Science Case Research Articles

Sappho Scientific Evidence Platform on Gender: Narratives of Academics and Non-Academics about a Community Science Case

Modern society's digitization has led to the creation of online science platforms. Research shows that academic-oriented platforms boost active research teams, enhance scientific collaboration, and encourage manuscript reviews. However, there is limited research on platforms for citizen participation in science. This study examines the Sappho Scientific Evidence Platform, which aims to provide a science-based participatory tool with a focus on gender-related issues. Using a qualitative communicative approach, 10 users (6 primary school teachers, 2 researchers, and 2 university professors) were interviewed about their platform usage, impacts encountered, and the dialogues between citizens and scientists. The findings reveal that both academics and non-academics can contribute to science on Sappho. Participants reported improved scientific literacy, enhanced conversations about scientific evidence, and the use of this evidence in their personal and professional lives. The platform empowers users to critically engage with gender issues. These results highlight Sappho's positive impact and its potential as a valuable tool for promoting scientific evidence among its users.

Is phenomenal consciousness really a special case in science?

In the metaphysics of science, it is often held that higher-level properties are grounded in micro-physical properties. According to many philosophers, however, phenomenal consciousness resists this view. Many famous arguments in Philosophy of Mind have been given to reject this notion. In this paper, we argue that there is something odd about the idea that phenomenal consciousness is a special case in science and give a constructive proposal on how consciousness can fit in the natural world. To do so, we will first introduce a general notion of what grounding is. Then, we will briefly explain how the arguments for the specialness of phenomenal consciousness work by considering two famous examples, namely the zombie and the knowledge argument. In a further step, we will briefly discuss two cases from other areas in science, i.e., in particle physics and chemistry. We will demonstrate that the standard view about the reductive relation does not hold, even in these paradigm cases of the natural sciences. If what we argue is true, we think that most arguments from phenomenal consciousness cannot defeat physicalism per se. Finally, we will introduce an alternative way to naturalize phenomenal consciousness.

Identifying Process Differences with ToF-SIMS: An MVA Decomposition Strategy.

In time-of-flight secondary ion mass spectrometry (ToF-SIMS), multivariate analysis (MVA) methods such as principal component analysis (PCA) are routinely employed to differentiate spectra. However, additional insights can often be gained by comparing processes, where each process is characterized by its own start and end spectra, such as when identical samples undergo slightly different treatments or when slightly different samples receive the same treatment. This study proposes a strategy to compare such processes by decomposing the loading vectors associated with them, which highlights differences in the relative behavior of the peaks. This strategy identifies key information beyond what is captured by the loading vectors or the end spectra alone. While PCA is widely used, partial least-squares discriminant analysis (PLS-DA) serves as a supervised alternative and is the preferred method for deriving process-related loading vectors when classes are narrowly separated. The effectiveness of the decomposition strategy is demonstrated using artificial spectra and applied to a ToF-SIMS materials science case study on the photodegradation of N719 dye, a common dye in photovoltaics, on a mesoporous TiO2 anode. The study revealed that the photodegradation process varies over time, and the resulting fragments have been identified accordingly. The proposed methodology, applicable to both labeled (supervised) and unlabeled (unsupervised) spectral data, can be seamlessly integrated into most modern mass spectrometry data analysis workflows to automatically generate a list of peaks whose relative behavior varies between two processes, and is particularly effective in identifying subtle differences between highly similar physicochemical processes.

The impact of COVID-19 on the debate on open science: a qualitative analysis of published materials from the period of the pandemic

This study is an analysis of the international debate on open science that took place during the pandemic. It addresses the question, how did the COVID-19 pandemic impact the debate on open science? The study takes the form of a qualitative analysis of a large corpus of key articles, editorials, blogs and thought pieces about the impact of COVID on open science, published during the pandemic in English, German, Portuguese, and Spanish. The findings show that many authors believed that it was clear that the experience of the pandemic had illustrated or strengthened the case for open science, with language such as a “stress test”, “catalyst”, “revolution” or “tipping point” frequently used. It was commonly believed that open science had played a positive role in the response to the pandemic, creating a clear ‘line of sight’ between open science and societal benefits. Whilst the arguments about open science deployed in the debate were not substantially new, the focuses of debate changed in some key respects. There was much less attention given to business models for open access and critical perspectives on open science, but open data sharing, preprinting, information quality and misinformation became most prominent in debates. There were also moves to reframe open science conceptually, particularly in connecting science with society and addressing broader questions of equity.

Could bibliometrics reveal top science and technology achievements and researchers? The case for evaluatology-based science and technology evaluation

By utilizing statistical methods to analyze bibliographic data, bibliometrics faces inherent limitations in identifying the most significant science and technology achievements and researchers. To overcome this challenge, we present an evaluatology-based science and technology evaluation methodology. At the heart of this approach lies the concept of an extended evaluation condition, encompassing nine crucial components derived from a field. We define four relationships that illustrate the connections among various achievements based on their mapped extended EC components, as well as their temporal and citation links. Within a relationship under an extended evaluation condition, evaluators can effectively compare these achievements by carefully addressing the influence of confounding variables. We establish a real-world evaluation system encompassing an entire collection of achievements, each of which is mapped to several components of an extended EC. Within a specific field like chip technology or open source, we construct a perfect evaluation model that can accurately trace the evolution and development of all achievements in terms of four relationships based on the real-world evaluation system. Building upon the foundation of the perfect evaluation model, we put forth four-round rules to eliminate non-significant achievements by utilizing four relationships. This process allows us to establish a pragmatic evaluation model that effectively captures the essential achievements, serving as a curated collection of the top N achievements within a specific field during a specific timeframe. We present a case study on the top 100 Chip achievements to demonstrate the effectiveness of our science and technology evaluatology. The case study highlights its practical application and efficacy in identifying significant achievements and researchers that otherwise can not be identified by using bibliometrics.

The PAU survey: photometric redshift estimation in deep wide fields

ABSTRACT We present photometric redshifts (photo-z) for the deep wide fields of the Physics of the Accelerating Universe Survey (PAUS), covering an area of $\sim$50 deg$^{2}$, for $\sim$1.8 million objects up to $i_{\rm {AB}}\lt 23$. The PAUS deep wide fields overlap with the W1 and W3 fields from CFHTLenS and the G09 field from KiDS/GAMA. Photo-z are estimated using the 40 narrow bands (NB) of PAUS and the broad-bands (BB) of CFHTLenS and KiDS. We compute the redshifts with the SED template-fitting code bcnz, with a modification in the calibration technique of the zero-point between the observed and the modelled fluxes, that removes any dependence on spectroscopic redshift samples. We enhance the redshift accuracy by introducing an additional photo-z estimate ($z_{\textrm {b}}$), obtained through the combination of the bcnz and the BB-only photo-z. Comparing with spectroscopic redshift estimates ($z_{\textrm {s}}$), we obtain a $\sigma _{68} \simeq 0.020$ for all galaxies with $i_{\rm {AB}}\lt 23$ and a typical bias $|z_{\textrm {b}}\!-\!z_{\textrm {s}}|$ smaller than 0.01. For $z_{\textrm {b}} \sim (0.10\!-\!0.75)$, we find $\sigma _{68} \simeq (0.003\!-\!0.02)$, this is a factor of $10\!-\!2$ higher accuracy than the corresponding BB-only results. We obtain similar performance when we split the samples into red (passive) and blue (active) galaxies. We validate the redshift probability $p(z)$ obtained by bcnz and compare its performance with that of $z_{\textrm {b}}$. These photo-z catalogues will facilitate important science cases, such as the study of galaxy clustering and intrinsic alignment at high redshifts ($z \lesssim 1$) and faint magnitudes.

HOMERUN: A new approach to photoionization modeling

We present HOMERUN (Highly Optimized Multi-cloud Emission-line Ratios Using photo-ionizatioN), a new approach to modeling emission lines from photoionized gas that can simultaneously reproduce all observed line intensities from a wide range of ionization levels with high accuracy. Our approach is based on the weighted combination of multiple single-cloud photoionization models, and contrary to previous works, the novelty of our approach consists of using the weights as free parameters of the fit and constraining them with the observed data. One of the main applications of HOMERUN is the accurate determination of gas-phase metallicities, and we show that a critical point is to allow for a variation of the N/O and S/O abundance ratios, as this can significantly improve the quality of the fit and the accuracy of the results. Moreover, our approach provides a major improvement compared to the single-cloud constant-pressure models commonly used in the literature. By using high-quality spectra from the literature of H II regions, where 10 to 20 emission lines (including several auroral lines) are detected with a high signal-to-noise ratio, we show that all lines are reproduced by the model with an accuracy better than 10%. In particular, the model is able to simultaneously reproduce [O I]λλ6300, 6363; [O II]λλ3726, 3729; [O III]λλ4959, 5007; [S II]λλ6717, 6731; and [S III]λλ9069, 9532 emission lines, which to our knowledge is an unprecedented result. Finally, we show that the gas metallicities estimated with our models for HII regions in the Milky Way are in better agreement with the stellar metallicities than the estimates based on the Te method. Overall, our method provides a new accurate tool to estimate the metallicity and the physical conditions of the ionized gas. It can be applied to many different science cases, from HII regions to active galactic nuclei, and wherever there are emission lines from photoionized gas.

The NIRSpec Wide GTO Survey

The Near-infrared Spectrograph (NIRSpec) on the James Webb Space Telescope is uniquely suited to studying galaxies in the distant Universe with its combination of multi-object capabilities and sensitivity over a large range in wavelength (0.6 − 5.3 μm). Here we present the NIRSpec Wide survey, part of the NIRSpec Instrument Science Team’s Guaranteed Time Observations, using NIRSpec’s microshutter array to obtain spectra of more than 3200 galaxies at z > 1 at both low and high resolution (R ≈ 100 and 2700) for a total of 105 hours. With 31 pointings covering ≈320 arcmin2 across the five CANDELS fields with exquisite ancillary photometry from the Hubble Space Telescope, the NIRSpec Wide survey represents a fast and efficient way of probing galaxies in the early Universe. Pointing centers are determined to maximize the observability of the rarest, high-value sources. Subsequently, the microshutter configurations are optimized to observe the maximum number of “census” galaxies with a selection function based primarily on HST/F160W magnitude, photometric or slitless grism redshift, and predicted Hα flux tracing the bulk of the galaxy population at cosmic noon (zmed = 2.0). We present details on the survey strategy, the target selection, an outline of the motivating science cases, and discuss upcoming public data releases to the community.

Women are under-represented in adaptation policy research and are more likely to emphasise justice topics

Abstract This paper is the first to analyse the role of women authors in fostering justice-relevant topics in climate adaptation research. As representation, citation and payment patterns remain gender-biased across scientific disciplines, we explore the case of climate science, particularly adaptation, as its most human-oriented facet. In climate research and policy, there has been a recent surge of interest in climate justice topics: mentions of justice have increased almost tenfold in IPCC Working Group 2 reports between the latest assessment cycles (AR5 and AR6). We conduct a systematic examination of the topic space in the adaptation policy scholarship. As it is a vast and rapidly growing field, we use topic modelling, an unsupervised machine learning method, to identify the literature on climate justice and related fields, as well as to examine the relationship between topic prevalence and the gender of the authors. We find climate change adaptation policy research to be male dominated, with women holding 38.8% of first and 28.8% of last authorships. However, we observe topic-specific variability, whereby the share of female authors is higher among publications on justice-relevant topics. Female authorship is highly linked to topics such as Community, Local Knowledge, and Governance, but less to Food Security and Climate Finance. Our findings corroborate the evidence that female authors play a significant role in advancing the research and dialogue on the relationship between climate change and areas that have meaningful impact on lives of women and other marginalised groups.

A bilinear modeling in counts time series with applications

This paper introduces a modified bilinear model for integer-valued time series in which thinning operators are applied in bilinear terms involving the product of the input and state process separately. The proposed model is able to consider overdispersion. Furthermore, it connects a feature of the integer-valued autoregressive conditional heteroskedasticity and integer-valued autoregressive processes. Important properties of the proposed model as well as the sufficient condition for stationarity are derived. After considering some estimation methods based on time domain and frequency domain approaches, simulation studies are conducted to check the performance of the estimates. The analysis of practical cases in social science is accomplished to highlight the usefulness of the proposed model in applications, and the model’s adequacy is provided. Further, the suggested model discusses the problem of data forecasting.

Synergies between the circular economy and carbon emission reduction

Climate change and sustainable development drive transformation in economic development models. Carbon emission reduction and the circular economy propel climate change and sustainable development, yet it's unclear if they synergize or counteract each other. This study examines the question from theoretical and practical perspectives. Using a theory-practice framework, bibliometric and big data analyses were conducted on the Web of Science and Chinese case data, totaling 2.29GB, to explore synergies between carbon emission reduction and the circular economy. The study finds predominantly synergistic interactions between the circular economy and carbon emission reduction, with minimal offsetting effects. That is, the circular economy markedly enhances carbon emissions reduction. At the theoretical level, the two fields are gradually evolving towards in-depth research, while at the practical level, collaboration is coalescing around four areas: hot fields, potential fields, auxiliary fields and common goals. A noteworthy contribution of this study is the development of a framework that synergizes theory and practice, providing a structured approach for future research in this domain. By quantifying the synergistic and offsetting relationship between the circular economy and carbon emissions reduction through systematic big data analysis, this research offers insights essential for achieving the UN's Sustainable Development Goals. We also stress the need for diverse case studies and multi-dimensional analyses in ongoing research.

Numerical simulations for the SAXO+ upgrade: Performance analysis of the adaptive optics system

SPHERE, operating at the VLT since 2014, is currently one of the high-contrast instruments with a higher performance. Its adaptive optics system, known as SAXO, will be upgraded to SAXO+, which features the addition of a second stage of adaptive optics. This stage will use a near-infrared pyramid wavefront sensor to record images of fainter exoplanets around redder stars. In this work, we compare the performance of SAXO and SAXO+. We look for the optimal values of the key system parameters of SAXO+ for various science cases and turbulence conditions. We performed numerical simulations using COMPASS, an end-to-end adaptive optics simulation tool. We simulated perfect coronagraph images of an on-axis point source, and we minimized the residual starlight intensity between 3 and $5\ / D$ as a performance criterion. The explored parameter space includes science cases (described by magnitude in G and J bands), turbulence conditions (seeing and coherence time), and key system parameters (first and second stage gains, first and second stage frequencies, pyramid modulation radius, pyramid modal gains optimization). In every science case and turbulence condition, SAXO+ reduces the residual starlight intensity inside the correction zone of the second stage by a factor of ten compared to SAXO. The optimal first stage gain is lower for SAXO+ than for SAXO alone. We quantified the gain in performance of SAXO+ when changing the second stage frequency from 2\,kHz to 3\,kHz, and we conclude that 2\,kHz may be sufficient for most realistic conditions. We give the optimal first stage gain as well as the first and second stage frequencies for every seeing, coherence time, and science case. Finally, we find that a $2\ WFS / D$ pyramid modulation radius is a good trade-off between performance and robustness against varying turbulence conditions. This study shows that the future SAXO+ system will outperform the current SAXO system in all studied cases.

Science development study for the Atacama Large Aperture Submillimeter Telescope (AtLAST): Solar and stellar observations.

Observations at (sub-)millimeter wavelengths offer a complementary perspective on our Sun and other stars, offering significant insights into both the thermal and magnetic composition of their chromospheres. Despite the fundamental progress in (sub-)millimeter observations of the Sun, some important aspects require diagnostic capabilities that are not offered by existing observatories. In particular, simultaneously observations of the radiation continuum across an extended frequency range would facilitate the mapping of different layers and thus ultimately the 3D structure of the solar atmosphere. Mapping large regions on the Sun or even the whole solar disk at a very high temporal cadence would be crucial for systematically detecting and following the temporal evolution of flares, while synoptic observations, i.e., daily maps, over periods of years would provide an unprecedented view of the solar activity cycle in this wavelength regime. As our Sun is a fundamental reference for studying the atmospheres of active main sequence stars, observing the Sun and other stars with the same instrument would unlock the enormous diagnostic potential for understanding stellar activity and its impact on exoplanets. The Atacama Large Aperture Submillimeter Telescope (AtLAST), a single-dish telescope with 50m aperture proposed to be built in the Atacama desert in Chile, would be able to provide these observational capabilities. Equipped with a large number of detector elements for probing the radiation continuum across a wide frequency range, AtLAST would address a wide range of scientific topics including the thermal structure and heating of the solar chromosphere, flares and prominences, and the solar activity cycle. In this white paper, the key science cases and their technical requirements for AtLAST are discussed.

Programme science methodologies and practices that address "FURRIE" challenges: examples from the field.

"Programme science" deploys scientific methods to address questions that are a priority to support the impact of public health programmes. As such, programme science responds to the challenges of making such studies: (1) feasible to undertake, (2) useful, (3) rigorous, (4) real-world-relevant, (5) informative, and undertaken by (6) equitable partnerships. The acronym "FURRIE" is proposed to describe this set of six challenges. This paper discusses selected HIV/STI (sexually transmitted infection) programme science case studies to illustrate how programme science rises to the FURRIE challenges. One way in which programme science is made more feasible is through the analysis and interpretation of data collected through service delivery. For some questions, these data can be augmented through methods that reach potential clients of services who have not accessed services or been lost to follow-up. Process evaluation can enhance the usefulness of programme science by studying implementation processes, programme-client interactions and contextual factors. Ensuring rigour by limiting bias and confounding in the real-world context of programme science studies requires methodological innovation. Striving for scientific rigour can also have the unintended consequence of creating a gap between what happens in a study, and what happens in the "real-world." Community-led monitoring is one approach to grounding data collection in the real-world experience of clients. Evaluating complex, context-specific strategies to strengthen health outcomes in a way that is informative for other settings requires clear specification of the intervention packages that are planned and delivered in practice. Programme science provides a model for equitable partnership through co-leadership between programmes, researchers and the communities they serve. Programme science addresses the FURRIE challenges, thereby improving programme impact and ultimately health outcomes and health equity. The adoption and adaptation of the types of novel programme science approaches showcased here should be promoted within and beyond the HIV/STI field.

Atacama Large Aperture Submillimeter Telescope (AtLAST) science: Probing the transient and time-variable sky

The study of transient and variable events, including novae, active galactic nuclei, and black hole binaries, has historically been a fruitful path for elucidating the evolutionary mechanisms of our universe. The study of such events in the millimeter and submillimeter is, however, still in its infancy. Submillimeter observations probe a variety of materials, such as optically thick dust, which are hard to study in other wavelengths. Submillimeter observations are sensitive to a number of emission mechanisms, from the aforementioned cold dust, to hot free-free emission, and synchrotron emission from energetic particles. Study of these phenomena has been hampered by a lack of prompt, high sensitivity submillimeter follow-up, as well as by a lack of high-sky-coverage submillimeter surveys. In this paper, we describe how the proposed Atacama Large Aperture Submillimeter Telescope (AtLAST) could fill in these gaps in our understanding of the transient universe. We discuss a number of science cases that would benefit from AtLAST observations, and detail how AtLAST is uniquely suited to contributing to them. In particular, AtLAST’s large field of view will enable serendipitous detections of transient events, while its anticipated ability to get on source quickly and observe simultaneously in multiple bands make it also ideally suited for transient follow-up. We make theoretical predictions for the instrumental and observatory properties required to significantly contribute to these science cases, and compare them to the projected AtLAST capabilities. Finally, we consider the unique ways in which transient science cases constrain the observational strategies of AtLAST, and make prescriptions for how AtLAST should observe in order to maximize its transient science output without impinging on other science cases.

The social construction of science Case of researchers from the National System of Researchers in Mexico

The social construction of science Case of researchers from the National System of Researchers in Mexico

CREDIT CARD FRAUD DETECTION

It is important that credit card companies are able to recognize fraudulent credit card transactions so that customers are not charged for items that they did not purchase. In an era where digital transactions have become ubiquitous, the security of financial transactions is of paramount importance. The advent of machine learning and data science techniques offers promising avenues for enhancing fraud detection mechanisms. Analysing a dataset is a critical step in obtaining relevant insights from massive amounts of data. This research paper delves into the use case of Data science & Machine Learning and its applications for our major project. It goes into the use of Python as a powerful tool for data analysis, emphasizing its importance in dealing with complex datasets. Furthermore, the project investigates the many Python libraries used in data science and machine learning applications, the significance of data visualization with Libraries such as Seaborn and Matplotlib, etc. After which it goes on with the main work. This project of ours delves into the realm of credit card fraud detection, leveraging Python and its powerful libraries such as NumPy, Pandas, Seaborn, TensorFlow, and Matplotlib for comprehensive data analysis and visualization. Employing a host of machine learning algorithms including K-Nearest Neighbors, Logistic Regression, Random Forest, Decision Tree, and LDA, the project aims to tackle the challenge posed by highly unbalanced datasets, specifically transactions made by European cardholders in September 2013. By discerning fraudulent transactions accurately, this endeavour seeks to bolster the integrity of financial systems, safeguarding both customers and institutions from potential losses. Keywords: Python, pandas, seaborn, data science, machine learning.

Into the red: An M-band study of the chemistry and rotation of β Pictoris b at high spectral resolution

Abstract High-resolution cross-correlation spectroscopy (HRCCS) combined with adaptive optics has been enormously successful in advancing our knowledge of exoplanet atmospheres, from chemistry to rotation and atmospheric dynamics. This powerful technique now drives major science cases for ELT instrumentation including METIS/ELT, GMTNIRS/GMT and MICHI/TMT, targeting biosignatures on rocky planets at 3–5 μm, but remains untested beyond 3.5 μm where the sky thermal background begins to provide the dominant contribution to the noise. We present 3.51–5.21 μm M-band CRIRES+/VLT observations of the archetypal young directly imaged gas giant β Pictoris b, detecting CO absorption at S/N = 6.6 at 4.73 μm and H2O at S/N = 5.7, and thus extending the use of HRCCS into the thermal background noise dominated infrared. Using this novel spectral range to search for more diverse chemistry we report marginal evidence of SiO at S/N = 4.3, potentially indicative that previously proposed magnesium-silicate clouds in the atmosphere are either patchy, transparent at M-band wavelengths, or possibly absent on the planetary hemisphere observed. The molecular detections are rotationally broadened by the spin of β Pic b, and we infer a planetary rotation velocity of vsin(i) = 22 ± 2 km s−1 from the cross-correlation with the H2O model template, consistent with previous K-band studies. We discuss the observational challenges posed by the thermal background and telluric contamination in the M-band, the custom analysis procedures required to mitigate these issues, and the opportunities to exploit this new infrared window for HRCCS using existing and next-generation instrumentation.

A bibliometric analysis of the literature on goat breeding

Background Bibliometric analysis plays an essential role in scientific research. However, some research areas still have several gaps. This is also the case in the animal sciences. Therefore, the status of current studies can be analyzed to provide guidance for future research through scientific studies that will be conducted. The aim of this study was to perform a bibliometric analysis of goat breeding to evaluate current trends, gaps in knowledge, and future perspectives. Methods A large dataset was extracted from the Web of Science (WoS), a popular database for scientific studies. According to the WoS, we used 1000 scientific papers (1991–2023) that contained articles, book chapters, data papers, proceedings papers, meeting abstracts, and notes. All bibliometric analyses were performed using the bibliometrix package. Results and Conclusions In 2023, there were 34 studies available. Average citations per year showed that the highest average citation count occurred in 2006 (31.35). In total, 265 scientific journals in the WoS database have published goat breeding studies. Small Ruminant Research led to the remaining 145 articles. In conclusion, scientific studies on goat breeding have become popular in recent years. The authors may gravitate towards popular journals in the future.

An industry review of recent graduate employee’s performance compared to workplace expectations: An environmental science case study

This study developed and tested a model of higher education environmental science program review through industry-wide surveys of environmental science graduate employers. We surveyed 62 environmental professionals who manage recent environmental science graduate employees in eastern Australia. The survey captured expectations of graduates’ skill performance compared to workplace expectations in the first 6 months of employment in both degree-specific skills and general employment skills. Graduate employee skill importance was ranked significantly higher than their actual performance in degree-specific skills including field work, formal correspondence, policy development, data analysis/interpretation, and understanding environmental legislation. Performance was also significantly lower than expectations of generic employment skills including foundation, collaborative, and employability skills. Work placement within undergraduate programs was reported as being pivotal in efficiently preparing graduates, although workplace time limitations hinder participation. This study provides new evidence for universities to adopt work placement or other work integrated learning as a core program component, embed skill awareness and skill portfolio development in curricula, and periodically undertake industry review of graduate employee performance compared to workplace expectations. The new model presented here, of higher education program review, incorporating both graduate employee performance and employer expectations, will assist universities continuing relevancy in a dynamic employment market.