Environmental degradation poses significant challenges to Bangladesh's sustainable development, given its dense population and vulnerability to climate change. Media, particularly print journalism, plays a crucial role in addressing these challenges by raising awareness and fostering public discourse. This study examines environmental reporting in Bangladeshi print media, focusing on depth, source diversity, and long-term impact. Through qualitative analysis and interviews, it evaluates coverage depth, source credibility, and societal outcomes. Findings reveal a mix of superficial and investigative reporting, with varied source usage. While challenges like resource constraints and censorship exist, opportunities for improvement through training, investigative focus, source diversification, and ethical reporting practices are identified. Enhancing environmental journalism's quality and impact can promote public awareness, policy discourse, and societal change, contributing to Bangladesh's environmental sustainability.
Ioanna Mitropoulou, Amir Vaxman, Olga Diamanti
et al.
We present a method to fabricate double shell structures printed in trans-versal directions using multi-axis fused-deposition-modeling (FDM) robot-ic 3D printing. Shell structures, characterized by lightweight, thin walls, fast buildup, and minimal material usage, find diverse applications in pro-totyping and architecture for uses such as façade panels, molds for concrete casting, or full-scale pavilions. We leverage an underlying representation of transversal strip networks generated using existing methods and propose a methodology for converting them into printable partitions. Each partition is printed separately and assembled into a double-shell structure. We out-line the specifications and workflow that make the printing of each piece and the subsequent assembly process feasible. The versatility and robust-ness of our method are demonstrated with both digital and fabricated re-sults on surfaces of different scales and geometric complexity.
Maryam Eftekharifar, Churun Zhang, Jialiang Wei
et al.
We present a framework that pioneers the prediction of photochemical conversion in complex three-dimensionally printed objects, introducing a challenging new computer vision task: predicting dense, non-visual volumetric physical properties from 3D visual data. This approach leverages the largest-ever optically printed 3D specimen dataset, comprising a large family of parametrically designed complex minimal surface structures that have undergone terminal chemical characterisation. Conventional vision models are ill-equipped for this task, as they lack an inductive bias for the coupled, non-linear interactions of optical physics (diffraction, absorption) and material physics (diffusion, convection) that govern the final chemical state. To address this, we propose Coupled Physics-Gated Adaptation (C-PGA), a novel multimodal fusion architecture. Unlike standard concatenation, C-PGA explicitly models physical coupling by using sparse geometrical and process parameters (e.g., surface transport, print layer height) as a Query to dynamically gate and adapt the dense visual features via feature-wise linear modulation (FiLM). This mechanism spatially modulates dual 3D visual streams-extracted by parallel 3D-CNNs processing raw projection stacks and their diffusion-diffraction corrected counterparts allowing the model to recalibrate its visual perception based on the physical context. This approach offers a breakthrough in virtual chemical characterisation, eliminating the need for traditional post-print measurements and enabling precise control over the chemical conversion state.
Given the substantial growth in the use of additive manufacturing in construction (AMC), it is necessary to ensure the quality of printed specimens which can be much more complex than conventionally manufactured parts. This study explores the various aspects of geometry and surface quality control for 3D concrete printing (3DCP), with a particular emphasis on deposition-based methods, namely extrusion and shotcrete 3D printing (SC3DP). A comprehensive overview of existing quality control (QC) methods and strategies is provided and preceded by an in-depth discussion. Four categories of data capture technologies are investigated and their advantages and limitations in the context of AMC are discussed. Additionally, the effects of environmental conditions and objects' properties on data capture are also analyzed. The study extends to automated data capture planning methods for different sensors. Furthermore, various quality control strategies are explored across different stages of the fabrication cycle of the printed object including: (i) During printing, (ii) Layer-wise, (iii) Preassembly, and (iv) Assembly. In addition to reviewing the methods already applied in AMC, we also address various research gaps and future trends and highlight potential methodologies from adjacent domains that could be transferred to AMC.
Imami Arum Tri Rahayu, Handini Novita Sari, Lilik Anifah
et al.
Daun Efek is a Small Medium Enterprises in Sidoarjo which is engaged in the production of eco-print batik cloth. In making eco-print batik, UKM Daun Efek still uses conventional methods, thus causing the limited amount of production produced. Other constraints faced are the lack of attractive product packaging and lack of widespread marketing, so that turnover is difficult to increase due to lack of consumer reach. This activity uses an implementation method through a participatory approach, including such as FGDs, training and mentoring as well as discussion activities to exchange experiences between the proposing team and partners. From the implementation method that implemented, a grant machine was produced in the form of an eco-print batik steamer machine, which is able to increase the amount of production from 6 sheets of batik cloth per day to 18 pieces of batik cloth per day. In addition to production management, there was also improved the quality of product packaging from simple and unattractive to a packaging that has good, creative, and imprinted elements in the eyes of consumers through green box-shaped packaging with the partner logo. The reach of consumers has become wider with the marketing through social media.
Joan Casals Pañella, Marta Domènech, Sara Vima Grau
et al.
El presente artículo plantea una reflexión en torno al legado arquitectónico residencial en Europa posterior a la Segunda Guerra Mundial, a través del estudio de la rehabilitación del edificio DeFlat Kleiburg, ubicado en el barrio Bijlmermeer de Ámsterdam (2017). En particular, se propone una revisión crítica sobre la obsolescencia de las grandes actuaciones residenciales modernas concebidas como respuesta a la necesidad de provisión masiva de vivienda en el período de posguerra, así como sobre las estrategias y motivaciones contemporáneas para su rehabilitación. El texto profundiza en el estudio de los debates y prácticas que entienden el entorno habitado como un componente crucial del patrimonio construido, subrayando la necesidad de preservar los conjuntos residenciales como instrumento para fortalecer la cohesión social. Asimismo, se analiza en detalle la transformación llevada a cabo en Kleiburg, basada en una estrategia de rehabilitación interior orientada a salvaguardar la composición, los acabados y la estructura original, al tiempo que promueve la flexibilidad funcional y la diversificación tipológica y de usos.
Conservation and restoration of prints, Architectural drawing and design
Mark Donald C Reñosa, Shannon A McMahon, Jonas Wachinger
et al.
Introduction Mass media plays a key role in shaping medical discourses on a societal level, and understanding this role could inform context-specific approaches to address current health challenges. However, public health scholarship that focuses on low- and middle-income countries, draws on media analytic approaches established in other fields, or utilises the potential of digital platforms for understanding non-print mass media remains limited. One context meriting a better understanding of media communication is vaccination in the Philippines, where large-scale discourses have repeatedly challenged vaccine confidence.Methods To understand how vaccine information has been communicated on Philippine TV broadcasts, we systematically searched and extracted n=108 broadcasts using YouTube API queries. Our approach covered 16 years of broadcasting throughout three major waves of vaccination reporting including routine communication, the Dengvaxia controversy and its fallout, and the COVID-19 pandemic. We conducted a content analysis of the full dataset, followed by an in-depth qualitative framing analysis of 16 purposively selected broadcasts.Results Our results highlight how broadcasts across periods of varying discourse intensity were generally pro-vaccine leaning. However, key vaccine information, such as regarding the safety and efficacy of immunisation, was often lacking. Framing of vaccination varied within and across broadcasts and over time as communication stakeholders (including broadcasters, medical or scientific professionals, political actors, and lay individuals) employed medical (eg, providing explanations of disease risks or vaccine functioning), political (eg, suggesting accountability and highlighting actions taken) and social frames (eg, emphasising belonging and community-level relevance).Conclusion Vaccine messaging changes based on shifting societal discourses, stakeholders and communication objectives. Training health professionals to emphasise under-represented information and to purposively engage with prominent message frames could improve vaccination communication. Beyond vaccine hesitancy, our results also highlight how methodological advances can guide public health stakeholders analysing societal discourses and seeking to convey medical information to the broader population.
Ethics for Journalists tackles many of the issues which journalists face in their everyday lives - from the media's supposed obsession with sex, sleaze and sensationalism, to issues of regulation and censorship. Its accessible style and question and answer approach highlights the relevance of ethical issues for everyone involved in journalism, both trainees and professionals, whether working in print, broadcast or new media. Keeble provides a comprehensive overview of ethical dilemmas and features interviews with a number of journalists. Presenting a range of imaginative strategies for improving media standards and supported by a thorough bibliography and a wide ranging list of websites, Ethics for Journalists considers many problematic subjects including: The representation of women, blacks, gays and lesbians, and the mentally ill Controversial calls for a privacy law to restrain the power of the press Journalistic techniques such as sourcing the news, doorstepping, deathknocks and the use of subterfuge The impact of competition, ownership and advertising on media standards The handling of confidential sources and the dilemmas of war reporting.
Sammy Florczak, Gabriel Groessbacher, Davide Ribezzi
et al.
We introduce Generative, Adaptive, Context-Aware 3D Printing (GRACE), a novel approach combining 3D imaging, computer vision, and parametric modelling to create tailored, context-aware geometries using volumetric additive manufacturing. GRACE rapidly and automatically generates complex structures capable of conforming directly around features ranging from cellular to macroscopic scales with minimal user intervention. We demonstrate its versatility in applications ranging from synthetic objects to biofabrication, including adaptive vascular-like geometries around cell-laden bioinks, resulting in improved functionality. GRACE also enables precise alignment of sequential prints, in addition to the detection and overprinting of opaque surfaces through shadow correction. Compatible with various printing modalities, GRACE transcends traditional additive manufacturing limitations, opening new avenues in tissue engineering and regenerative medicine.
Media bias significantly shapes public perception by reinforcing stereotypes and exacerbating societal divisions. Prior research has often focused on isolated media bias dimensions such as \textit{political bias} or \textit{racial bias}, neglecting the complex interrelationships among various bias dimensions across different topic domains. Moreover, we observe that models trained on existing media bias benchmarks fail to generalize effectively on recent social media posts, particularly in certain bias identification tasks. This shortfall primarily arises because these benchmarks do not adequately reflect the rapidly evolving nature of social media content, which is characterized by shifting user behaviors and emerging trends. In response to these limitations, our research introduces a novel dataset collected from YouTube and Reddit over the past five years. Our dataset includes automated annotations for YouTube content across a broad spectrum of bias dimensions, such as gender, racial, and political biases, as well as hate speech, among others. It spans diverse domains including politics, sports, healthcare, education, and entertainment, reflecting the complex interplay of biases across different societal sectors. Through comprehensive statistical analysis, we identify significant differences in bias expression patterns and intra-domain bias correlations across these domains. By utilizing our understanding of the correlations among various bias dimensions, we lay the groundwork for creating advanced systems capable of detecting multiple biases simultaneously. Overall, our dataset advances the field of media bias identification, contributing to the development of tools that promote fairer media consumption. The comprehensive awareness of existing media bias fosters more ethical journalism, promotes cultural sensitivity, and supports a more informed and equitable public discourse.
The common layer-by-layer deposition of regular, 3-axis 3D printing simplifies both the fabrication process and the 3D printer's mechanical design. However, the resulting 3D printed objects have some unfavourable characteristics including visible layers, uneven structural strength and support material. To overcome these, researchers have employed robotic arms and multi-axis CNCs to deposit materials in conformal layers. Conformal deposition improves the quality of the 3D printed parts through support-less printing and curved layer deposition. However, such multi-axis 3D printing is inaccessible to many individuals due to high costs and technical complexities. Furthermore, the limited GUI support for conformal slicers creates an additional barrier for users. To open multi-axis 3D printing up to more makers and researchers, we present a cheap and accessible way to upgrade a regular 3D printer to 5 axes. We have also developed a GUI-based conformal slicer, integrated within a popular CAD package. Together, these deliver an accessible workflow for designing, simulating and creating conformally-printed 3D models.
Kedar Karpe, Avinash Sinha, Shreyas Raorane
et al.
This paper presents a distributed multi-robot printing method which utilizes an optimization approach to decompose and allocate a printing task to a group of mobile robots. The motivation for this problem is to minimize the printing time of the robots by using an appropriate task decomposition algorithm. We present one such algorithm which decomposes an image into rasterized geodesic cells before allocating them to the robots for printing. In addition to this, we also present the design of a numerically controlled holonomic robot capable of spraying ink on smooth surfaces. Further, we use this robot to experimentally verify the results of this paper.
Levi C. Felix, Rushikesh S. Ambekar, Cristiano F. Woellner
et al.
In this work, We combined fully atomistic molecular dynamics and finite elements simulations with mechanical testings to investigate the mechanical behavior of atomic and 3D-printed models of pentadiamond. Pentadiamond is a recently proposed new carbon allotrope, which is composed of a covalent network of pentagonal rings. Our results showed that the stress-strain behavior is almost scale-independent. The stress-strain curves of the 3D-printed structures exhibit three characteristic regions. For low-strain values, this first region presents a non-linear behavior close to zero, followed by a well-defined linear behavior. The second regime is a quasi-plastic one and the third one is densification followed by structural failures (fracture). The Young's modulus values decrease with the number of pores. The deformation mechanism is bending-dominated and different from the layer-by-layer deformation mechanism observed for other 3D-printed structures. They exhibit good energy absorption capabilities, with some structures even outperforming kevlar. Interestingly, considering the Ashby chart, 3D-printed pentadiamond lies almost on the ideal stretch and bending-dominated lines, making them promising materials for energy absorption applications.
We propose a real-time image matching framework, which is hybrid in the sense that it uses both hand-crafted features and deep features obtained from a well-tuned deep convolutional network. The matching problem, which we concentrate on, is specific to a certain application, that is, printing design to product photo matching. Printing designs are any kind of template image files, created using a design tool, thus are perfect image signals. However, photographs of a printed product suffer many unwanted effects, such as uncontrolled shooting angle, uncontrolled illumination, occlusions, printing deficiencies in color, camera noise, optic blur, et cetera. For this purpose, we create an image set that includes printing design and corresponding product photo pairs with collaboration of an actual printing facility. Using this image set, we benchmark various hand-crafted and deep features for matching performance and propose a framework in which deep learning is utilized with highest contribution, but without disabling real-time operation using an ordinary desktop computer.