Complex Matter Research Articles

Building a .NET and AI-Powered Collaborative Platform to Strengthen Inter-Entity Relationships and Foster US Economic Growth

In this study, we take stock of how AI powered collaborative platforms, utilizing .NET technologies can be integrated to handle several critical inter-entity collaboration problems and their potential in boosting economic growth of US. Increasingly, demand in business, finance and government organizations is mounting on efficient communication and data sharing, and AI and .NET frameworks are offering strong solutions at hand. In particular, the research shows that these technologies can enhance collaboration in terms of scalability, system reliability, data security and processing of large volumes of real time data. For organizations, this implementation of AI driven tools such as predictive analytics, machine learning and real time monitoring can be used to make better decisions, boost productivity and build better inter organizational relationships. The challenge of integrating AI and .NET frameworks is evident though they have the potential. Systems are not compatible, infrastructure for legacy applications is a limitation, and it is a complex matter to make sure real time data can be exchanged between dissimilar platforms. Secondly, data privacy and security risks, and scalability problems in large—scale environment are critical areas of concern. This study looks in detail at how these challenges are being tackled, and what further refinements are required to enhance the performance and reliability of collaborative platforms. The results of this research provide important implications for business, policy makers and financial institutions wanting to develop economies by using AI and .NET technologies. In addition, the paper highlights research gaps and emerging issues related to AI powered collaboration, which may drive future innovation, technological development and policy reforms. Finally, the research hopes to guide the creation of more efficient, scalable, and secure collaborative platforms that can support sustainable U.S. economy growth.

Экологические особенности восстановления нарушенных земель приполярья при использовании растительных сообществ в Тюменской области

This paper provided research on the restoration of disturbed lands in the circumpolar area using plant communities in the Tyumen Region. The opening up and development of the circumpolar and polar zones of the Tyumen Region has been carried out for 60 years. Construction is underway and dozens of cities, hundreds of villages, many industrial facilities have been built, thousands of kilometers of pipelines have been laid. As a result of these constructions, the vegetation of the tundra and forest-tundra was destroyed over vast areas, and the bottom of the ancient ocean was opened. Work to restore the soil and vegetation cover of the lands of the Far North, carrying out biological reclamation, is a new and rather complex matter. The goal of our research was to develop a technology for biological land reclamation using perennial grasses, peat and fertilizers for given conditions. Work to restore disturbed lands was carried out in the permafrost zone of the subpolar and polar zones of the Tyumen Region. The natural and climatic conditions of the territory are characterized by a long eight-month winter with little snow and a short summer with cold winds, mainly from the north. Experimental tests on biological land reclamation were carried out near the city of Novy Urengoy, subpolar zone, in a quarry adjacent to gas processing complex № 6. According to observation data over three years of research, at a peat application rate of 1.0 thousand m3/ha, the yield in the control variant was 17.1 c/ha. With a minimum dose of flour of 2 t/ha, the dry matter yield reached 22.9 c/ha. When the dose of dolomite flour was increased to 4–8 t/ha, the yield of dry mass of perennial grasses was 23.4–23.7 c/ha. These experiments need to be continued.

3D printing and artificial intelligence tools for droplet microfluidics: Advances in the generation and analysis of emulsions

Droplet microfluidics has emerged as highly relevant technology in diverse fields such as nanomaterials synthesis, photonics, drug delivery, regenerative medicine, food science, cosmetics, and agriculture. While significant progress has been made in understanding the fundamental mechanisms underlying droplet generation in microchannels and in fabricating devices to produce droplets with varied functionality and high throughput, challenges persist along two important directions. On one side, the generalization of numerical results obtained by computational fluid dynamics would be important to deepen the comprehension of complex physical phenomena in droplet microfluidics, as well as the capability of predicting the device behavior. Conversely, truly three-dimensional architectures would enhance microfluidic platforms in terms of tailoring and enhancing droplet and flow properties. Recent advancements in artificial intelligence (AI) and additive manufacturing (AM) promise unequaled opportunities for simulating fluid behavior, precisely tracking individual droplets, and exploring innovative device designs. This review provides a comprehensive overview of recent progress in applying AI and AM to droplet microfluidics. The basic physical properties of multiphase flows and mechanisms for droplet production are discussed, and the current fabrication methods of related devices are introduced, together with their applications. Delving into the use of AI and AM technologies in droplet microfluidics, topics covered include AI-assisted simulations of droplet behavior, real-time tracking of droplets within microfluidic systems, and AM-fabrication of three-dimensional systems. The synergistic combination of AI and AM is expected to deepen the understanding of complex fluid dynamics and active matter behavior, expediting the transition toward fully digital microfluidic systems.

Living through extended liminality: Reintegration experiences of génocidaire ex-prisoners in Rwanda

In Rwanda, following the 1994 Genocide against the Tutsi, meting out justice on suspected génocidaires has resulted in the need to reintegrate an unprecedent number of ex-prisoners, a process that continues even now, three decades later. Doing so in a society that still bears scars of this genocide, but which is also experiencing drastic social transformation, is a complex matter. Qualitative research carried out in the framework of a community-based psychosocial support program, implemented in ten, mostly rural, districts of Rwanda, aimed to study lived experiences of ex-prisoners going through the reintegration process. Twenty-seven focus group discussions and twenty-five interviews were conducted with ex-prisoners and people living close to them. The research was executed between June 2021 and June 2022. Findings revealed factors, both isolated and intersecting, hindering the reintegration process and consequently keeping ex-prisoners in liminality after imprisonment. These factors include advanced age, bodily and mental frailties, family infightings, land scarcity, and social repercussions of being a génocidaire. There are also ex-prisoners who manage to enter the post-liminal phase after being released due to psychosocial support initiatives or people's empowerment-oriented policies, laws, and programs. This article leaves room for further investigations, especially regarding the sustainability of ex-prisoners' reintegration initiatives.

Shared Decision-Making on Tobacco Smoking by Older Adults Living in Residential Care Facilities: Care Professionals' Perspectives.

Older adults with physical or cognitive disabilities may need to move to residential care facilities (RCFs). Some older adults smoke tobacco and become dependent on their care professionals to continue smoking. Care professionals need to balance an individual resident's quality of life and well-being with the health and safety of all residents and staff. Shared decision-making (SDM) could support care professionals in these dilemmas. This study assesses multiple factors that could affect care professionals' behavior and degree of SDM regarding residents' tobacco use. We conducted quantitative cross-sectional research. We included care professionals working in psychogeriatric and somatic units in Dutch RCFs. Data were collected with an online or hard copy survey and analyzed with t-tests and regression analyses using SPSS. Care professionals' positive attitudes toward residents' tobacco use are significantly associated with a lower degree of SDM concerning this use and enabling residents to smoke more often. The degree of SDM regarding residents' tobacco use is significantly positively associated with limiting residents' tobacco use and the degree of person-centered care (PCC). Care professionals working in somatic units report a significantly higher degree of SDM regarding residents' tobacco use compared with those working in psychogeriatric units. Residents' wish to smoke tobacco is a complex matter within RCFs. Care professionals' attitudes cause inconsistencies in their behavior and the degree of SDM. Moreover, care professionals tend to use SDM more often when they need to limit residents' use and cannot fulfill residents' unhealthy habits, such as smoking tobacco. SDM could support care professionals to deal with dilemmas regarding residents' tobacco use by including residents in decisions, regardless of the outcome. However, multiple factors affect care professionals' behavior and the degree of SDM. Especially, their attitudes need to be addressed. SDM is further complicated by national acts and organizational policies.

A matter of complexity? The role of the dorsal posterior parietal cortex in processing changes in spatial information across time.

The posterior parietal cortex (PPC) is an associative neocortical region that integrates multiple streams of information and is implicated in spatial cognition and decision making. In some cases, however, the PPC is not required for these functions. One possibility is that the PPC is recruited when spatial complexity is high. Yet, few studies of PPC function have explicitly manipulated environmental complexity, complexity of spatial changes, or the temporal structure of spatial tasks. To examine whether task complexity recruits PPC function, we tested rats with neurotoxic damage to the dorsal PPC on a series of tasks varying in spatial and temporal complexity. Recognition memory was first assessed in standard exploration tasks, including object recognition, object location, and object in place, as well as a more complex object task in which spatial changes occurred across multiple delays. Spatial navigation was assessed in the circular hole board maze (Barnes maze), and temporal processing was assessed in a temporal order task. PPC damage spared performance on standard recognition memory tasks but caused deficits on tasks involving changes in object configuration or multiple changes across time. PPC damage spared acquisition on the Barnes maze but impaired retention and decreased efficiency of search strategies. PPC damage did not impact temporal order memory. Overall, these results suggest that the PPC is necessary when spatial complexity of the task increases attentional and long-term memory demands. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

Executive functioning challenges of adolescents born extremely and very preterm.

Children born very preterm (VPT; <32 weeks) are at increased risk of executive functioning (EF) difficulties. But less is known about the nature and extent of these executive difficulties during late adolescence, particularly across multiple EF domains and in response to varying degrees of executive demand. Using data from a prospective longitudinal study, this paper describes the EF profiles of 92 VPT and 68 full-term (FT) adolescents at age 17 years. Relations between gestational age (GA) and later EF performance, in addition to neonatal predictors, were examined. VPT-born adolescents performed less well than FT adolescents across the domains of working memory, planning, and cognitive flexibility, with the largest differences observed for those born <28 weeks GA (effect sizes -0.6 to -1.0 SD), and when task demands were high. The effects of GA on EF outcome were fully mediated by neonatal medical complexity (b = 0.169, t = -1.73) and term equivalent white matter abnormalities (b = 0.107, t = -3.33). Findings support the need for long-term cognitive support for individuals born very preterm, particularly those exposed to high levels of medical and neurological risk, with these factors largely explaining associations between GA and EF outcome.

Politics of Energy Transitions in South Sudan: Who is Fooling Who?

One of the critical themes in oil and gas industry is energy transition from fossil fuel to renewables. While energy transition is importance for any society progress, it has been politicized. The politics is about the genesis and speed of transitions. While African countries wanted to transit to renewables at their phases given that they don’t emit substantive emissions, Western countries wanted every country to transit fully to renewables by 2050. Yet, the Western countries are still carrying out exploration for new oilfields in the United Kingdom and Norway. The paper discuses the concept of energy transition, impacts of energy transition on extractive industries development in Africa. The paper in detail discusses economic impacts, social impacts as well as regulatory framework impacts. It examines South Sudan energy transition by looking at the obstacles as well as solutions to transition to renewables. While the study methodology embraces qualitative research design as well as case study of South Sudan, energy transition has remained as a complex matter where the Western world is fooling the developing world. Although energy transition is imperative, the study concludes that it must be just, progressive and free from coercion. Future research is hereby recommended to the stakeholders in oil and gas industry and particularly, those that have been associated with energy transition to adopt energy mix.

Cortical complexity alterations in motor subtypes of Parkinson's disease: A surface-based morphometry analysis of fractal dimension.

Based on motor symptoms, Parkinson's disease (PD) can be classified into tremor dominant (TD) and postural instability gait difficulty (PIGD) subtypes. Few studies have examined cortical complexity differences in PD motor subtypes. This study aimed to investigate differences in cortical complexity and grey matter volume (GMV) between TD and PIGD. We enrolled 36 TD patients, 27 PIGD patients and 66 healthy controls (HC) from the PPMI (Parkinson's Progression Markers Initiative) database. Voxel-based morphometry (VBM) and surface-based morphometry (SBM) were utilized to assess differences in GMV, cortical thickness and cortical complexity. The structural MRI data of participants was analysed using CAT12/SPM12 (p < 0.05, FDR corrected). Additionally, correlations between clinical data and structural changes were examined (p < 0.05, Holm-Bonferroni corrected). In comparison to both HC and TD groups, PIGD patients exhibited a significant fractal dimension (FD) decrease in many cortical regions. A significant negative correlation between age and FD was observed in the left insula for the PIGD patients and in the bilateral insula for the TD patients. However, no significant differences were found in GMV, cortical thickness or other complexity indices. Altered FD in the bilateral insula indicates that postural instability and gait disturbances may result from a failure to integrate information from various structures, whereas parkinsonian rest tremor is not associated with this integration. Also, widespread decreases in cortical FD demonstrate that FD is more sensitive than other complexity measures and can serve as a novel biomarker for identifying subtle changes in cortical morphology in the PIGD subtype.

Manuscript for: Journal of Environmental Chemical Engineering New insights into the influence of ultrafiltration pretreatment on reverse osmosis membrane fouling during urban sewage reclamation: Interaction between extracellular polymeric substances and inorganic foulants

Ultrafiltration (UF) has been frequently employed as pretreatment to mitigate reverse osmosis (RO) membrane fouling. The organic and inorganic substances outflowing from UF pretreatment collectively determine the subsequent RO membrane fouling behavior. However, most of the previous studies were focused on single organic compounds as well as CaSO4 scaling, yet complex organic matter such as extracellular polymeric substances (EPS) and various inorganic scaling (i.e. CaCO3, Ca3(PO4)2) coexisted during urban sewage reclamation. In this study, the impact of UF pretreatment on RO membrane fouling behavior, especially the interaction between EPS and CaCO3/Ca3(PO4)2 scaling, were systematically investigated. Results showed that the presence of UF significantly reduced the normalized flux decline (9.3% vs. 14.3%) and enhanced cleaning recovery efficiency (84.6% vs. 51.6%) of RO membrane, but increased scattered crystals (CaCO3 and Ca3(PO4)2) formation on RO membrane surface. Further investigation showed that the binding energy of the Ca2p1/2 and Ca2p3/2 peaks on fouled RO membrane exhibited a shift towards lower energy, which indicated a weak complexation between EPS and Ca2+, thereby increasing inorganic scaling and confirming the two-sides role of EPS retained by UF in RO membrane fouling. Moreover, static experiments indicated that EPS inhibited CaCO3 scaling rather than Ca3(PO4)2 scaling with the inhibition rates of 7.3% and 0.7%, respectively. To the best of our knowledge, it is the first to reveal the different effect of EPS on CaCO3 and Ca3(PO4)2 scaling. The results may provide a new insight into the effect of UF pretreatment on RO membrane fouling during urban sewage reclamation process.

Symmetry of the face – Review of a complex matter

Symmetry of the face – Review of a complex matter

Plateau Pika Disturbance Changes Soil Bacterial Functions and Exoenzyme Abundance to Modulate the C Cycle Pathway in Alpine Grasslands.

Plateau pika (Ochotona curzoniae) is crucial to soil organic carbon (SOC) storage in the Qinghai-Tibetan plateau (QTP), but its role in bacterial SOC metabolisms across different degraded alpine grasslands remains unclear. In this study, we investigated the soil physicochemical properties and the composition and function of the bacterial communities in control and pika-disturbed grasslands experiencing different degradation levels (undegraded, UDM; lightly, LDM; moderately, MDM and severely, SDM). The results demonstrate that (i) the primary bacterial phyla include Proteobacteria, Acidobacteriota, Actinobacteriota, Bacteroidota and Verrucomicrobiota. Soil physicochemical properties significantly impact the composition of the bacterial communities and determine the influence of pika disturbance. Pika disturbance increases bacterial OTUs by 7.5% in LDP (p > 0.05) and by 50.5% in MDP (p < 0.05), while decreases OTUs by 21.4% in SDP (p < 0.05). (ii) Pika disturbance downregulates the exoenzyme abundance associated with simple and complex organic matter decomposition by 9.5% and 13.9% in LDP, and 29.4% and 26.3% in MDP (p < 0.05), while upregulates these exoenzymes by 23.6% and 37.9% in SDP (p < 0.05). These changes correspond to the increase in TC and SOC in LDP and MDP but declines in SDP. (iii) Plateau pika disturbance can enhance SOC accumulation through upregulating the C cycle pathway of ethanol production in LDP and MDP. However, it upregulates the pathway of pyruvate to CO2 conversion in SDP, leading to negative influence on SOC storage.

Microbial trait multifunctionality drives soil organic matter formation potential

Soil microbes are a major source of organic residues that accumulate as soil organic matter, the largest terrestrial reservoir of carbon on Earth. As such, there is growing interest in determining the microbial traits that drive soil organic matter formation and stabilization; however, whether certain microbial traits consistently predict soil organic matter accumulation across different functional pools (e.g., total vs. stable soil organic matter) is unresolved. To address these uncertainties, we incubated individual species of fungi in soil organic matter-free model soils, allowing us to directly relate the physiological, morphological, and biochemical traits of fungi to their soil organic matter formation potentials. We find that the formation of different soil organic matter functional pools is associated with distinct fungal traits, and that ‘multifunctional’ species with intermediate investment across this key grouping of traits (namely, carbon use efficiency, growth rate, turnover rate, and biomass protein and phenol contents) promote soil organic matter formation, functional complexity, and stability. Our results highlight the limitations of categorical trait-based frameworks that describe binary trade-offs between microbial traits, instead emphasizing the importance of synergies among microbial traits for the formation of functionally complex soil organic matter.

Change and Detection of Emotions Expressed on People’s Faces in Photos

Human emotions are an element of attention in various areas of interest such as psychology, marketing, medicine, and public safety. Correctly detecting human emotions is a complex matter. The more complex and visually similar emotions are, the more difficult they become to distinguish. Making visual modifications to the faces of people in photos in a way that changes the perceived emotion while preserving the characteristic features of the original face is one of the areas of research in deepfake technologies. The aim of this article is to showcase the outcomes of computer simulation experiments that utilize artificial intelligence algorithms to change the emotions on people’s faces. In order to detect and change emotions, deep neural networks discussed further in this article were used.

A comparative study on the use of spatiotemporal maps for teaching data visualization in a hybrid learning context

ABSTRACT Data visualization is a complex matter and so is teaching it in the context of engineering and data science. Even more challenging is teaching in a midst of once in a century pandemic. In this paper, we show the results of a workshop conducted with second-year students on a university degree in data science, which took place in the context of pandemic restrictions in a hybrid learning environment. About half of the students were in the classroom and the other half at home. They learned to use STMaps, a tool developed in the scope of the SILKNOW project. We transferred research outcomes to the classroom; similarly, the results of evaluating the tool were transferred to the project. But more importantly, we found insights that the learning process of students that were online was not the same quality as of those that were physically in the classroom. While both groups performed well in terms of correctly fulfilling the tasks proposed during the workshop, the students at home were less motivated and perceived the tasks more cumbersome to achieve. From a research perspective, this activity was perceived as very useful, and similar activities are being planned for each academic year.

The Role of Stewards of Trust in Facilitating Trust in Science: A Multistakeholder View

AbstractTrust in science post-Covid appears to be a complex matter. On the one hand, the COVID-19 pandemic added value to the epistemic trustworthiness of scientific opinion and its potential to drive evidence-based policies, while it also spurred scientific distrust and societal polarization (e.g., vaccines), especially on social media. In this work we sought to understand the ways in which trust in science might be bolstered by adopting a multistakeholder perspective. This objective was achieved by considering stakeholders’ views on (a) how perceived key actors affect trust in science, and (b) what proposed actions can be taken by each actor identified. Data were collected using 16 focus groups and 10 individual interviews across different European contexts with general public (n = 66), journalists (n = 23) and scientists (n = 35), and were analysed using thematic analysis. Regarding how perceived key actors affect trust in science, participants viewed policymakers, media, scientific and social media actors as occupying a dual function (facilitators and hinderers of trust in science), and pointed to the value of multi-actor collaboration. Regarding what actions should be taken for enhancing trust in science, participants indicated the value of enhancing understanding of scientific integrity and practices, through science literacy and science communication, and also pointed to social media platform regulation. Implications stemming from the data are discussed, considering how multiple identified stewards of trust can contribute to an ecosystem of trust.

Is It True That More Than Half of Web Contents Are in English? Not If Multilingualism Is Paid Due Attention!

The belief that English is and will remain largely dominant as the first language of the Internet in terms of content and is the natural lingua franca in cyberspace plays against the mobilization of human and funding resources to incorporate minority languages. We sustain that this belief stands on biased data and that multilingualism is more and more the nature of the Internet and translation its lingua franca. We challenge the validity of a source widely used, since 2011, to state that English represents a steady percentage of web contents over 50%. This business source, W3Techs, is well-famed and considered reliable for its surveys on web technologies, exploring a large sample of the Web. However, languages differ from other web technologies, in the fact than more than one language could be used on a website. Not taking into account the multilingual nature of the Web is a serious bias that leads to major errors. The study of the rate of multilingualism of the sample of websites used by W3Techs concludes that the percentage of English contents on the Web is within a 20%–30% range, a value coherent with the results from three referenced alternative methods. We plan for 2025 to create a tool for measurement of languages and rate of multilingualism in a series of websites, with thorough attention to list all the languages used within a website, a complex matter. This tool will be applied to the same sampling and should close definitively this matter.

Polyvinyl fluoride: Predicting polarization in a complex soft matter system

We use first-principle density functional theory (DFT) to predict properties for semicrystalline polyvinyl fluoride (PVF) and compare with polyvinylidiene fluoride. We note that the crystalline regions of PVF are complex in the sense that we lack a complete experimental characterization of the detailed atomic organization. We therefore turn to DFT to predict both the structure and associated materials properties, illustrating a possible work flow for complex soft-matter modeling. We rely on the nonempirical consistent-exchange van der Waals density functional version [K. Berland and P. Hyldgaard, ] and identify plausible ground-state and excited-state motifs. From there we predict the elastic response of the crystalline motifs, and an upper limit estimate of the PVF polarization at room temperature. Published by the American Physical Society 2024

Light, Switch, Action! The Influence of Geometrical Photoisomerization in an Adaptive Self-Assembled System.

The ubiquitous ability of natural dynamic nanostructures to adapt to environmental changes is a highly desirable property for chemical systems, particularly in the development of complex matter, molecular machines, and life-like materials. Designing such systems is challenging due to the generation of complex mixtures with responses that are difficult to predict, characterize, and diversify. Here, we navigate between self-assembled architectures using light by operating an intrinsic photoswitchable building block that governs the state of the system. When complementary units are present, the photoswitch determines the predominant architecture, reversibly adapting between the cage and macrocycles, including (otherwise inaccessible) higher-energy assemblies. Our study showcases this concept with seven different transformations, offering an unprecedented degree of control, diversification, and adaptation by self-selecting complementary units. These findings could enable applications of on-demand dissipative macrocycles based on dynamic bonds. We also envision different transient nanostructures, e.g., reticular and polymeric materials, being explored by fine-tuning the nature of the complementary unit.

Into the Open: Shared Stories of Open Educational Practices in Teacher Education

Navigating through the Faculty of Education as a teacher educator in Canada is complex and complicated. Research literature calls for an intentional focus on media and digital literacies, and technological competencies, in teacher education. Program directions are confounded by technological trends emerging in kindergarten to grade twelve education and higher education. This post-intentional phenomenological research study examined moments, materials, and insights from the stories shared by participants as they revealed media and digital skills, fluencies, competencies, and literacies in their open educational practice. This research provides insights into how teacher educators seize opportunities to work through complex matters while applying technology resources. It is becoming ever more important to share expertise as practitioners, researchers, and theorists in the field of education by making explicit what is often tacit and unspoken, and when sharing knowledge, reflections, and actions. By actively thinking-out-loud through blogs, social media, and open scholarly publications, educators can openly share details of what, how, and why they do what they do. Research findings reveal the importance of media and digital literacies in the dimensions of communication, creativity, connections, and criticality within an open educational practice as a teacher educator.