Miracle-dz/UniFAR-FTUs huggingface dataset:
A Simplified Perturbed Hard-Sphere Model for the Activity Coefficients of Amino Acids and Peptides in Aqueous Solutions

A simple perturbed hard-sphere model has been developed to correlate the activity coefficients of amino acids and peptides in aqueous solutions. The perturbation terms are those due to dispersion forces and dipole−dipole interactions. These interactions are represented by a Lennard-Jones (6−12) and a Keesom expression, respectively. Dipole moments of amino acids and peptides, calculated by a quantum mechanical approach using the Hyperchem molecular modeling software, are reported. The model can accurately correlate the activity coefficients of amino acids and peptides in aqueous solutions. The model was used to correlate and predict the solubilities of amino acids in aqueous solutions at different temperatures. New values of Δg and Δh of solution of amino acids are reported.
Assessment of regional aerosol radiative effects under the SWAAMI campaign – Part 2: Clear-sky direct shortwave radiative forcing using multi-year assimilated data over the Indian subcontinent

Abstract. Clear-sky, direct shortwave aerosol radiative forcing (ARF) has been estimated over the Indian region, for the first time employing multi-year (2009–2013) gridded, assimilated aerosol products, as an important part of the South West Asian Aerosol Monsoon Interactions (SWAAMI) which is a joint Indo-UK research field campaign focused at understanding the variabilities in atmospheric aerosols and their interactions with the Indian summer monsoon. The aerosol datasets have been constructed following statistical assimilation of concurrent data from a dense network of ground-based observatories and multi-satellite products, as described in Part 1 of this two-part paper. The ARF, thus estimated, is assessed for its superiority or otherwise over other ARF estimates based on satellite-retrieved aerosol products, over the Indian region, by comparing the radiative fluxes (upward) at the top of the atmosphere (TOA) estimated using assimilated and satellite products with spatiotemporally matched radiative flux values provided by CERES (Clouds and Earth's Radiant Energy System) single-scan footprint (SSF) product. This clearly demonstrated improved accuracy of the forcing estimates using the assimilated vis-à-vis satellite-based aerosol datasets at regional, subregional and seasonal scales. The regional distribution of diurnally averaged ARF estimates has revealed (a) significant differences from similar estimates made using currently available satellite data, not only in terms of magnitude but also the sign of TOA forcing; (b) the largest magnitudes of surface cooling and atmospheric warming over the Indo-Gangetic Plain (IGP) and arid regions from north-western India; and (c) negative TOA forcing over most parts of the Indian region, except for three subregions – the IGP, north-western India and eastern parts of peninsular India where the TOA forcing changes to positive during pre-monsoon season. Aerosol-induced atmospheric warming rates, estimated using the assimilated data, demonstrate substantial spatial heterogeneities (∼0.2 to 2.0 K d−1) over the study domain with the IGP demonstrating relatively stronger atmospheric heating rates (∼0.6 to 2.0 K d−1). There exists a strong seasonality as well, with atmospheric warming being highest during pre-monsoon and lowest during winter seasons. It is to be noted that the present ARF estimates demonstrate substantially smaller uncertainties than their satellite counterparts, which is a natural consequence of reduced uncertainties in assimilated vis-à-vis satellite aerosol properties. The results demonstrate the potential application of the assimilated datasets and ARF estimates for improving accuracies of climate impact assessments at regional and subregional scales.
Indication of the coronavirus model particles using a nanowire biosensor

The presented results indicate virus-like particles of the coronavirus (CVP) using a nanowire (NW) biosensor based on silicon-on-insulator technology. In the experiment, we used suspensions of CVP and of specific antibodies to the virus. Measurements of the current value of the field-effect transistor before and after the introduction of the CVP on the surface of the nanowire were performed. Results showed antibody + CVP complexes on the phase section with the surface of the nanowire modulate the current of the field-effect transistor; CVP has an electrically positive charge on the phase section “nanowire surface-viral suspension»; antibody + CVP complexes have an electrically negative charge on the phase section “nanowire surface-viral suspension”; the sensitivity of the biosensor is made up of 10−18 M; the time display was 200–300 s.
Birth trauma from the perspective of perinatal counsellors: A mini focus group study

One in five women in the UK develop mental health problems during pregnancy or in the first year after childbirth. ‘Birth trauma’ is a common birth-related mental health issue which stems from perceiving childbirth as a traumatic experience; the term ‘birth trauma’ also encompasses living with and experiencing the accompanying symptoms of trauma after childbirth. A mini focus group study was conducted with two experienced perinatal counsellors to discuss their experiences working with parents struggling with birth trauma. Analysis of the focus group revealed five key themes: the complexity of birth trauma; the power of communication; changes in culture; falling through the gaps and coping with trauma. The themes identified reflect previous academic research on parent and clinician experiences of birth trauma as well as national reports aimed at improving maternity care for parents.
Cross-Media Retrieval Based on Canonical Correlation Analysisand Decision Tree

The retrieval of approximate data from massive multimedia data is the key of computer science research. With the explosive growth of data scale, data retrieval needs to face the overlapping massive multimodal data called “dimension disaster”, and the traditional retrieval methods appeared to be inefficient. The cross-media retrieval with canonical correlation analysis (CCA) is a kind of way to map different media features to the largest correlation isomorphism subspaceand then compare the similarity between cross-media data in this subspace. However CCA is a linear model and it is difficult to map the lower data to the higher semantic. This paper proposed a cross-media retrieval method based on CCA and Decision Tree to solve the problem. CCA was uesd to depict the correlation between image and text feature, Decision Tree was uesd toapproach to feedback and repeatedly adjust the correlation. Experiments on the Wikipedia text-image datasetsverified that the Tree-CM model can mine the complex correlation between cross-media data and has better performance than other state-of-the-art models.
Tangki NAHRIM 2.0: an R-based water balance model for rainwater harvesting tank sizing application

Tangki NAHRIM, a desktop application developed in 2008, is widely used for the calculation of optimal tank size for rainwater harvesting in Malaysia. Here we present an overview of the updated version, Tangki NAHRIM 2.0 (TN2) which was developed in the R computing environment. In TN2, a rainwater harvesting system is simulated using a daily water balance model with rainfall input from a built-in database by adopting the yield-after-spillage (YAS) convention. Proposed tank sizes are evaluated based on water saving and storage efficiencies. These results are then visualised in charts showing the relationships between tank sizes and both efficiency measures to help users select the optimal tank size based on their criteria of choice. A simulation was conducted based on a typical Malaysian household for domestic non-potable use as a case study. A web-based GUI for TN2 was developed in R Shiny framework for the public. The GUI has the advantage of being accessible online from any device, and will be able to facilitate the adoption of rainwater harvesting systems by the public at large.
Efficient Mercury Removal at Ultralow Metal Concentrations by Cysteine Functionalized Carbon-Coated Magnetite

This work reports the preparation and utility of cysteine-functionalized carbon-coated Fe3O4 materials (Cys-C@Fe3O4) as efficient sorbents for remediation of Hg(II)-contaminated water. Efficient removal (90%) of Hg(II) from 1000 ppb aqueous solutions is possible, at very low Cys-C@Fe3O4 sorbent loadings (0.01 g sorbent per liter of Hg(II) solution). At low metal concentrations (5–100 ppb Hg(II)), where adsorption is typically slow, Hg(II) removal efficiencies of 94–99.4% were achievable, resulting in final Hg(II) levels of <1.0 ppb. From adsorption isotherms, the Hg(II) adsorption capacity for Cys-C@Fe3O4 is 94.33 mg g−1, around three times that of carbon-coated Fe3O4 material. The highest partition coefficient (PC) of 2312.5 mgg−1µM−1 was achieved at the initial Hg (II) concentration of 100 ppb, while significantly high PC values of 300 mgg−1µM−1 and above were also obtained in the ultralow concentration range (≤20 ppb). Cys-C@Fe3O4 exhibits excellent selectivity for Hg(II) when tested in the presence of Pb(II), Ni(II), and Cu(II) ions, is easily separable from aqueous media by application of an external magnet, and can be regenerated for three subsequent uses without compromising Hg(II) uptake. Derived from commercially available raw materials, it is highly possible to achieve large-scale production of the functional sorbent for practical applications.
Performance Analysis of Active Queue Management Algorithm Based on Reinforcement Learning

In the information society, data explosion has led to more congestion in the core network, dampening the network performance. Random early detection (RED) is currently the standard algorithm for active queue management (AQM) recommended by the Internet Engineering Task Force (IETF). However, RED is particularly sensitive to both service load and algorithm parameters. The algorithm cannot fully utilize the bandwidth at a low service load, and might suffer a long delay at a high service load. This paper designs the reinforcement learning AQM (RLAQM), a simple and practical variant of RED, which controls the average queue length to the predictable value under various network loads, such that the queue size is no longer sensitive to the level of congestion. Q-learning was adopted to adjust the maximum discarding probability, and derive the optimal control strategy. Simulation results indicate that RLAQM can effectively overcome the deficiency of RED and achieve better congestion control; RLAQM improves the network stability and performance in complex environment; it is very easy to migrate from RED to RLAQM on Internet routers: the only operation is to adjust the discarding probability.
The Causal Relationship Between Temperature Change And Food Indices In The World

The effects of temperature change on different sectors have been one of the most essential problems in the last decades. Agricultural sector is definitely the most fragile sector of all, not only production of food causes temperature change but also temperature change led to the instability of production and prices. The objective of this study was to analyse the relationship between temperature change and production or price indices in the world for the period of 1990-2016. The time series of temperature change, Food Price Index and Gross Production Index for foods were obtained from the database of the Food and Agriculture Organization of the United Nations. Johansen cointegration and Granger causality analysis were used to evaluate relations between the indicators in the short and long runs. The results of the study indicated that temperature change, Food Price Index and Gross Production Index for foods were cointegrated and so they move together in the long run. On the other hand, Granger causality analysis highlighted that there is unidirectional causality runs from temperature change to both Food Price Index and Gross Production Index for foods and at the same time from Gross Production Index for foods to Food Price Index. This research concluded that temperature has an essential effect both on agricultural production and prices, whereas food prices are sensitive to production. Therefore, the environmentally friendly technologies should be developed and applied in agricultural sector. However, the food prices could be regulated
Inverse Space Filling Curve Partitioning Applied to Wide Area Graphs

The most recent developments in graph partitioning research often consider scale-free graphs. Instead we focus on partitioning geometric graphs using a less usual strategy: Inverse Spacefilling Partitioning (ISP). ISP relies on a space filling curve to partition a graph and was previously applied to graphs essentially generated from Meshes. We extend ISP to apply it to a new context where the targets are now Wide Area Graphs. We provide an extended comparison with two state-of-the-art graph partitioning streaming strategies, namely LDG and FENNEL. We also propose customized metrics to better understand and identify the use cases for which the ISP partitioning solution is best suited. Experimentations show that in favourable contexts, edge-cuts can be drastically reduced, going from more 34% using FENNEL to less than 1% using ISP.
Morphology-photovoltaic property correlation in perovskite solar cells: One-step versus two-step deposition of CH3NH3PbI3

Perovskite CH3NH3PbI3 light absorber is deposited on the mesoporous TiO2 layer via one-step and two-step coating methods and their photovoltaic performances are compared. One-step coating using a solution containing CH3NH3I and PbI2 shows average power conversion efficiency (PCE) of 7.5%, while higher average PCE of 13.9% is obtained from two-step coating method, mainly due to higher voltage and fill factor. The coverage, pore-filling, and morphology of the deposited perovskite are found to be critical in photovoltaic performance of the mesoporous TiO2 based perovskite solar cells.
Top management team international diversity and the performance of international R&D

We investigate how international diversity in Top Management Teams (TMTs) contributes to the effectiveness of geographically dispersed R&D strategies in enhancing innovation performance. Both international work experience and nationality diversity may enhance the effectiveness of geographically dispersed R&D when there is alignment between the countries of work experience and nationality of TMT members, on the one hand, and firms’ R&D locations on the other. This influence is stronger for international work experience diversity than for nationality diversity, as the former provides more task-related knowledge to coordinate R&D activities and is less associated with the risk of social categorization. We find partial support for these notions in a panel analysis of the innovation performance of 165 leading MNCs based in Europe, Japan and the United States.
Stochastic neural network based data analysis‐related talent recruitment optimization via CDN server

The competition for talent is always intense, especially in the era of big data, the data analysis‐related talent recruitment plays an important role in promoting the development of enterprises. Regarding resume screening, it is considerably significant during the process of talent recruitment. Consider that Neural Network (NN) has the strong stability on the prediction result and is given a lot of attention, this paper uses Stochastic NN (SNN) to optimize the data analysis‐related talent recruitment. Meanwhile, SNN is used to train resume‐related dataset and make resume screening. In addition, in order to accelerate the training process and decrease the training complexity, this paper uses Locally Linear Embedding (LLE) to do dimension reduction in terms of the extracted data features. Furthermore, in order to guarantee the on‐line resume screening, this paper does resume screening under Content Delivery Network (CDN) scenario, where CDN has two functions, that is, data storage and hot resumes recommendation. The experiments are made based on the collected 7000 resumes, and the result show that this paper has good optimization effect on data analysis‐related talent recruitment.
Zinc-Substituted Polyoxometalate for Oxidative Desulfurization of Dibenzothiophene

Abstract An oxidative desulfurization process for model compound has been studied using Na12[WZn3(H2O)2(ZnW9O34)2] · 46H2O as catalyst and 30 wt% aqueous hydrogen peroxide as the oxidizing agent. The effects of the reaction time, the reaction temperature, the amount of the oxidizing agent and the catalyst on the removal of dibenzothiophene (DBT) were investigated. The oxidated resultant was removed by extraction with polar solvent to reduce the sulfur level in the model compound. The maximum removal of DBT was up to 70%.
Oxidation of Selected Trace Organic Compounds through the Combination of Inline Electro-Chlorination with UV Radiation (UV/ECl2) as Alternative AOP for Decentralized Drinking Water Treatment

A large variety of Advanced Oxidation Processes (AOPs) to degrade trace organic compounds during water treatment have been studied on a lab scale in the past. This paper presents the combination of inline electrolytic chlorine generation (ECl2) with low pressure UV reactors (UV/ECl2) in order to allow the operation of a chlorine-based AOP without the need for any chlorine dosing. Lab studies showed that from a Free Available Chlorine (FAC) concentration range between 1 and 18 mg/L produced by ECl2 up to 84% can be photolyzed to form, among others, hydroxyl radicals (OH) with an UV energy input of 0.48 kWh/m3. This ratio could be increased to 97% by doubling the UV energy input to 0.96 kWh/m3 and was constant throughout the tested FAC range. Also the achieved radical yield of 64% did not change along the given FAC concentration range and no dependence between pH 6 and pH 8 could be found, largely simplifying the operation of a pilot scale system in drinking water treatment. Whereas with ECl2 alone only 5% of benzotriazoles could be degraded, the combination with UV improved the degradation to 89%. Similar results were achieved for 4-methylbenzotriazole, 5-methylbenzotriazole and iomeprol. Oxipurinol and gabapentin were readily degraded by ECl2 alone. The trihalomethanes values were maintained below the Germany drinking water standard of 50 µg/L, provided residual chlorine concentrations are kept within the permissible limits. The here presented treatment approach is promising for decentralized treatment application but requires further optimization in order to reduce its energy requirements.
An Assessment of the Spatial Variability of Tropical Swamp Forest along a 300 km Long Transect in the Usumacinta River Basin, Mexico

The provision of valuable ecosystem services by tropical swamp forests (mainly carbon sequestration and storage in biomass and soil) explains their ecological importance. Current efforts toward the conservation of these ecosystems, however, face strong limitations as their spatial variation is largely unknown, particularly in regions where they occur over large areas. Here, we analyze the α-diversity (i.e., effective number of species or true diversity) and community structure variability of three tropical swamp forest communities distributed along an approximately 300 km long portion of the Usumacinta River Basin, southern Mexico. We sampled eighty-three 625-m2 plots to characterize the diversity and structural attributes of the woody plant communities. We recorded 2302 individuals belonging to 60 species and 25 families. Both α-diversity and structural attributes differed significantly among the three communities. The most inland community stood out for having the highest α-diversity for three true diversity values. Interestingly, the mangrove Rhizophora mangle L. was one of the dominant species, both in the swamp forest located closest to the coast and in the community farthest away from the sea. Basal area and density of individuals also had their maxima in the most inland swamp forest. The diversity and structural differences observed among the examined swamp forests seem to be related to contrasting environmental conditions, such as water salinity, distance to the coastline, and the hydrological dynamics of the Usumacinta River. We emphasize the urgency to conserve R. mangle populations in the swamp forest located farthest away from the coast due to its unusual habitat association, which appears to be a relictual condition.
NO reduction by activated carbons. II: Catalytic effect of potassium

The results of an investigation are reported concerning the NO reduction activity of different carbons loaded by ion exchange with varying amounts of a potassium catalyst. The samples were characterized by physical adsorption of CO 2 (at 0 o C) and N 2 (at -196 o C) and by chemisorption of CO 2 at 250 o C. The reactivity of the pure carbons was determined in both NO and CO 2 . The catalytic effect of potassium in NO reduction was evaluated in a fixed-bed flow reactor at atmospheric pressure using two types of experiments: (i) temperature-programmed reaction in a NO/He mixture; and (ii) isothermal reaction at 300-600 o C. The reaction products were monitored in both cases, thus allowing detailed oxygen and nitrogen balances to be determined. Potassium was found to be an excellent catalyst for the NO reduction by carbon. At temperatures below 600 o C, the products of the reaction were primarily N 2 and CO 2 . The catalytic activity, and thus the concentration of catalytically active sites, is dependent on both catalyst dispersion and carbon reactivity
Visual Impairment Prevalence, Causes, and Role of Healthcare Access: A Systematic Review and Meta-Analysis in Iran

Purpose Healthcare access is one of the determinants of visual impairment (VI), as a public health problem. The objective of this study was to estimate VI prevalence, related causes, and its correlation with access to physicians in Iran. Methods : This systematic review and meta-analysis include observational studies published in Iran. PubMed, Web of Science, Scopus, Google Scholar, and local databases were systematically searched by using the MeSH headings. Data on the provincial distribution of physicians, as an index of access to healthcare, was retrieved. A random-effect meta-analysis was performed to assess. Results Eight articles were included. The pooled prevalence of blindness, low vision, and VI was 0.80% (95% CI: 0.61–0.99%), 2.92% (95% CI: 2.40–3.44%), and 5.57% (95% CI: 4.71–6.43%). Refractive errors were the most common causes of VI based on PVA with the pooled prevalence of 54.6% (95% CI: 43.4–65.8%). Based on BCVA, we found that the pooled prevalence of cataracts was 37.4% (95% CI: 29.5–45.3%) as the most common cause of VI. The results of metaregression showed that the greater number of general practitioners (GPs) (P value = 0.01) and pharmacists (P value = 0.024) per population were associated with a lower prevalence of blindness. Conclusion Some of the main causes of visual impairment in Iran are preventable. Access to healthcare services may lead to early diagnosis of preventable causes of VI. Further well-designed studies and national surveys should be conducted to provide accurate data from different regions of Iran.