Hasil untuk "Environmental Science"

Kibebework Getachew, Wuletawu Abera, Tefera Belay et al.

Land degradation in Ethiopia is a pressing issue that demands immediate attention. Although various sustainable land management options have been introduced through top-down approaches, farmers have shown low adoption rates. The objective of this research was to assess the community prioritization of landscape restoration technologies and the appropriation of ecosystem services in the Basona-Worena and Doyo-Gena woredas of Ethiopia. The evaluation of land management option tool was used to survey farmers' preferences and compare different land management options based on input, cost, perceived advantages, and potential drawbacks.Data from 64 participants revealed that farmers were interested in a wide range of benefits. However, their top three preferences were increased food supply, enhanced soil fertility, and improved water supply. The study emphasized the need for site-specific land management measures. Farmers in Basona-Worena favored terrace and bund practices, while farmers in Doyo-Gena preferred exclosure and agroforestry practices. Conversely, the propensity of terracing to attract rodents and pests, the lengthy time takes to see results from bunding, and the cost of gabions were among the shortcomings that farmers identify in conservation techniques. Terracing was the first option for supplying fundamental ecosystem services in both locations, followed by biological measures, water percolation pits, and bunds. All farmers ranked the business-as-usual option as their least preferred option because they perceived it to have limited potential for yielding desired benefits. These findings provide a robust model for informed decision-making on suitable restoration technologies, holding promise for landscape restoration initiatives in Ethiopia and similar locations worldwide.

Walid El Kayal, Maya Salameh, Diana Nacouzi

ABSTRACT Avocado (Persea americana) stands out as one of the most significant crops globally. Due to its abundance in essential nutrients and phytochemicals, its consumption and commercialization have notably surged in recent years. The interplay between genotype and environment profoundly influences fruit maturity dates and physicochemical attributes. This study aimed to assess the transcript levels of genes involved in hormone regulation and biosynthesis in avocado fruits, correlating their expression with the crop's physiological characteristics across varying altitudes during maturity and ripening stages. The study focused on five prevalent avocado varieties: Fuerte, Hass, Pinkerton, Lambhass, and Reed. Sixteen genes participating in diverse metabolic pathways and five hormones: Abscisic acid, Jasmonic acid, Salicylic acid, Gibberellic acid, and Zeatin were quantified over the harvesting season across seven locations in Lebanon. Results revealed a notable correlation between the expression of certain genes and hormone levels in the tested varieties, contingent upon both variety and location. Phytohormone quantification exhibited significant variations across locations compared to varieties. Additionally, physicochemical characteristics were evaluated, with principal component analysis demonstrating a positive correlation between some quantified phytohormones and maturity indices among varieties and locations. This study significantly advances our understanding of the intricate relationship among phytohormones, altitudes, fruit maturity, and ripening processes across five of the most common avocado varieties.

Muhammad Waqas, Habibullah Nadeem, Ayshah Aysh Alrashidi et al.

Abstract Potassium (K+) is an essential nutrient for plants. It contributes to most physiological and biochemical pathways for plant metabolism, growth, and development. It is the most available plant nutrient, comprising 10–15% of plant weight. Plants have a sophisticated system of K+ transporters and channels for distribution in plant body. Apple is one of the most consumed fruits in the world. Its fruit quality and yield are positively affected by K+. However, limited information is available about K+ transport systems in Apple. In this study, 47 candidate genes (26 K+ transporters and 21 K+ channels) have been identified in Apple (Malus domestica) genome. The phylogenetic comparisons with other plants (Glycine max, Arabidopsis thaliana, and Oryza sativa) indicated that the K+ transport system is much conserved among different plants. The analysis of Gene structure showed the presence of specific introns and exon patterns for these gene families. Transcriptomic data analysis and RT-qPCR demonstrated significant variations in the transcript abundance of these genes in response to abiotic stresses. The current project represents the first report about the K+ transport system in Apple. Therefore, it may act as a starting point for further functional characterizations.

Chukwuma Ogechukwu Bose, Rafatullah Mohd, Kapoor Riti Thapar et al.

Lignocellulosic biomass, owing to its recalcitrant nature, requires a consortium of enzymes for its breakdown. The present study deals with the isolation of cellulolytic bacterial strains from landfill leachate collected from the Pulau Burung landfill site of Penang, Malaysia, and consortia were constructed to test their cellulolytic efficiency. The dinitro salicylate method was used for the estimation of enzyme activity, and consortia were compared with promising bacterial strains. The combined potential of promising bacterial strains was optimized at varying experimental conditions to detect their maximum cellulolytic activity. The results showed that eight bacterial strains reflected hydrolytic activities, and these were identified by 16S rDNA sequence as Bacillus subtilis, Bacillus pumilus, Bacillus proteolyticus, Bacillus paramycoides, Bacillus cereus, Bacillus altitudinis, Bacillus niacin, and Bacillus thuringiensis. Consortia A included Bacillus proteolyticus, Bacillus subtilis, Bacillus pumilus, and Bacillus paramycoides and reflected high thermophilic inclination as the optimal temperature was 45°C at pH 6 with the highest cellulase activity of 0.90 U/ml. Consortia B included Bacillus cereus, Bacillus altitudinis, Bacillus niacin, and Bacillus thuringiensis and showed a cellulase activity of 0.78 U/ml at 38°C and pH 6. The results reflected the significant potential of these Bacillus strains and consortia in the breakdown of cellulose into useful end products. The consortia further proved that a synergistic relationship was more favourable for bioconversion processes.

Olga D Anosova, Vitaliy A Kurlin

This book introduces the new research area of Geometric Data Science, where data can represent any real objects through geometric measurements. The first part of the book focuses on finite point sets. The most important result is a complete and continuous classification of all finite clouds of unordered points under rigid motion in any Euclidean space. The key challenge was to avoid the exponential complexity arising from permutations of the given unordered points. For a fixed dimension of the ambient Euclidean space, the times of all algorithms for the resulting invariants and distance metrics depend polynomially on the number of points. The second part of the book advances a similar classification in the much more difficult case of periodic point sets, which model all periodic crystals at the atomic scale. The most significant result is the hierarchy of invariants from the ultra-fast to complete ones. The key challenge was to resolve the discontinuity of crystal representations that break down under almost any noise. Experimental validation on all major materials databases confirmed the Crystal Isometry Principle: any real periodic crystal has a unique location in a common moduli space of all periodic structures under rigid motion. The resulting moduli space contains all known and not yet discovered periodic crystals and hence continuously extends Mendeleev's table to the full crystal universe.

M. S. Rajeevan, B. Mini Devi

In an age of fast-paced technological change, patents have evolved into not only legal mechanisms of intellectual property, but also structured storage containers of knowledge full of metadata, categories, and formal innovation. This chapter proposes to reframe patents in the context of information science, by focusing on patents as knowledge artifacts, and by seeing patents as fundamentally tied to the global movement of scientific and technological knowledge. With a focus on three areas, the inventions of AIs, biotech patents, and international competition with patents, this work considers how new technologies are challenging traditional notions of inventorship, access, and moral accountability.The chapter provides a critical analysis of AI's implications for patent authorship and prior art searches, ownership issues arising from proprietary claims in biotechnology to ethical dilemmas, and the problem of using patents for strategic advantage in a global context of innovation competition. In this analysis, the chapter identified the importance of organizing information, creating metadata standards about originality, implementing retrieval systems to access previous works, and ethical contemplation about patenting unseen relationships in innovation ecosystems. Ultimately, the chapter called for a collaborative, transparent, and ethically-based approach in managing knowledge in the patenting environment highlighting the role for information professionals and policy to contribute to access equity in innovation.

Sarah Al-Nasser, Maha Hamadien Abdulla, Noura Alhassan et al.

<i>Background and Objectives</i>: Colorectal cancer (CRC) remains a major global health issue. Although chemotherapy is the first-line treatment, its effectiveness is limited due to drug resistance developed in CRC. To overcome resistance and improve the prognosis of CRC patients, investigating new therapeutic approaches is necessary. <i>Materials and Methods</i>: Using human colorectal adenocarcinoma (HT29) and metastatic CRC (SW620) cell lines, the potential anticancer properties of a newly synthesized compound 1-(Isobutyl)-3-(4-methylbenzyl) benzimidazolium chloride (IMBZC) were evaluated by performing MTT cytotoxicity, cell migration, and colony formation assays, as well as by monitoring apoptosis-related protein and gene expression using Western blot and reverse transcription–quantitative polymerase chain reaction technologies. <i>Results:</i> Tested at various concentrations, the half-maximal inhibitory concentrations (IC₅₀) of IMBZC on HT29 and SW620 cell growth were determined to be 22.13 µM (6.97 μg/mL) and 15.53 µM (4.89 μg/mL), respectively. IMBZC did not alter the cell growth of normal HEK293 cell lines. In addition, IMBZC inhibited cell migration and significantly decreased colony formation, suggesting its promising role in suppressing cancer metastasis. Mechanistic analyses revealed that IMBZC treatment increased the expression of pro-apoptotic proteins p53 and Bax, while decreasing the expression of anti-apoptotic proteins Bcl-2 and Bcl-xL, thus indicating the induction of apoptosis in IMBZC-treated CRC cells, compared to untreated cells. Additionally, the addition of IMBZC to conventional chemotherapeutic drugs (i.e., 5-fluorouracil, irinotecan, and oxaliplatin) resulted in an increase in the cytotoxic potential of the drugs. <i>Conclusions</i>: This study suggests that IMBZC has substantial anticancer effects against CRC cells through its ability to induce apoptosis, inhibit cancer cell migration and colony formation, and enhance the cytotoxic effects of conventional chemotherapeutic drugs. These findings indicate that IMBZC could be a promising chemotherapeutic drug for the treatment of CRC. Further research should be conducted using in vivo models to confirm the anti-CRC activities of IMBZC.

P. Voit, M. Heistermann

<p>Counterfactuals are scenarios that describe alternative ways of how an event, in this case an extreme rainfall event, could have unfolded. In this study, we present the results of a counterfactual search for flash flood events in Germany. We used a radar-based precipitation dataset from Germany's national meteorological service (Deutscher Wetterdienst) to identify the 10 most extreme precipitation events in Germany from 2001 to 2022 and then assumed that any of these top 10 events could have happened anywhere in Germany. In other words, the events were shifted around all over Germany. For all resulting positions of the precipitation fields, we simulated the corresponding peak discharge for any affected catchment smaller than 750 km<span class="inline-formula">²</span>. From all the realizations of this simulation experiment, the maximum peak discharge was identified for each catchment.</p> <p>In a case study, we first focused on the devastating flood event in July 2021 in western Germany. We found that a moderate shifting of the event in space could change the event peak flow at the Altenahr gauge by a factor of 2. Compared to the peak flow of 1004 m<span class="inline-formula">³</span> s<span class="inline-formula">⁻¹</span> caused by the event in its original position, the worst-case counterfactual of that event led to a peak flow of 1311 m<span class="inline-formula">³</span> s<span class="inline-formula">⁻¹</span>. Shifting another event that had occurred just 1 month earlier in eastern Germany over the Ahr River valley even effectuated a simulated peak flow of 1651 m<span class="inline-formula">³</span> s<span class="inline-formula">⁻¹</span>.</p> <p>For all analysed subbasins in Germany, we found that, on average, the highest counterfactual peak exceeded the maximum original peak (between 2001 and 2022) by a factor of 5.3. For 98 % of the basins, the factor was higher than 2.</p> <p>We discuss various limitations of our analysis, which are important to be aware of, namely, the quantification and selection of candidate rainfall events, the hydrological model, and the design of the counterfactual search experiment. Still, we think that these results might help to expand the view of what could happen in the case that certain extreme events occurred elsewhere and thereby reduce the element of surprise in disaster risk management.</p>

Fetcia Jackulin, P. Senthil Kumar, Gayathri Rangasamy

Among the azo dye, Tartrazine is widely used for most of applications like pharmaceuticals, cosmetics, food, etc. As the demand for dye application is increased, the disposal of dye is also increasing. However it is very difficult to cleave due to its stability. Different methods are available, but the Advanced Oxidation Process (AOP) is an emerging technique used for treating various contaminants. In this study, sulfate radical (SO4−.) based AOP was performed to degrade tartrazine dye using iron oxide (Fe3O4) nanoparticles (NP). This NP was synthesized using the co-precipitation method, analyzed by X-Ray Diffraction (XRD), revealed the crystalline structure of the material and the average size of the particle was 16.17 nm also High Resolution- Scanning Electron Microscope (HR-SEM) showed spherical and cube shape of the particles with agglomeration. Response surface methodology (RSM) was carried out to determine the optimum condition based on central composite design. The optimum conditions were found to be pH-5.34, time- 113.58 min, NP- 0.89 g, SPS- 15.40 mM, and predicted degradation efficiency - 97.22% which was correlated to the experimental value- 96.66% with minimal error. Application of SO4−. radical implied an efficient degradation due to the involvement of both SO4−. and hydroxyl (OH-.) radical. Excess formation of SO4−. radicals, Fe2+ was majorily responsible for suppressive degradation. The intermediate compound was identified from Gas Chromatography-Mass Spectrometry (GC-MS), proved the absence of parent dye and occurrence of degradation due to Fe3O4/PS system.

Laken S. Ganoe, Amy E. Mayer, Charles Brown et al.

Abstract Understanding mesocarnivore responses to both natural and anthropogenic disturbance is crucial for understanding species' potential to maintain landscape persistence into the future. We examined the response of five mesocarnivore species (bobcat, coyote, fisher, gray fox, and red fox) to both types of disturbances and climatic conditions. The Northeastern U.S. has experienced multiple large‐scale disturbances, such as a mass defoliation event following larval spongy moth outbreak and high densities of infrastructure that divide the natural landcover into roadless zones where these species inhabit. Using dynamic occupancy models in a Bayesian framework, we aimed to (1) examine variation in species' responses over a 4‐year study by estimating variation in site‐level occupancy, colonization and extirpation of each species in the state of Rhode Island relative to natural disturbance (i.e., defoliation event), anthropogenic disturbance (i.e., parceling of natural landcover bounded by roads, distance to roads), and climate (i.e., seasonal precipitation) and (2) compare current occurrence trends to predicted asymptotic occupancy to identify key variables contributing to distribution instability. Our findings indicated declines in the occurrence of both fox species, and fisher. There was variation in mesocarnivore response to disturbance among the species. We found gray fox and fisher occupancy dynamics to be sensitive to all forms of disturbance and coyote occurrence was positively associated with anthropogenic disturbance. Although bobcat and red fox were predicted to respond positively to future climate scenarios, fisher and gray fox were not, and persistence of fisher and gray fox in a landscape of disturbance relies on large areas with high forest and shrubland cover. With the wide‐spread spongy moth outbreak across much of southern New England, our findings indicate that efforts to conserve forested lands may be crucial in maintaining the persistence of several mesocarnivore species in this region experiencing large‐scale disturbance.

Xiaoming Zhai, Matthew Nyaaba, Wenchao Ma

This study aimed to examine an assumption that generative artificial intelligence (GAI) tools can overcome the cognitive intensity that humans suffer when solving problems. We compared the performance of ChatGPT and GPT-4 on 2019 NAEP science assessments with students by cognitive demands of the items. Fifty-four tasks were coded by experts using a two-dimensional cognitive load framework, including task cognitive complexity and dimensionality. ChatGPT and GPT-4 responses were scored using the scoring keys of NAEP. The analysis of the available data was based on the average student ability scores for students who answered each item correctly and the percentage of students who responded to individual items. Results showed that both ChatGPT and GPT-4 consistently outperformed most students who answered the NAEP science assessments. As the cognitive demand for NAEP tasks increases, statistically higher average student ability scores are required to correctly address the questions. This pattern was observed for students in grades 4, 8, and 12, respectively. However, ChatGPT and GPT-4 were not statistically sensitive to the increase in cognitive demands of the tasks, except for Grade 4. As the first study focusing on comparing GAI and K-12 students in problem-solving in science, this finding implies the need for changes to educational objectives to prepare students with competence to work with GAI tools in the future. Education ought to emphasize the cultivation of advanced cognitive skills rather than depending solely on tasks that demand cognitive intensity. This approach would foster critical thinking, analytical skills, and the application of knowledge in novel contexts. Findings also suggest the need for innovative assessment practices by moving away from cognitive intensity tasks toward creativity and analytical skills to avoid the negative effects of GAI on testing more efficiently.

Fan Zhao, Yijia Chen, Dianhan Xi et al.

Hermit crabs play a crucial role in coastal ecosystems by dispersing seeds, cleaning up debris, and disturbing soil. They serve as vital indicators of marine environmental health, responding to climate change and pollution. Traditional survey methods, like quadrat sampling, are labor-intensive, time-consuming, and environmentally dependent. This study presents an innovative approach combining UAV-based remote sensing with Super-Resolution Reconstruction (SRR) and the CRAB-YOLO detection network, a modification of YOLOv8s, to monitor hermit crabs. SRR enhances image quality by addressing issues such as motion blur and insufficient resolution, significantly improving detection accuracy over conventional low-resolution fuzzy images. The CRAB-YOLO network integrates three improvements for detection accuracy, hermit crab characteristics, and computational efficiency, achieving state-of-the-art (SOTA) performance compared to other mainstream detection models. The RDN networks demonstrated the best image reconstruction performance, and CRAB-YOLO achieved a mean average precision (mAP) of 69.5% on the SRR test set, a 40% improvement over the conventional Bicubic method with a magnification factor of 4. These results indicate that the proposed method is effective in detecting hermit crabs, offering a cost-effective and automated solution for extensive hermit crab monitoring, thereby aiding coastal benthos conservation.

Miguel Fuentes, Juan Pablo Cárdenas, Gastón Olivares et al.

Resilience in social systems is crucial for mitigating the impacts of crises, such as climate change, which poses an existential threat to communities globally. As disasters become more frequent and severe, enhancing community resilience has become imperative. This study introduces a cutting-edge framework, quantitative network-based modeling called Complex Analysis for Socio-environmental Adaptation (CASA) to evaluate and strengthen social resilience. CASA transforms resilience models' linear and static structure into a complex network that integrates complexity and systems thinking, utilizing global scientific knowledge and complex network methodologies. The resulting resilience framework features rich interdependencies, and subsequent dimensionality reduction produces robust resilience indicators. This innovative application of network sciences is then demonstrated by quantitatively assessing what are known as "Sacrifice Zones," socio-environmentally sensitive areas. Results unveil the potential of this novel application of complex network methodologies as tools for systemic diagnostics, identifying vulnerabilities, and guiding policies and practices to enhance climate resilience and adaptation. The CASA framework represents a pioneering tool for assessing territorial resilience, leveraging network science applications, big data analytics, and artificial intelligence. CASA serves as a systemic diagnostic tool for urban resilience and a guide for policymakers, urban planners, and other professionals to promote sustainable, healthy cities in an era of climate change.

Cate Ryan, Bradley S. Case, Craig D. Bishop et al.

Biodiversity and ecosystem functions are deteriorating worldwide, and there is an urgent need to reverse these declines and set ecosystems on a path to recovery. Effective monitoring, including a fit for purpose indicator framework, is essential to track progress towards targets but, as yet there is no universal framework that delivers timely data on biodiversity and ecosystem change. Ecosystem integrity is a unifying concept that refers to the capacity of an ecosystem to be resilient to natural or anthropogenic perturbations, and to maintain characteristic species composition, structure, functioning and self-organisation over time within a natural range of variability. Using a case study which can be generalised to international contexts, we implement and test a new global standard for the assessment, monitoring and ranking of ecosystem integrity of active sand dunes in Aotearoa New Zealand.

Jingyu Zhao, Hanqi Ming, Tao Guo et al.

Abstract Temperature variation and gas generation at different depths and positions in the coal combustion process were studied to determine the propagation and evolution of high temperature regions in the process of coal spontaneous combustion. This study selected coal samples from Mengcun, Shaanxi Province, People’s Republic of China, and developed a semi-enclosed experimental system (furnace) for simulating coal combustion. The thermal mass loss of coal samples under various heating rates (5, 10, and 15 °C/min) was analyzed through thermogravimetric analysis, and the dynamic characteristics of the coal samples were analyzed; the reliability of the semi-enclosed experimental system was verified through the equal proportional method of fuzzy response. The results reveal that the high-temperature zone is distributed nonlinearly from the middle to the front end of the furnace, and the temperatures of points in this zone decreased gradually as the layer depth increased. The apparent activation energy of the coal samples during combustion first increased and then decreased as the conversion degree increased. Furthermore, the proportion of mass loss and the mass loss rate in the coal samples observed in the thermogravimetric experiment is consistent with that observed in the first and second stages of the experiment conducted using the semi-enclosed system. The research findings can provide a theoretical basis for the prevention and control of high-temperature zones in coal combustion.

Andres F. Castro Torres, Aliakbar Akbaritabar

The importance of research teams' diversity for the progress of science is highlighted extensively. Despite the seemingly hegemonic role of hypothesis testing in modern quantitative research, little attention has been devoted to the diversity of quantitative methods, epitomized by the linear model framework of analysis. Using bibliometric data from the Web of Science, we conduct a large-scale and cross-disciplinary assessment of the prevalence of linear-model-based research from 1990 to 2022. In absolute terms, linear models are widely used across all fields of science. In relative terms, three patterns suggest linear models are hegemonic among Social Sciences. First, there is a high and growing prevalence of linear-model-based research. Second, global patterns of linear-model-based research prevalence align with global inequalities in knowledge production. Third, there was a citation premium to linear-model-based research until 2012 for articles' number of citations and for the entire period in terms of having at least one citation. Previous research suggests that the confluence of these patterns may be detrimental to the Social Sciences as it potentially marginalizes theories incompatible with the linear models' framework, lowers the diversity of narratives about social phenomena, and prevents innovative and path-breaking research, limiting the breadth of research.

Katelyn Breivik, Andrew J. Connolly, K. E. Saavik Ford et al.

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) dataset will dramatically alter our understanding of the Universe, from the origins of the Solar System to the nature of dark matter and dark energy. Much of this research will depend on the existence of robust, tested, and scalable algorithms, software, and services. Identifying and developing such tools ahead of time has the potential to significantly accelerate the delivery of early science from LSST. Developing these collaboratively, and making them broadly available, can enable more inclusive and equitable collaboration on LSST science. To facilitate such opportunities, a community workshop entitled "From Data to Software to Science with the Rubin Observatory LSST" was organized by the LSST Interdisciplinary Network for Collaboration and Computing (LINCC) and partners, and held at the Flatiron Institute in New York, March 28-30th 2022. The workshop included over 50 in-person attendees invited from over 300 applications. It identified seven key software areas of need: (i) scalable cross-matching and distributed joining of catalogs, (ii) robust photometric redshift determination, (iii) software for determination of selection functions, (iv) frameworks for scalable time-series analyses, (v) services for image access and reprocessing at scale, (vi) object image access (cutouts) and analysis at scale, and (vii) scalable job execution systems. This white paper summarizes the discussions of this workshop. It considers the motivating science use cases, identified cross-cutting algorithms, software, and services, their high-level technical specifications, and the principles of inclusive collaborations needed to develop them. We provide it as a useful roadmap of needs, as well as to spur action and collaboration between groups and individuals looking to develop reusable software for early LSST science.

Xiao-qiang Cao, Fei Xiao, Xiao-yu Xie et al.

Functional magnetic Fe3O4@PPy microspheres were prepared and characterized by XRD, FTIR, SEM, TEM, and magnetometer, and the adsorption of Hg(II) onto Fe3O4@PPy was investigated. The results showed that the adsorption of Hg(II) onto Fe3O4@PPy dramatically increases within 5 min and reaches adsorption equilibrium at 200 min. The adsorption of Hg(II) increases with pH increased, and a removal efficiency (RE) of 90.5% was obtained at pH 7.2. The isotherm studies revealed that the adsorption of Hg(II) onto the Fe3O4@PPy fits well with the Langmuir isotherm model, and the calculated qm value of 232.56 mg/g. The adsorption process of Hg(II) onto the Fe3O4@PPy is well-fitted by the pseudo-second-order model with a high correlation coefficient (R2) of 0.999. The thermodynamic coefficients (ΔH°, ΔS°, and ΔG°) were calculated from the temperature-dependent adsorption isotherms and illustrated that the adsorption of Hg(II) on the Fe3O4@PPy was spontaneous and endothermic. Different desorption agents were used to recover Hg(II) adsorbed onto Fe3O4@PPy, and a satisfactory recovery percentage of 93.0% was obtained by using 0.1 M HCl and 0.05 M NaCl. HIGHLIGHTS Amino-functional magnetic Fe3O4@PPy microspheres were prepared and characterized.; The Hg(II) can be adsorbed by Fe3O4@PPy effectively.; The used Fe3O4@PPy could be regenerated by two-component desorbent of HCl and NaCl.;

Johan SETIAWAN, MTh Sri BUDIASTUTI, Evi GRAVITIANI et al.

The tourist spot of the Top Selfie Kragilan, Mt. Merbabu National Park, a conservation area in Indonesia has not been managed with a business strategy despite the community initiatives increase to utilize the surrounding tourist spots for their livelihood. The study aimed at formulating the tourism business management strategy using Business Model Canvas (BMC) and Strength-Weakness-Opportunity-Threat (SWOT) approaches. BMC modeling used nine aspects, namely customer segments, value propositions, channels, customer relationships, revenue streams, key resources, key activities, key partners, and cost structure; then analyzed using SWOT approaches. A total of 377 respondents were interviewed to collect the data. The results showed that every aspect of the old business model has been added or innovated according to the analysis of internal and external factors. Also, there has been a "meeting point" between market expectations, the value offered, and the promotional channels used. The combined strategy of Aggressive (S-O) and Diversification (S-T) should be applied to mitigate damage impact, conserve the natural resources, and arranging visits and selfie vehicles/ photo spot to boost revenue streams.

Tor Ole B. Odden, Devin Silvia, Anders Malthe-Sørenssen

This article reports on a study investigating how computational essays can be used to redistribute epistemic agency--cognitive control and responsibility over one's own learning--to students in higher education STEM. Computational essays are a genre of scientific writing that combine live, executable computer code with narrative text to present a computational model or analysis. The study took place across two contrasting university contexts: an interdisciplinary data science and modeling course at Michigan State University, USA, and a third-semester physics course at the University of Oslo, Norway. Over the course of a semester, computational essays were simultaneously and independently used in both courses, and comparable datasets of student artifacts and retrospective interviews were collected from both student populations. These data were analyzed using a framework which operationalized the construct of epistemic agency across the dimensions of programming, inquiry, data analysis and modeling, and communication. Based on this analysis, we argue that computational essays can be a useful tool in redistributing epistemic agency to students within higher education science due to their combination of adaptability and disciplinary authenticity. However, we also argue that educational contexts, scaffolding, expectations, and student backgrounds can constrain and influence the ways in which students choose to take up epistemic agency.