Efficient Information Research Articles

Holistic Approach to Niche Formation: A Case on Transition to Nearly Zero-Energy Buildings in Türkiye

The long-term challenges of climate change are becoming increasingly evident. Considering the ever-increasing need for energy in parallel with population growth and the impact of greenhouse gases, the built environment is among the issues that should be addressed as a priority. As international agreements, the EU, and national legislation become institutionalized, the need to decarbonize the built environment increases. For this reason, there is a need for an understanding that enables the transition to a more sustainable society. In line with this understanding, a transition to zero-energy buildings is required. In this article, the evaluation framework is created by combining the Transition Management (TM) approach, which is a framework developed to understand long-term changes in culture, structure, and practices for sustainable development solutions, and the Strategic Niche Management (SNM) approach, which encourages technological and social change to initiate sustainable innovations at the niche level. Applications regarding energy efficiency and niche formation for the built environment in Türkiye (Gaziantep) were discussed. When the applications and theories are evaluated together, it can be seen that the applications carried out in Gaziantep regarding Nearly Zero Energy Buildings may be starter experiments. However, these projects are insufficient to create a niche, and the developments are progressing very slowly.

Skin Cancer Segmentation using CNN

This groundbreaking research introduces a comprehensive strategy for advancing medical image segmentation, merging two pivotal concepts to significantly enhance both the accuracy and efficiency of the segmentation process. The first component of our approach involves the integration of polar transformations as a preprocessing step applied to the original dataset. This transformative technique is designed to address the challenges associated with segmenting single structures of elliptical shape in medical images, such as organs (e.g., heart and kidneys), skin lesions, polyps, and various abnormalities. By centering the polar transformation on the object's focal point, a reduction in dimensionality is achieved, coupled with a distinct separation of segmentation and localization tasks. Two distinct methodologies for selecting an optimal polar origin are proposed: one involving estimation through a segmentation neural network trained on non-polar images, and the other employing a dedicated neural network trained to pre dict the optimal origin. The second key element of our approach is around the integration of the DoubleU-Net architecture, a powerful encoder-decoder model specifically designed for the task of semantic image segmentation. DoubleU- Net is a group of two U-Net architectures, each with a specific purpose. The initial U-Net is pre-trained on VGG-19 as the encoder and uses features learned from ImageNet to provide efficient information transfer. In order to store more semantic information and content, a second U-Net was added to the base to enhance the capabilities of the network. Join Atrous Spatial Pyramid Pooling (ASPP) to develop network data extraction content. The combination of DoubleU-Net architecture and joint transformation as a step forward shows good segmentation performance in different clinical tasks, including liver segmentation, polyp detection vision, skin segmentation, and epicardial fat tissue segmentation. It shows that various medical projects, including various diagnostic methods such as colonoscopy, dermoscopy, microscopy, have a positive impact on the plan. More importantly, the method performs well in difficult cases, such as the segmentation of small and flat polyps in CVC-ClinicDB and the 2015 subset of the MICCAI Automated Polyp Detection dataset. The results demonstrate the accuracy and generality of the combination, making it the best way to evaluate medical images in context; Our study has revealed a new method of skin cancer diagnosis that combines the power of deep learning with innovation. Advanced technology. The combination of dual U-Net architecture and polar coordinate transformation not only improves the accuracy of classification of lesions but also improves the robustness of the model to changes in image features. This study contributes to the development of computer-aided diagnostic systems for early diagnosis. Experimental results show that our method provides good accuracy, sensitivity, and specificity in detecting malignant and benign tumors. Additionally, we are conducting ablation studies to determine the contribution of each presentation and treatment of skin cancer to ultimately benefit patients and determine these benefits. We also apply the transformation of the joint as the first step to improve the discrimination ability of the model. This mechanical change effectively reduces the impact caused by changes in wound size, shape, and direction by displaying the original image of the polar system. By standardizing the representation of skin diseases, polar transformation improves the model's ability to generalize across different data sets and improves overall performance.

Is there a time-varying nexus between stock market liquidity and informational efficiency? – A cross-regional evidence

Is there a time-varying nexus between stock market liquidity and informational efficiency? – A cross-regional evidence

Two Distinct Classes of Quiescent Galaxies at Cosmic Noon Revealed by JWST PRIMER and UNCOVER

We present a measurement of the low-mass quiescent size–mass relation at cosmic noon (1 < z < 3) from the JWST PRIMER and UNCOVER treasury surveys, which highlights two distinct classes of quiescent galaxies. While the massive population is well studied at these redshifts, the low-mass end has been previously underexplored due to a lack of observing facilities with sufficient sensitivity and spatial resolution. We select a conservative sample of low-mass quiescent galaxy candidates using rest-frame UVJ colors and specific star formation rate criteria and measure galaxy morphology in both rest-frame UV/optical wavelengths (F150W) and rest-frame near-infrared (F444W). We confirm an unambiguous flattening of the low-mass quiescent size–mass relation, which results from the separation of the quiescent galaxy sample into two distinct populations at log(M⋆/M⊙)∼10.3 : low-mass quiescent galaxies that are notably younger and have disky structures, and massive galaxies consistent with spheroidal morphologies and older median stellar ages. These separate populations imply mass quenching dominates at the massive end while other mechanisms, such as environmental or feedback-driven quenching, form the low-mass end. This stellar mass-dependent slope of the quiescent size–mass relation could also indicate a shift from size growth due to star formation (low masses) to growth via mergers (massive galaxies). The transition mass between these two populations also corresponds with other dramatic changes and characteristic masses in several galaxy evolution scaling relations (e.g., star formation efficiency, dust obscuration, and stellar-to-halo mass ratios), further highlighting the stark dichotomy between low-mass and massive galaxy formation.

The Interplay between the Initial Mass Function and Star Formation Efficiency through Radiative Feedback at High Stellar Surface Densities

The observed rest-UV luminosity function at cosmic dawn (z ∼ 8–14) measured by JWST revealed an excess of UV-luminous galaxies relative to many prelaunch theoretical predictions. A high star formation efficiency (SFE) and a top-heavy initial mass function (IMF) are among the mechanisms proposed for explaining this excess. Although a top-heavy IMF has been proposed for its ability to increase the light-to-mass ratio (ΨUV), the resulting enhanced radiative pressure from young stars could decrease the SFE, potentially driving galaxy luminosities back down. In this Letter, we use idealized radiation hydrodynamic simulations of star cluster formation to explore the effects of a top-heavy IMF on the SFE of clouds typical of the high-pressure conditions found at these redshifts. We find that the SFE in star clusters with solar-neighborhood-like dust abundance decreases with increasingly top-heavy IMFs—by ∼20% for an increase of a factor of 4 in ΨUV and by 50% for a factor of ∼10 in ΨUV. However, we find that an expected decrease in the dust-to-gas ratio (∼0.01 × solar) at these redshifts can completely compensate for the enhanced light output. This leads to a (cloud-scale; ∼10 pc) SFE that is ≳70% even for a factor of 10 increase in ΨUV, implying that highly efficient star formation is unavoidable for high surface density and low-metallicity conditions. Our results suggest that a top-heavy IMF, if present, likely coexists with efficient star formation in these galaxies.

Origin of the light-induced spin currents in heavy metal/magnetic insulator bilayers.

Light-induced spin currents with the faster response is essential for the more efficient information transmission and processing. Herein, we systematically explore the effect of light illumination energy and direction on the light-induced spin currents in the W/Y3Fe5O12 heterojunction. Light-induced spin currents can be clearly categorized into two types. One is excited by the low light intensity, which mainly involves the photo-generated spin current from spin photovoltaic effect. The other is caused by the high light intensity, which is the light-thermally induced spin current and mainly excited by spin Seebeck effect. Under low light-intensity illumination, light-thermally induced temperature gradient is very small so that spin Seebeck effect can be neglected. Furthermore, the mechanism on spin photovoltaic effect is fully elucidated, where the photo-generated spin current in Y3Fe5O12 mainly originates from the process of spin precession induced by photons. These findings provide some deep insights into the origin of light-induced spin current.

CXCR3-Independent Role of CXCL10 in Alveolar Epithelial Repair.

The alveolar Type II epithelial (AEC2) cells act as stem cells in the lung for alveolar epithelial maintenance and repair. Chemokine CXCL10 is expressed in injured tissues, modulating multiple cellular functions. AEC2s, previously reported to release chemokines to recruit leukocytes, were found in our study to secrete CXCL10 after bleomycin injury. We found that Sftpc-Cxcl10 transgenic mice were protected from bleomycin injury. The transgenic mice showed an increase in the AEC2 population in the lung by flow cytometry analysis. Both endogenous and exogenous CXCL10 promoted the colony formation efficiency of AEC2s in a 3D organoid growth assay. We identified that the regenerative effect of CXCL10 was CXCR3 independent using Cxcr3-deficient mice, but it was related to the TrkA pathway. Binding experiments showed that CXCL10 interacted with TrkA directly and reversibly. This study demonstrates a previously unidentified AEC2 autocrine signaling of CXCL10 to promote their regeneration and proliferation, probably involving a CXCR3-independent TrkA pathway.

Structured and disordered regions of Ataxin-2 contribute differently to the specificity and efficiency of mRNP granule formation.

Ataxin-2 (ATXN2) is a gene implicated in spinocerebellar ataxia type II (SCA2), amyotrophic lateral sclerosis (ALS) and Parkinsonism. The encoded protein is a therapeutic target for ALS and related conditions. ATXN2 (or Atx2 in insects) can function in translational activation, translational repression, mRNA stability and in the assembly of mRNP-granules, a process mediated by intrinsically disordered regions (IDRs). Previous work has shown that the LSm (Like-Sm) domain of Atx2, which can help stimulate mRNA translation, antagonizes mRNP-granule assembly. Here we advance these findings through a series of experiments on Drosophila and human Ataxin-2 proteins. Results of Targets of RNA Binding Proteins Identified by Editing (TRIBE), co-localization and immunoprecipitation experiments indicate that a polyA-binding protein (PABP) interacting, PAM2 motif of Ataxin-2 may be a major determinant of the mRNA and protein content of Ataxin-2 mRNP granules. Transgenic Experiments with transgenic Drosophila indicate that while the Atx2-LSm domain may protect against neurodegeneration, structured PAM2- and unstructured IDR- interactions both support Atx2-induced cytotoxicity. Taken together, the data lead to a proposal for how Ataxin-2 interactions are remodelled during translational control and how structured and non-structured interactions contribute differently to the specificity and efficiency of RNP granule condensation as well as to neurodegeneration.

Information management and optimization methods in architectural construction drawings: A case study of the "Coconut forest settlement" in Hainan

This paper investigates information management and optimization methods within architectural construction drawings, using the Coconut Forest Settlement project in Hainan as a case study. Five key categories of methods are explored: clarification, structuring, standardization, precision, and lightweight. These methods address issues such as the lack of case-based analysis, the need for better information management, and the reduction of information redundancy. By classifying and discussing these strategies, the study highlights the enduring relevance of construction drawings in the digital age. Furthermore, it envisions the transferability of these methods to different contexts due to their emphasis on logical commonalities and the ever-present need for efficient information management. Practical examples from other fields, such as Revit, Rhino, and Grasshopper, are cited to demonstrate the potential applicability of these methods beyond traditional construction drawings. This paper contributes to the enhancement of information management in architectural design, fostering innovation and improved efficiency across various applications.

The neural compensation phenomenon in schizophrenia with mild attention deficits during working memory task

BackgroundWorking memory (WM) and attention are essential cognitive processes, and their interplay is critical for efficient information processing. Schizophrenia often exhibits deficits in both WM and attention, contributing to function impairments. This study aims to investigate the neural mechanisms underlying the relationship between WM impairments and attention deficits in schizophrenia. MethodsWe assessed the functional-MRI scans of the 184 schizophrenias with different attention deficits (mild=133; severe=51) and 146 controls during an N-back WM task. We explored their whole-brain functional connectome profile by adopting the voxel-wise degree centrality (DC). Linear analysis was conducted to explore the associations among attention deficit severity, altered DC, and WM performance in patients. ResultsWe observed that all patients showed decreased DC in the pre-supplementary area (pre-SMA), and posterior cerebellum compared to the controls, and schizophrenia patients with mild attention deficits showed decreased DC in the supramarginal gyrus, insula, and precuneus compared with the other 2 groups. DC values of the detected brain regions displayed U-shaped or inverted U-shaped curves, rather than a linear pattern, in response to increasing attention deficits. The linear analysis indicated that altered DC of the pre-SMA can modulate the relationship between attention deficits and WM performance. ConclusionThe U-shaped or inverted U-shaped pattern in response to increasing attention deficits may reflect a compensation mechanism in schizophrenia with mild attention deficits. This notion is also supported by the linear analysis that schizophrenia patients with mild attention deficits can improve their WM performance by increasing the DC value of the pre-SMA.

Complete gold extraction and recovery from double refractory gold ores by thiourea after bio-oxidation

Cyanidation, a conventional process to extract gold from gold ores, has been used for over 130 years in industrial mining because of the high efficiency and rate of formation of Au(CN)2− and the high recovery efficiency by adsorption of Au(CN)2− on activated carbon. However, carbonaceous refractory gold ores are not targeted because Au(CN)2− is easily adsorbed on carbonaceous matter in the ores, resulting in high recovery loss. In this study, the flotation concentrates of a carbonaceous refractory gold ores was subjected to biooxidation at 45 °C using a mixed culture containing iron-oxidizing and sulfur-oxidizing bacteria, followed by gold extraction using thiourea under strongly acidic conditions. The gold extraction efficiency reached ∼100% in 12 h without re-adsorption. Finally, the quantitative recovery of the Au(CS(NH2)2)2+ complex was confirmed by adsorption on strongly cationic exchange resin. Biooxidation reduced the amount of Fe-containing metal sulfides, which minimized the decomposition of thiourea, and the Au(CS(NH2)2)2+ complex had a low affinity toward carbonaceous matter, different to Au(CN)2−. Since the process described in this study does not require roasting to remove carbonaceous materials in pretreatment and does not use cyanide for gold extraction, it is environmentally friendly and should be considered for practical applications in carbonaceous gold ore-producing mines.

Analysis of sales demand and production capacity to determine the need for direct labour

This study consists of meeting the sales demand using the existing production capacity in an electronic goods industry and thus determining the amount of direct labor (MOD) necessary to meet the needs of customers. Since obtaining the correct number of operators on a production line is extremely important in the pursuit of productivity and cost reduction. Therefore, using concepts such as takt time, cycle time and line efficiency and other information related to the product or products that will be assembled on a production line, it will be possible to quickly and assertively determine the number of operators that must serve directly the client's demand, thus guaranteeing productive efficiency and the correct application of labor resources using as assumptions the capacity and equipment already existing in the production line. Thus, based on the company's sales projection, it will be possible to determine month by month the number of operators, number of shifts and the appropriate volume to be produced to meet the requested demand.

Efficient information reconciliation for high-dimensional quantum key distribution

The information reconciliation phase in quantum key distribution has significant impact on the range and throughput of any QKD system. We explore this stage for high-dimensional QKD implementations and introduce two novel methods for reconciliation. The methods are based on nonbinary LDPC codes and the Cascade algorithm, respectively, and achieve efficiencies close the Slepian–Wolf bound on q-ary symmetric channels.

Optimizing Urban Mobility: Assessing the Impact of Selangor's Intelligent Transport System (SITs)

This paper addresses Malaysia's public transport system, primarily managed by small operators in its developing state. Efficient transportation management relies on collaborative information sharing. Systems must provide an easy and effective way to manage staff and registered users, including students and community members. Working passengers require efficient route information to minimize delays. Therefore, systems should cater to all users' needs. Registered users, such as students, also require real-time bus updates to avoid long waits and inform the organization of delays via SMS. Implementing and managing these services collectively presents challenges. Mobile technology, including smartphones and laptops, offers a solution through location-based applications for managing transportation with map navigation. The recent mobile technology revolution has intensified competition among developers, resulting in similar yet distinct applications. Modern transit services now offer virtual access to schedules and advanced features like integration with Google Maps and real-time tracking. De-spite benefits, implementing a Smart Transportation Application (STA) with GPS and digital route maps can be daunting and costly for smaller operators.

A comprehensive analysis of the influence of information technology on organizational management characteristics

The paper conducts a thorough investigation and broadens current academic and mainstream literature to deliver a comprehensive evaluation of how information technology (IT) impacts organizational characteristics and outcomes. First, drawing from the literature analysis, we delineate two key advantages of IT in enhancing performance: information efficiencies, which streamline processes, resource allocation along with information synergies, which foster collaborative environments as well as amplify the value derived from data integration and sharing across organizational domains. Following our discussion, we proceed to delineate the fundamental organizational outcomes that stem from the integration of IT, which encapsulate these inherent advantages. Following that, we research into the multifaceted impact of IT on managing the connection between various organizational attributes, including its pivotal role in fostering innovation, streamlining efficiency, facilitating information synergies and promoting effectiveness in interorganizational relationships. In our comprehensive exploration, we thoroughly investigate and analyze the attainment of strategic outcomes, the optimization of organizational efficiency, along with the fostering of innovation in the realm of information technology. Our examination extends beyond the positive aspects, as we delve deeply into the multifaceted landscape of constraints and potential adverse outcomes intricately intertwined with IT usage. This thorough scrutiny allows gaining valuable insights into the challenges that can arise, providing a nuanced understanding of the intricate dynamics involved. Conclude our investigation; we scrutinize various pivotal avenues for future research, ensuring a forward-looking perspective that addresses emerging trends and evolving challenges in the ever-changing landscape of information technology.

ICT in Nursing and Patient Healthcare Management: Scoping Review and Case Studies

Over the past few decades, Information and Communication Technologies (ICT) have revolutionized the fields of nursing and patient healthcare management. This scoping review and the accompanying case studies shed light on the extensive scope and impact of ICT in these critical healthcare domains. The scoping review explores the wide array of ICT tools employed in nursing care and patient healthcare management. These tools encompass electronic health records systems, mobile applications, telemedicine solutions, remote monitoring systems, and more. This article underscores how these technologies have enhanced the efficiency, accuracy, and accessibility of clinical information, contributing to improved patient care. ICT revolution has revitalized nursing care and patient management, improving the quality of care and patient satisfaction. This review and the accompanying case studies emphasize the ongoing potential of ICT in the healthcare sector and call for further research to maximize its benefits.

Building an Efficient Land Information System in Ghana: Insights from Land Governance

Building an Efficient Land Information System in Ghana: Insights from Land Governance

Particle Swarm Optimization-Based Model Abstraction and Explanation Generation for a Recurrent Neural Network

In text classifier models, the complexity of recurrent neural networks (RNNs) is very high because of the vast state space and uncertainty of transitions, which makes the RNN classifier’s explainability insufficient. It is almost impossible to explain the large-scale RNN directly. A feasible method is to generalize the rules undermining it, that is, model abstraction. To deal with the low efficiency and excessive information loss in existing model abstraction for RNNs, this work proposes a PSO (Particle Swarm Optimization)-based model abstraction and explanation generation method for RNNs. Firstly, the k-means clustering is applied to preliminarily partition the RNN decision process state. Secondly, a frequency prefix tree is constructed based on the traces, and a PSO algorithm is designed to implement state merging to address the problem of vast state space. Then, a PFA (probabilistic finite automata) is constructed to explain the RNN structure with preserving the origin RNN information as much as possible. Finally, the quantitative keywords are labeled as an explanation for classification results, which are automatically generated with the abstract model PFA. We demonstrate the feasibility and effectiveness of the proposed method in some cases.

On bursty star formation during cosmological reionization - how does it influence the baryon mass content of dark matter halos?

Abstract The baryon mass content (i.e. stellar and gas mass) of dark matter halos in the early Universe depends on both global factors - e.g. ionizing ultraviolet (UV) radiation background - and local factors - e.g. star formation efficiency and assembly history. We use a lightweight semi-analytical model to investigate how both local and global factors impact the halo baryon mass content at redshifts of z ≥ 5. Our model incorporates a time delay between when stars form and when they produce feedback of 0 ≤ td/Myr ≤ 30, which can drive bursts of star formation, and a mass and redshift dependent UV background, which captures the influence of cosmological reionization on gas accretion onto halos. We use statistically representative halo assembly histories and assume that the cosmological gas accretion rate is proportional to the halo mass accretion rate. Delayed (td&gt;0) feedback leads to oscillations in gas mass with cosmic time, behaviour that cannot be captured with instantaneous feedback (td=0). Highly efficient star formation drives stronger oscillations, while strong feedback impacts when oscillations occur; in contrast, inefficient star formation and weak feedback produce similar long-term behaviour to that observed in instantaneous feedback models. If the delayed feedback timescale is too long, a halo retains its gas reservoir but the feedback suppresses star formation. Our model predicts that lower mass systems (halo masses mh ≤ 107M⊙) at z ≤ 10 should be strongly gas deficient (mg → 0), whereas higher mass systems retain their gas reservoirs because they are sufficiently massive to continue accreting gas through cosmological reionization. Interestingly, in higher mass halos, the median m⋆/(m⋆ + mg) ≃ 0.01 – 0.05, but is a factor of 3-5 smaller when feedback is delayed. Our model does not include seed supermassive black hole feedback, which is necessary to explain massive quenched galaxies in the early Universe.

Do spiral arms enhance star formation efficiency?

Spiral arms, as those of our own Milky Way, are some of the most spectacular features in disc galaxies. It has been argued that star formation should proceed more efficiently in spiral arms as a result of gas compression. Yet, observational studies have so far yielded contradictory results. Here, we examine arm/interarm surface density contrasts at sim 100\,pc resolution in 28 spiral galaxies from the PHANGS survey. We find that the arm AND interarm contrast in stellar mass surface density ($ is very modest, typically a few tens of percent. This is much smaller than the contrasts measured for molecular gas ($ mol $) or star formation rate ($ SFR $) surface density, which typically reach a factor of $ sim 3$. However, $ mol $ and $ SFR $ contrasts show a significant correlation with the enhancement in $ suggesting that the small stellar contrast largely dictates the stronger accumulation of gas and star formation. All these contrasts increase for grand-design spirals compared to multi-armed and flocculent systems (and for galaxies with high stellar mass). The median star formation efficiency (SFE) of the molecular gas is $16$&lt;!PCT!&gt; higher in spiral arms than in interarm regions, with a large scatter, and the contrast increases significantly (median SFE contrast $2.34$) for regions of particularly enhanced stellar contrast ($ contrast $&gt;1.97$). The molecular-to-atomic gas ratio ($ mol atom $) is higher in spiral arms, pointing to a transformation of atomic to molecular gas. As a consequence, the total gas contrast ($ mol atom $) slightly drops compared to $ mol $ (median $4$&lt;!PCT!&gt; lower, working at sim kpc resolution), while the SFE contrast increases when we include atomic gas (median $8$&lt;!PCT!&gt; higher than for $ mol $). The contrasts show important fluctuations with galactocentric radius. We confirm that our results are robust against a number of effects, such as spiral mask width, tracers, resolution, and binning. In conclusion, the boost in the SFE of molecular gas in spiral arms is generally modest or absent, except for locations with exceptionally large stellar contrasts.