Miracle-dz/UniFAR-FTUs huggingface dataset:
Standardisation: What is it and How is it Done? Part 1

The term "standardise" appeared in 1881 in Nature where it was advised that, "This other mode of measurement should be standardised (sic) . by comparison with Mr. Harcourt's air-gas flame, which should alone be taken as the official standard. "1 The term was first applied to instrument standardisation in 1889 in the Daily News which stated, "The supply of electrical energy under statutory powers could not be effectively carried out unless there was some method of standardising (sic) the meters and other instruments. "1 These quotations from the late 19th century show that the problem of standardisation is as old as analytical chemistry, and has had varying definitions since its inception. In the first cas·e, a standard method was proposed against which all newer methods would be tested, while in the second instruments were being required to give the same response. It should be no surprise, then, that the problem of standardisation and its ambiguous definition have grown along with analysis and includes a set of related problems. This paper describes the scope of standardisation and gives a description of the methods associated with standardisation. Part 2 will cover the advantages and disadvantages of each approach . According to Webster's Dictionary standardisation means: "1 . to compare with a standard 2. to bring into conformity with a standard. "2 The fundamental problem of standardisation is making an instrument response conform to a "standard" instrument response. The current formulation of the standardisation problem can be seen by examining the aspects of a generic instrument response, in the hope of defining the important aspects of a "standard" instrument respo111se . The first aspect of the standard instrument response is the instrument. The methods of Shenk et al. and those of Wang et al.3-f3 have mathematically modified the instrument response function of a second instrument to match the instrument response function of a primary instrument. They succeeded to varying degrees by correcting spectra of the same samples, taken with different instruments. Shenk has shown that instrument differences can be corrected between similar instruments, such as correcting a near infrared reflectance
Direct determination of nitrate in small volumes of natural surface waters using a simple spectrophotometric method

Abstract A simple, sensitive and selective spectrophotometric method is proposed for rapid and direct determination of nitrate in small volumes of natural surface waters (maximum 2.0 ml), and optimal experimental conditions, along with other analytical parameters, have been evaluated. The method is based on the reaction between nitrate and chromotropic acid, in concentrated sulfuric acid media (95%), when a yellow colored product is obtained. The visible spectra of this reaction product, recorded against a blank solution, show a maximum at 412 nm, and the absorbance remains stable for at least 24 h. The method allows the nitrate determination over the range 0.50–11.00 mg l-1, with a molar absorptivity of 3.837×104 l mol-1 cm-1 and a detection limit of 0.12 ppm. The interferences caused by several common ions (K+, NH4+, Na+, Ca2+, Mg2+, Al3+, Cl-, NO2-, HCO3-, CO32-, H2PO4-, HPO42-) which are present in most natural surface waters were determined. The validation of the spectrophotometric method was done by comparing the nitrate content obtained by the proposed method with those obtained by using the standard method with sulphosalicylic acid, for all studied types of waters (drinking water, tap water, river water and sea water). The results show that the proposed method can be successfully used for direct determination of nitrate in small volumes of natural surface waters (maximum 2.0 ml). The main advantage of this method is that the colored reaction product appears immediately after mixing the reagents; other intermediary steps are not necessary.
Philosophy in Science: Can philosophers of science permeate through science and produce scientific knowledge?

Most philosophers of science do philosophy ‘on’ science. By contrast, others do philosophy ‘in’ science (‘PinS’), i.e., they use philosophical tools to address scientific problems and to provide scientifically useful proposals. Here, we consider the evidence in favour of a trend of this nature. We proceed in two stages. First, we identify relevant authors and articles empirically with bibliometric tools, given that PinS would be likely to infiltrate science and thus to be published in scientific journals (‘intervention’), cited in scientific journals (‘visibility’) and sometimes recognized as a scientific result by scientists (‘contribution’). We show that many central figures in philosophy of science have been involved in PinS, and that some philosophers have even ‘specialized’ in this practice. Second, we propose a conceptual definition of PinS as a process involving three conditions (raising a scientific problem, using philosophical tools to address it, and making a scientific proposal), and we ask whether the articles identified at the first stage fulfil all these conditions. We show that PinS is a distinctive, quantitatively substantial trend within philosophy of science, demonstrating the existence of a methodological continuity from science to philosophy of science.
Construction and Characterization of Structure Models of Crystalline Porous Polymers

Metal–organic frameworks (MOFs) and covalent organic frameworks (COFs) are examples of advanced porous polymeric materials that have emerged in recent years. Their crystalline structure and modular synthesis offer unmatched versatility in their design. By exchanging chemical building blocks, one can both explore the unlimited space of possible structural chemistry within an isoreticular (same crystal topology) series and achieve a wide range of alternative topologies. This reticular paradigm potentially enables the design of structures with any desired porosity and internal surface chemistry. Reliable structure models are typically required in order to predict material properties using a broad spectrum of molecular modeling techniques. In this work, we introduce an algorithm for the assembly of crystalline porous polymer structure models which permits precise control over the underlying topologies of the generated models. This tool has been applied to high-throughput combinatorial structure enumeration an.
Performance Assessment for Short-Term Water Demand Forecasting Models on Distinctive Water Uses in Korea

It is crucial to forecast the water demand accurately for supplying water efficiently and stably in a water supply system. In particular, accurately forecasting short-term water demand helps in saving energy and reducing operating costs. With the introduction of the Smart Water Grid (SWG) in a water supply system, the amount of water consumption is obtained in real-time through a smart meter, which can be used for forecasting the short-term water demand. The models widely used for water demand forecasting include Autoregressive Integrated Moving Average, Radial Basis Function-Artificial Neural Network, Quantitative Multi-Model Predictor Plus, and Long Short-Term Memory. However, there is a lack of research on assessing the performance of models and forecasting the short-term water demand in the SWG demonstration plant. Therefore, in this study, the short-term water demand was forecasted for each model using the data collected from a smart meter, and the performance of each model was assessed. The Smart Water Grid Research Group installed a smart meter in block 112 located in YeongJong Island, Incheon, and the actual data used for operating the SWG demonstration plant were adopted. The performance of the model was assessed by using the Residual, Root Mean Square Error, Normalized Root Mean Square Error, Nash–Sutcliffe Efficiency, and Pearson Correlation Coefficient as indices. As a result of water demand forecasting, it is difficult to forecast water demand only by time and water consumption. Therefore, as the short-term water demand forecasting models using only time and the amount of water consumption have limitations in reflecting the characteristics of consumers, a water supply system can be managed more precisely if other factors (weather, customer behavior, etc.) influencing the water demand are applied.
Deep Learning-Based Channel Prediction for LEO Satellite Massive MIMO Communication System

Low Earth orbit (LEO) satellite is one of the most promising infrastructures for realizing next-generation global wireless networks with enhanced data rates. Applying massive multiple-input multiple-output (mMIMO) to LEO satellite communication systems is a novel idea to enhance communication capacity and realize the global high-speed interconnection. However, obtaining effective instantaneous channel state information (iCSI) is challenging due to the time-varying propagation environment and long transmission delay. In this letter, a deep learning (DL)-based CSI prediction scheme is proposed to address channel aging problem by exploiting the correlation of changing channels. Specifically, we design a satellite channel predictor (SCP) that is composed by long short term with memory (LSTM) units. The predictor is first trained by offline learning and then feeds back the corresponding output results online based on the input data to realize channel feature extraction and future CSI prediction in LEO satellite scenarios. Numerical results demonstrate that the proposed DL-based predictor can mitigate the channel aging problem in LEO satellite mMIMO system effectively.
Holocene environmental history of a freshwater wetland in southern Louisiana: a sedimentary record of delta development, coastal evolution and human activity

The world's most extensive and active deltas, Louisiana's wetlands, are deteriorating rapidly due to multiple stressors. Their ecological and anthropogenic histories on a multimillennial timescale have not been thoroughly documented. This study investigates hydrological and anthropogenic impacts on southern Louisiana wetlands to guide future efforts toward environmental restoration. A 3.6 m sediment core (JOYWMA) extracted from a freshwater wetland adjacent to Lake Pontchartrain yielded a 5000‐year record. Multiproxy data indicate four distinct stages, with the earliest period representing an oyster reef (~4.5 cal yr bp) marked by elevated Ca and Sr concentrations. Evolution to a freshwater marsh occurred 4.5–4.0 cal yr bp during the St. Bernard delta progradation, marked by increased Zr and Br concentrations. The site transitioned to a lake due to the isolation from the St. Bernard delta and local subsidence (4.0–2.0 cal yr bp), marked by increased Ti, Fe, Mn and K concentrations. The site altered to a cypress swamp after 2.0 cal yr bp due to increased sediment supply during the St. Bernard subdelta progradation. Both natural (delta progradation and subsidence) and anthropogenic (fire, deforestation) stressors have impacted the site over the last 4500 years. Delta‐switching of the Mississippi River caused the significant geomorphological and ecological changes.
Learning and teaching benchmarking in Australian universities: the current state of play

ABSTRACT Benchmarking is a formalised evaluation process by which a university can measure the standard of their policies, processes, programmes or strategies through comparison with other universities. Currently, there is a paucity of research that focuses on the documentation associated with external benchmarking undertaken by Australian universities. Given that Australia’s higher education regulatory body requires universities to reflect the purposes of external benchmarking within policy frameworks and for external referencing to be overseen by peak academic governance bodies such limited research is of significance. This paper contributes to the literature by investigating whether documented structures, policies and guidelines are in place to inform learning and teaching external referencing processes. Using a qualitative documentary thematic analysis, policies, procedures and guidelines found on university governance websites were investigated and analysed. The findings indicate that many Australian universities are at risk of not meeting mandatory regulatory requirements.
Long-Term Arsenic Sequestration in Biogenic Pyrite from Contaminated Groundwater: Insights from Field and Laboratory Studies

Pumping groundwater from arsenic (As)-contaminated aquifers exposes millions of people, especially those in developing countries, to high doses of the toxic contaminant. Previous studies have investigated cost-effective techniques to remove groundwater arsenic by stimulating sulfate-reducing bacteria (SRB) to form biogenic arsenian pyrite. This study intends to improve upon these past methods to demonstrate the effectiveness of SRB arsenic remediation at an industrial site in Florida. This study developed a ferrous sulfate and molasses mixture to sequester groundwater arsenic in arsenian pyrite over nine months. The optimal dosage of the remediating mixture consisted of 5 kg of ferrous sulfate, ~27 kg (60 lbs) of molasses, and ~1 kg (2 lbs) of fertilizer per 3785.4 L (1000 gallons) of water. The remediating mixture was injected into 11 wells hydrologically upgradient of the arsenic plume in an attempt to obtain full-scale remediation. Groundwater samples and precipitated biominerals were collected from June 2018 to March 2019. X-ray diffraction (XRD), X-ray fluorescence (XRF), electron microprobe (EMP), and scanning electron microscope (SEM) analyses determined that As has been sequestered mainly in the form of arsenian pyrite, which rapidly precipitated as euhedral crystals and spherical aggregates (framboids) 1–30 μm in diameter within two weeks of the injection. The analyses confirmed that the remediating mixture and injection scheme reduced As concentrations to near or below the site’s clean-up standard of 0.05 mg/L over the nine months. Moreover, the arsenian pyrite contained 0.03–0.89 weight percentage (wt%) of sequestered arsenic, with >80% of groundwater arsenic removed by SRB biomineralization. Considering these promising findings, the study is close to optimizing an affordable procedure for sequestrating dissolved As in industry settings.
Prediction of the Hypertension Risk of the Elderly in Built Environments Based on the LSTM Deep Learning and Bayesian Fitting Method

Hypertension has become the greatest risk factor for death in elderly populations. As factors influencing cardiovascular disease, indoor environmental parameters pose potential risks for older adults. In this study, elderly residents in Dalian (Liaoning Province, China) urban dwellings were selected as the research subjects, and the environmental parameters of the dwellings’ main activity rooms and the blood pressure parameters of the older adults were measured. Based on the Long Short-Term Memory (LSTM) deep learning algorithm and Bayesian fitting method, a hypertension disease model was established using the long-term environmental parameters to predict the hypertension risk of older adults in their building’s environment. The results showed that temperature, humidity, and some air quality parameters had an impact on blood pressure under single environmental factor, and the comprehensive environmental risks of high systolic blood pressure, high diastolic blood pressure, and high blood pressure were 16.44%, 0%, and 16.44% for the male elderly and 14.11%, 7.14%, and 17.55% for the female elderly, respectively. By comparing the results for the blood pressure measurement and prediction, it can be observed that the risk error of hypertension obtained by the algorithm maintains the variables’ relationship, and the result of the algorithm is reliable in this period. This technology can provide a basis for measuring environmental parameters and will be conducive to the development of an ecological smart building environment.
Variations in Soil Enzyme Activities and Microbial Communities along an Altitudinal Gradient on the Eastern Qinghai–Tibetan Plateau

The Qinghai–Tibetan Plateau is the highest plateau in the world and is sensitive to climate change. The dynamics of soil enzyme activities and microbial communities are good indicators of alpine biochemical processes during warming. We collected topsoil (0–10 cm) and subsoil (10–20 cm) samples at altitudes of 3200–4000 m; determined the activities of β-1,4-glucosidase (BG), cellobiohydrolase (CBH), β-1,4-N-acetyl-glucosaminidase (NAG) and acid phosphomonoesterase (PME); and performed Illumina 16S rRNA high-throughput sequencing. We found that the soil carbon (total organic carbon and dissolved organic carbon) and nitrogen (total nitrogen and dissolved organic nitrogen) fluctuated with altitude in both the topsoil and subsoil, whereas the dissolved phosphorus continuously decreased with the increasing altitude. BG and CBH decreased from 3200 to 3600 m and increased from 3800 to 4000 m, with the lowest levels occurring at 3600 m (topsoil) and 3800 m (subsoil). NAG and PME showed similar fluctuations with altitude, with the highest levels occurring at 3400 m and 4000 m in both the topsoil and subsoil. Generally, the altitudes from 3600 to 3800 m were an ecological transition belt where most of the nutrients and enzyme activities reached their lowest levels. All of the alpine soils shared similar dominant phyla, including Proteobacteria (32.7%), Acidobacteria (30.2%), Actinobacteria (7.7%), Bacteroidetes (4.4%), Planctomycetes (2.9%), Firmicutes (2.3%), Gemmatimonadetes (2.0%), Chloroflexi, (1.2%) and Nitrospirae (1.2%); Gemmatimonadetes and Verrucomicrobia were significantly affected by soil depth and Planctomycetes, Firmicutes, Gemmatimonadetes, Nitrospirae, Latescibacteria and Armatimonadetes were significantly affected by altitude. In addition, nutrient availability, enzyme activity and microbial diversity were higher in the topsoil than in the subsoil, and they had more significant correlations in the subsoil than in the topsoil. Our results provide useful insights into the close linkages between soil nutrient cycling and microbial activities on the eastern Qinghai–Tibetan Plateau, and are of great significance for further assessing the long-term impact of environmental changes in the alpine ecosystems.
Effect of Kangaroo care on Vulnerable Infant Syndrome in mother

ABSTRACT This study aims to examine the effect of kangaroo care on Vulnerable Infant Syndrome (VIS) in the mother. The sample group consisted of 58 preterm infants, 27 of whom were control and 31 were experimental groups. Data were collected using the question form, the Vulnerable Baby Scale (VBS), the Edinburgh Post PartumDepression Scale (EPDS), the Maternal Attachment Scale (MAS). The mean scores of VBS were found in the kangaroo group (17.22 ± 0.96) and in the control group (43.66 ± 0.89). It was found that there was a significant difference between the two groups in terms of VBS scores (p < 0.01). In addition, the mothers in the experimental group compared to the mothers in the control group; the mean EPDS score was low and the MAS mean score was high (p < 0.01). It was determined kangaroo care reduces maternal vulnerability, postpartum depression and increases maternal attachment.
Social Media and Romantic Relationship: Excessive Social Media Use Leads to Relationship Conflicts, Negative Outcomes, and Addiction via Mediated Pathways

Social media provides a useful platform for people to share information, develop networks, and connect with each other online. While social media allows one to foster relationships with ease, it may pose challenges for individuals in a romantic relationship. Mounting evidence suggests that social media use may have an adverse impact on relationship dynamics, largely due to reduced time and attention for relationship partners. However, it remains unclear (1) how the increased use of social media may lead to negative consequences of relationship quality; (2) how the increased use of social media and negative relationship consequences together may trigger social media addiction; and (3) whether there are psychological factors that may contribute to the mitigation of the negative consequences. Here, we explored these issues by selecting Instagram (IG) as the target platform because the unique feature of tracking objective time of usage within the IG app allowed us to more accurately determine the length of IG usage. Using a structural equation modeling approach, we found that increased IG usage reduced relationship satisfaction, which led to an increase in both conflicts and negative outcomes. The sequential effects of reduced relationship satisfaction and increased conflicts then triggered addictive use of IG. In contrast, tendency to make sacrifice for the relationship partner in everyday life produced a positive effect on relationship satisfaction, which in turn reduced the likelihood of conflicts, negative outcomes, and addiction. Taken together, we have delineated pathways through which excessive social media use may detrimentally affect both relationship and personal well-being and identified sacrifice as a possible psychological factor to mitigate the detrimental effects. We believe that these findings add to our understanding of the processes by which social media influences romantic relationship and highlight the interactive effects of social media and relationship on causing unexpected, adverse consequences.
Analysis of In Situ Optical Signals during Laser Metal Deposition of Aluminum Alloys

During laser metal deposition (LMD) of thin-walled aluminum alloy structures, the deposition height and width is hard to keep stable because of the special properties of aluminum alloys, such as high reflectivity to laser beams, low viscosity, and high thermal conductivity. Monitoring the LMD process allows for a better comprehension and control of this process. To investigate the characteristics of the aluminum alloy LMD process, three real-time coaxial optical sensors sensitive to visible light, infrared light, and back-reflected lasers ere used to monitor the aluminum alloy LMD process. Thin-walled parts were deposited with different laser power, and the characteristics of the three in situ signals are analyzed. The results show that there exists high linear correlation between reflected laser and accumulated deposition height. A laser reflection model was built to explain the correlation. Besides, the infrared light is linearly correlated with deposition width. Overall, the results of this study show that the optical signals are able to reflect the deposition height and width simultaneously. Infrared light signals and reflected laser signals have the potential to serve as the input of online feedback geometry control systems and real-time defect alarm systems of the LMD process.
Examining the Impact and Influencing Channels of Carbon Emission Trading Pilot Markets in China

As China has an important role in global climate change, the Chinese government has set goals to improve its environmental efficiency and performance and launched carbon emission trading pilot markets in 2013, aiming to reduce CO2 emissions. Based on panel data of 30 provinces from 2005 to 2017, this paper uses the difference-in-difference method to study the impact of China’s carbon emission trading pilot markets on carbon emissions and regional green development. The paper also explores possible influencing channels. The main conclusions are as follows: (1) China’s carbon emission trading policy has promoted a reduction in CO2 emissions and carbon emission intensity and has increased green development in the pilot areas. (2) The main path for China’s carbon emission trading policy to achieve carbon emission reduction and regional green development is to promote technology adoption. (3) China’s carbon emission trading policy achieves green development through synergistic SO2 emission reduction. The pilot carbon markets have reduced both the amount of SO2 emissions and SO2 emission intensity.