of ordinary portland cement and fly ash paste

An experimental investigation has been carried out to study the physical and mechanical property of high volume fly ash cement paste. Ordinary portland cement was replaced by 0, 20, 30, 40, 50, 60 and 70% class F fly ash (by weight). Water- binder ratio in all mixture was kept constant at 0.3. Cube specimens were compacted in table vibrator. As expected bulk density decreases with fly ash increment in the mixture. Apparent porosity and water absorption value increases with replacement of cement by fly ash. Results confirm the decrease in compressive strength at 3, 7 and 28 day with fly ash addition and it is more prominent in case of more than 30% fly ash content mixes. Ultrasonic pulse velocity test results indicate that the quality of the paste deteriorate with increase of fly ash content in the mixture.
Data-driven surrogate modeling of aerodynamic forces on the superstructure of container vessels

ABSTRACT The operation of fluid engineering systems is usually governed by a wide range of different parameters. Investigations of the entire parameter spectrum using classical, first-principle based CFD methods are costly with regards to CPU and wall-clock time. Therefore, a near real-time assessment of complex flows using CFD to support the operation is deemed unfeasible. The paper is concerned with methods for data-based surrogate models to predict the forces exerted by the aerodynamic pressure field on the superstructure of a full-scale container ship for different container loading conditions and wind directions. The strategy aims to assist a fuel-efficient operation and is based on a two-step approach. During an initial step, a reduced representation of pressure fields obtained from 3D Navier–Stokes simulations is compiled. To this extent, a classical proper orthogonal decomposition is compared with convolutional neural network autoencoders. A subsequent parameterization employs a feedforward neural network to link the reduced model with the operational parameters, i.e. the angle of attack and container loading condition, and to enable a rapid on board assessment. Both methods provide a similar agreement for the pressure fields, as well as the resulting forces, with the CNN-based surrogate model being significantly more compact.
SOT-MRAM Digital PIM Architecture With Extended Parallelism in Matrix Multiplication

Emerging device-based digital processing-in-memory (PIM) architectures have been actively studied due to their energy and area efficiency derived from analog to digital converter (ADC)-less PIM hardware. However, digital PIM architectures generally need large extra memories to copy parameters, and they also suffer from low computation per memory-cycle efficiencies. In this paper, we present a novel spin-orbit torque magnetic random access memory (SOT-MRAM) based digital PIM architecture to alleviate the extra memory size burden and computation cycle issues. First, we propose the spintronics-assisted logic-in-memory (SLIM) cells to support efficient digital logic operations inside memories, where the voltage-controlled magnetic anisotropy (VCMA) is exploited to enhance the computation per memory-cycle efficiencies. In addition, crossed input source PIM (CRISP) architecture is proposed to extend the merits of SLIM cells by eliminating the extra memories for parameter copying while significantly improving the degree of parallel processing. An intra-memory pipelining scheme is also considered to further increase the throughput of CRISP. The proposed CRISP architecture has been implemented using 28 nm CMOS process, and it presents 1.10 TOPS/W and 0.95 TOPS/mm2, showing considerable improvements of energy efficiency and throughput per area, compared to the state-of-the-art digital PIM architecture. Finally, to evaluate the impact of computation errors induced from the SOT devices and circuits in CRISP architecture, classification accuracy simulations have been performed while applying computation errors.
Extruded Snacks from Rice, Green lentil, Chickpea and Tomato Powder Finished with Frying / Microwave Roasting

Extrudates were first prepared through extrusion-cooking and air-drying of different formulations obtained through a D-optimal Mixture Design containing blends of rice flour (RF), green lentil flour (GL), chickpeas flour (CP), and tomato powder (TP) in different proportions. These extrudates were subjected to deep oil frying (DOF) at 200⁰C or microwave roasting (MWR) at 75% power level (1000W oven) in order to develop desirable color and flavor characteristics. Physical properties including color (L*, a*, b*), expansion ratio (ER), breaking stress (BS) and antioxidant activity (AA) were evaluated, and the influence of product variables on output parameters was assessed. Increasing CP and GL in the formulations resulted in a decrease in the ER and an increase in the BS. However, the inclusion of CP and TP helped to produce snacks of golden yellow color and increased their overall acceptability. The addition of TP also improved the antioxidant activity of the resulting product. Both DOF and MWR resulted in a lower antioxidant activity; however, MWR led to more than 80% retention of the original antioxidants and higher sensory acceptability. ER and L* values had a strong positive correlation with the overall acceptability of products. The extrusion - air-drying - microwave roasting process produced healthy snacks with acceptable sensory quality, high protein (through added pulses), and enriched antioxidant (through added tomato powder) contents.
Impacts of harvested species declines on Indigenous Peoples’ food sovereignty, well-being and ways of life: a case study of Anishinaabe perspectives and moose

Global declines in wildlife are increasing the vulnerability of Indigenous communities to food insecurity. Meanwhile, many colonial policies continue to ignore social-ecological relationships that have traditionally maintained a balance between wildlife and Indigenous Peoples’ subsistence needs. We provide a case study on perspectives and insights from three Anishinaabe Nations in Ontario, Canada on the importance of a traditional food, moose (mooz [Nishnaabemowin]; Alces alces), and how changes in the moose population are affecting food security, well-being, and ways of life. In partnership with each Nation, we conducted interviews with community members and related observations on change in the moose population to estimates of moose abundance and non-Indigenous harvest collected by the Ontario provincial government over a 16-year time frame (2001–2016). Moose was described as important for subsistence needs as well as for maintaining Anishinabek culture, traditions, and identity within each community. A decline in the moose population was observed by most participants, which corresponded with provincial data on moose abundance. Additionally, the number of non-Indigenous hunters per moose harvested on traditional territories increased linearly over time, and community members expressed concern over how the province was managing moose. The effects of moose decline in the communities included reduced food security and health, increased financial costs due to both relying more on store-bought foods and having to travel further to harvest moose, as well as a decline in the practice of traditions and ceremonies surrounding moose harvest and passing this knowledge on to younger generations. Despite the potential impacts on Indigenous subsistence harvest, there is a lack of collaborative decisionmaking with Indigenous communities on moose population and harvest management in Ontario. Using community perspectives and insights, we discuss how autonomous moose monitoring can support and facilitate co-management and collaborative decision-making to reinstate Indigenous food sovereignty.
Basal Values of Biochemical and Hematological Parameters in Elite Athletes

The purpose of this study was to show how continuous exercise affects the basal values of biochemical and hematological parameters in elite athletes. A total of 14,010 samples (male = 8452 and female = 5558 (March 2011–March 2020)) from 3588 elite athletes (male = 2258 and female = 1330, mean age 24.9 ± 6.9 vs. 24.1 ± 5.5 years, respectively) from 32 sport modalities, were studied over 9 years to check the variation of basal biochemical and hematological parameter values. There were differences seen in the basal values of creatine kinase (CK), urea, creatinine, aspartate transaminase (AST), alanine aminotransferase (ALT), lactate dehydrogenase (LDH), potassium, total bilirubin, and eosinophil percentage compared to reference population data. However, other analytes showed narrow ranges of variation like glucose, total protein, albumin, sodium, hemoglobin, mean cell volume (MCV), and platelet count. Exercise produces changes in biochemical and hematological basal values of athletes compared to the general population, with the greatest variation in CK, but AST, ALT, LDH, potassium, and total bilirubin (TBil) show high values in serum, only with a wider distribution of values. The data here reflects the effect of exercise on biochemical and hematological parameter baseline ranges in elite athletes. As clinical laboratories use reference intervals to validate clinical reports, these “pseudo” reference intervals should be used when validating laboratory reports.
Racial and Ethnic Disparities in Adult Vaccination: A Review of the State of Evidence

Background Adult vaccination coverage remains low in the United States, particularly among racial and ethnic minority populations. Objective To conduct a comprehensive literature review of research studies assessing racial and ethnic disparities in adult vaccination. Search Methods We conducted a search of PubMed, Cochrane Library, ClinicalTrials.gov, and reference lists of relevant articles. Selection Criteria Research studies were eligible for inclusion if they met the following criteria: (1) study based in the United States, (2) evaluated receipt of routine immunizations in adult populations, (3) used within-study comparison of race/ethnic groups, and (4) eligible for at least one author-defined PICO (patient, intervention, comparison, and outcome) question. Data Collection and Analysis Preliminary abstract review was conducted by two authors. Following complete abstraction of articles using a standardized template, abstraction notes and determinations were reviewed by all authors; disagreements regarding article inclusion/exclusion were resolved by majority rule. The Social Ecological Model framework was used to complete a narrative review of observational studies to summarize factors associated with disparities; a systematic review was used to evaluate eligible intervention studies. Results Ninety-five studies were included in the final analysis and summarized qualitatively within two main topic areas: (1) factors associated with documented racial-ethnic disparities in adult vaccination and (2) interventions aimed to reduce disparities or to improve vaccination coverage among racial-ethnic minority groups. Of the 12 included intervention studies, only 3 studies provided direct evidence and were of Level II, fair quality; the remaining 9 studies met the criteria for indirect evidence (Level I or II, fair or poor quality). Conclusions A considerable amount of observational research evaluating factors associated with racial and ethnic disparities in adult vaccination is available. However, intervention studies aimed at reducing these disparities are limited, are of poor quality, and insufficiently address known reasons for low vaccination uptake among racial and ethnic minority adults.
An Overlapping Community Detection Approach Based on Deepwalk and Improved Label Propagation

Label propagation-based overlapping community detection algorithms have been widely used in complex networks due to their simplicity and efficiency. However, such algorithms need to randomly choose neighbor nodes and do not fully take the network’s topology into consideration, resulting in low stability and accuracy. Aiming at this problem, we propose an overlapping community detection approach based on DeepWalk and the improved label propagation. We first use the DeepWalk model to learn the network’s topology to obtain low-dimensional vector representations that reflect the spatial location of nodes and construct the weight matrix through vector dot product operation. Then, we design a label propagation algorithm with a preference selection strategy, which can obtain stable overlapping communities by exchanging information with fixed neighbors on the basis of preserving the nodes’ own labels. The experimental results on the real network and synthetic datasets show that the proposed approach has better accuracy and stability than the baseline methods.
Association of TLR4 Rs4986791 Polymorphism and TLR9 Haplotypes with Acute Myeloid Leukemia Susceptibility: A Case-Control Study of Adult Patients

Toll-like receptors (TLRs) have an important role in innate immunity, and single nucleotide polymorphisms (SNPs) of TLR genes influence the risk of developing hematological malignancies. We aimed to evaluate the effect of TLR2 (rs5743708), TLR4 (rs11536889, rs4986790, rs4986791), TLR9 (rs187084, rs352140, rs5743836) on AML risk, the relation between investigated SNPs and somatic mutations, clinical features, and the overall survival of adult AML patients. All mentioned SNPs were genotyped in 511 AML cases and 503 healthy controls. DNMT3A (R882), FLT3 (D835, ITD), and NPM1 mutations’ status were investigated in AML patients. TLR4 rs4986791 was associated with an increased risk of AML under the dominant model (OR = 1.61, 95% CI: 1.001–2.59). Variant genotypes of the TLR4 rs4986790 or rs4986791 were associated with the odds of developing AML in the codominant model (OR = 3.14; 95% CI: 1.12–8.84; p = 0.032). The TLR9 rs5743836 variant genotype was associated with the NPM1 mutation (p = 0.002). The investigated SNPs were not associated with the DNMT3A, FLT3 mutations and had no significant contribution to the hazard of death after adjusting for covariates. Our findings suggest that TLR4 rs4986791 is associated with AML susceptibility. The combined variant genotypes of TLR4 rs4986790 and rs4986791 increase AML risk, the TLR9 C-G-A haplotype may represent a promising approach to predict a person’s risk for developing AML.
Recent Trends in Graphene/Polymer Nanocomposites for Sensing Devices: Synthesis and Applications in Environmental and Human Health Monitoring

Graphene-based nanocomposites are largely explored for the development of sensing devices due to the excellent electrical and mechanical properties of graphene. These properties, in addition to its large specific surface area, make graphene attractive for a wide range of chemical functionalization and immobilization of (bio)molecules. Several techniques based on both top-down and bottom-up approaches are available for the fabrication of graphene fillers in pristine and functionalized forms. These fillers can be further modified to enhance their integration with polymeric matrices and substrates and to tailor the sensing efficiency of the overall nanocomposite material. In this review article, we summarize recent trends in the design and fabrication of graphene/polymer nanocomposites (GPNs) with sensing properties that can be successfully applied in environmental and human health monitoring. Functional GPNs with sensing ability towards gas molecules, humidity, and ultraviolet radiation can be generated using graphene nanosheets decorated with metallic or metal oxide nanoparticles. These nanocomposites were shown to be effective in the detection of ammonia, benzene/toluene gases, and water vapor in the environment. In addition, biological analytes with broad implications for human health, such as nucleic bases or viral genes, can also be detected using sensitive, graphene-based polymer nanocomposites. Here, the role of the biomolecules that are immobilized on the graphene nanomaterial as target for sensing is reviewed.
Knowledge about COVID-19, coping and resilience in Mexican women: comparison by stress levels

Background: The psychosocial effects derived from the COVID-19 pandemic have represented a challenge for the population worldwide. Stress is a frequent problem reported by women, impacting the strategies they use to deal with problems in daily life and their ability to recover from this critical phenomenon. Objective: The objective of this study was to evaluate the relationship between stress levels, knowledge about COVID -19, ways of coping, and resilience in women. Method: A non-experimental, cross-sectional, and correlational study was carried out in a group of 386 Mexican women through a format that was distributed on social networks. Results: The data suggest that the higher the level of knowledge about COVID-19, the greater the perceived stress. High stress is positively and statistically significantly related to coping style, denial (r = .245; q = .20) and cognitive-reflective analysis (r = .303; q= .21). Low levels of stress are negatively and statistically significantly associated with a weak effect size with factors like social competence (r= -.198; q= .11) and family support (r = -. 227; q = .16). Conclusion: Stress affects women considerably due to work overload and interpersonal factors. This study offers the possibility of knowing the emotional state of women in times of COVID-19.