bluuebunny/crossref_metadata_2025 huggingface dataset:
Swarm Behavior of Adult-Born Neurons During Migration in a Non-Permissive Environment
Authors: Kaneko Naoko , Ishimaru Taisei
Published: August 2023

Much attention has been provided to autonomous decentralized systems based on swarm intelligence algorithms in robotics because of their resistance to component failure and ability to adapt to new environments. During development, various types of collectively migrating cells contribute to tissue and organ formation and have provided useful models for studying swarm behaviors. In the adult brain under physiological conditions, collective cell migration is almost exclusively observed in the rostral migratory stream, where adult-born new neurons travel long distances in contiguous chain-like formation. After ischemic stroke, some new neurons migrate toward the lesion site. Studies show that the promotion of migration is critical for efficient neuronal rewiring in the post-stroke brain in rodents. The new neurons traverse to injured tissues that are not conducive to migration by forming small chains, clearing a path through glial cells, and interacting with blood vessels. Although processes involved in migratory behavior, including cytoskeletal dynamics, intercellular adhesion, and chain formation, have been separately investigated, the mechanisms underlying neuronal swarm behavior are unclear. Future studies should help further our understanding of swarm intelligence and advance the development of novel strategies for controlling neuronal migration to promote efficient functional repair and rewiring in various pathological conditions.
Honey Bee Waggle Dance as a Model of Swarm Intelligence
Authors: Okada Ryuichi , Ikeno Hidetoshi , Aonuma Hitoshi , Sakura Midori , Ito Etsuro
Published: August 2023

Honey bees are social insects that form colonies (hives), which often consist of more than 10,000 individuals. In a colony, bees allocate jobs (division of labor) and work cooperatively and intelligently to maintain the colony’s activity, such as nursing broods, cleaning, and guarding against enemies. Among worker bees, only forager bees collect food, and success in finding food directly influences colony survival. For more efficient foraging, honey bees share location information pertaining to profitable food sources through specific behavior called “waggle dances.” During such dances, the direction and distance from the hive to the food source are encoded as body movements. Other foragers follow the dancing bees and receive location information. Some of these bees then fly to the advertised location to find the food source. Some of these “recruited bees” subsequently dance to recruit new bees. This process is then repeated. Consequently, many foragers visit the food source, and a colony can rapidly and flexibly collect large amounts of food even in foraging environment that can suddenly change (e.g., flowers disappear or nectar flux increases/decreases). To achieve effective food collection through the waggle dance, the behavior of both the dancers and followers probably contains information for an implementation of “swarm intelligence.” In this review, we introduce the properties of dance behavior at the levels of dancers, followers, and colonies. We found that errors in waggle dance information play an important role in adaptive foraging in dynamically changing environments.
Swarm Search Algorithm Based on Chemotactic Behaviors of Caenorhabditis elegans Nematodes
Authors: Nomoto Seiya , Hattori Yuya , Kurabayashi Daisuke
Published: August 2023

We investigated the chemotactic behaviors of the nematode Caenorhabditis elegans, whose individuals have only 302 neurons but might sense the density of other individuals. As an individual detects areas with high concentration of a target chemical, mimicking their behavior may improve the exploration efficiency of autonomous distributed agents with limited sensing area and no direct communication with others. Inspired by this behavior, we experimentally determined the relationship between the density of individuals and probability of rapid turns to develop a search algorithm. We found a parameter set of “elite” individuals that achieved a high similarity of individual distributions with respect to a chemical gradient. Then, we implemented a motion selection algorithm that reflects the observation results so that an autonomous distributed agent, which has limited sensing range, achieves effective searching in a multi-peak environment. We simulated autonomous agents and applied the parameter sets obtained from elite, inferior, and single individuals. Through verifications using various benchmark potential functions, we concluded that the parameters of the elite group improved the search efficiency.
Group Chase and Escape with Chemotaxis
Authors: Oosawa Chikoo
Published: August 2023

A model is proposed for group chase and escape using chemotactic movements only. In the proposed model, the movement depends on the concentration of the chemical substances released by each agent. Chemotaxis-based interactions propagate slower and later, and exist locally between agents, making groups chase and escape under more uncertain circumstances than in cases where agent distance measurements use electromagnetic waves, such as visible light. Numerical results with the model demonstrate that maintaining a longer distance between the chasers and targets is a better strategy for each group.
Toward Comparative Collective Behavior to Discover Fundamental Mechanisms Underlying Behavior in Human Crowds and Nonhuman Animal Groups
Authors: Murakami Hisashi , Abe Masato S. , Nishiyama Yuta
Published: August 2023

This article provides comparative perspectives on collective behaviors that are widely found throughout the animal kingdom, ranging from insect and crustacea swarms, fish schools, bird flocks, and mammal herds to human crowds. Studies of nonhuman animal and human collective behaviors have progressed almost separately even though they have a similar history. Theoretical studies have investigated the reproduction of collective phenomena from simple inter-individual rules, and subsequent empirical and experimental studies have found diverse and complex collective behaviors that are difficult to explain with classical theoretical models. As a consequence, a wide variety of interaction rules have been proposed. To determine models to be implemented in nature and find fundamental mechanisms of collective behaviors, this paper argues that we should compare collective behaviors among various species while adopting Tinbergen’s four questions regarding mechanism, function, development, and evolution as a methodological basis. As an example of a comparative collective behavior paradigm, we introduce our studies in which a mutual anticipation mechanism inspired by nonhuman animal collective behaviors can be linked to a self-organization function in human collective behaviors. We expect that the study of comparative collective behaviors will expand, the methodology will become more sophisticated, and new perspectives regarding the multitemporal features of collective behaviors will emerge.
Effect of Robotic Pile-Up Mechanism on Cooperative Transportation for Versatile Objects
Authors: Sueoka Yuichiro , Yong Wei Jie , Takebe Naoto , Sugimoto Yasuhiro , Osuka Koichi
Published: August 2023

In recent years, cooperative transportation systems using multiple mobile robots have been studied. The advantage will be to transport objects that cannot be dealt with by a single robot and transport them by using smaller robots. Although cooperative transportation by a group of robots has been studied, the conventional transportation targets are limited to objects whose posture is stable. In this paper, we propose a system in which robots pile up on each other to support an object, aiming at a system for more versatile object transportation, including unstable objects. After deriving the conditions by modeling the support system in object transportation, we verify the transporting performance including the robotic pile-up effect through actual robot experiments.
Experimental Analysis of Shepherding-Type Robot Navigation Utilizing Sound-Obstacle-Interaction
Authors: Tsunoda Yusuke , Nghia Le Trong , Sueoka Yuichiro , Osuka Koichi
Published: August 2023

This study considers a simple robot swarm navigation system based on shepherding in an environment with obstacles. Shepherding is a system in which a small number of control agents (shepherds and sheepdogs) indirectly guide several robots (sheep) by driving them from behind. Previous studies have predominantly focused on verifying proposed controllers based on numerical simulations and navigation experiments in well-prepared environments. However, additional shepherding experiments need to be conducted in environments with obstacles. This study aims to facilitate shepherding-type swarm robot navigation in an environment where a wall obstructs the goal. Usually, a high-end controller design is adopted for the robot to prevent it from getting trapped by obstacles. However, as the environment becomes more complex, the system design may become difficult. In contrast, this study proposes a simple shepherding navigation system based on creating and controlling “fields” to avoid obstacles. This research aims to verify whether the robot can be guided to a goal without obstacle recognition by creating an acoustic field based on the diffraction effects of sound. The proposed method modifies the previous shepherding models for sheep and shepherd robots to make them behave according to the acoustic field gradient. We demonstrate the validity of the proposed system by performing robot navigation for dog and sheep robots.
Generating Collective Behavior of a Multi-Legged Robotic Swarm Using Deep Reinforcement Learning
Authors: Morimoto Daichi , Iwamoto Yukiha , Hiraga Motoaki , Ohkura Kazuhiro
Published: August 2023

This paper presents a method of generating collective behavior of a multi-legged robotic swarm using deep reinforcement learning. Most studies in swarm robotics have used mobile robots driven by wheels. These robots can operate only on relatively flat surfaces. In this study, a multi-legged robotic swarm was employed to generate collective behavior not only on a flat field but also on rough terrain fields. However, designing a controller for a multi-legged robotic swarm becomes a challenging problem because it has a large number of actuators than wheeled-mobile robots. This paper applied deep reinforcement learning to designing a controller. The proximal policy optimization (PPO) algorithm was utilized to train the robot controller. The controller was trained through the task that required robots to walk and form a line. The results of computer simulations showed that the PPO led to the successful design of controllers for a multi-legged robotic swarm in flat and rough terrains.
When Less Is More in Embodied Evolution: Robotic Swarms Have Better Evolvability with Constrained Communication
Authors: Hiraga Motoaki , Morimoto Daichi , Katada Yoshiaki , Ohkura Kazuhiro
Published: August 2023

Embodied evolution is an evolutionary robotics approach that implements an evolutionary algorithm over a population of robots and evolves while the robots perform their tasks. In embodied evolution, robots send and receive genomes from their neighbors and generate an offspring genome from the exchanged genomes. This study focused on the effects of the communication range for exchanging genomes on the evolvability of embodied evolution. Experiments were conducted using computer simulations, where robot controllers were evolved during a two-target navigation task. The results of the experiments showed that the robotic swarm could achieve better performance by reducing the communication range for exchanging genomes.
Consensus Building in Box-Pushing Problem by BRT Agent that Votes with Frequency Proportional to Profit
Authors: Kubo Masao , Sato Hiroshi , Yamaguchi Akihiro
Published: August 2023

In this study, we added voting behavior in which voting proportionately reflects the value of a view (option, opinion, and so on) to the BRT agent. BRT agent is a consensus-building model of the decision-making process among a group of human, and is a framework that allows the expression of the collective behavior while maintaining dispersiveness, although it has been noted that it is unable to reach consensus by making use of experience. To resolve this issue, we propose the incorporation of a mechanism of voting at frequencies proportional to the value estimated using reinforcement learning. We conducted a series of computer-based experiments using the box-pushing problem and verified that the proposed method reached a consensus to arrive at solutions based on experience.
A Two-Step Fire Blanket Release Mechanism for Unmanned Aerial Vehicles
Authors: Ratsamee Photchara , Hanwong Thanarat , Sison Harn , Thungod Kaned
Published: August 2023

Using fire blankets is one effective option for fire extinguishing. This paper proposes a two-step release mechanism for unmanned aerial vehicles (UAVs) that can precisely drop a blanket onto a target location using the advantage of wind load, avoiding the ground effect. We analyzed wind velocity under the UAV body to find the optimized range that maximizes the release of the fire blanket. Afterwards, we tested the performance of our proposed system in an indoor environment with simulated wind disturbance. Our experiment results showed that the system is robust against wind disturbance at 3.5 m/s. Finally, we tested our system with UAVs in an outdoor environment with different heights and proved the effectiveness of the system for up to 4 m height in an outdoor environment.
Autonomous Navigation System for Multi-Quadrotor Coordination and Human Detection in Search and Rescue
Authors: Dsouza Jeane Marina , Rafikh Rayyan Muhammad , Nair Vishnu G.
Published: August 2023

There are many methodologies assisting in the detection and tracking of trapped victims in the context of disaster management. Disaster management in the aftermath of such sudden occurrences requires preparedness in terms of technology, availability, accessibility, perception, training, evaluation, and deployability. This can be achieved through intensive test, evaluation and comparison of different techniques that are alternative to each other, eventually covering each module of the technology used for the search and rescue operation. Intensive research and development by academia and industry have led to an increased robustness of deep learning techniques such as the use of convolutional neural networks, which has resulted in increased reliance of first responders on the unmanned aerial vehicle (UAV) technology equipped with state-of-the-art computers to process real-time sensory information from cameras and other sensors in quest of possibility of life. In this paper, we propose a method to implement simulated detection of life in the sudden onset of disasters with the help of a deep learning model, and simultaneously implement multi-robot coordination between the vehicles with the use of a suitable region-partitioning technique to further expedite the operation. A simulated test platform was developed with parameters resembling real-life disaster environments using the same sensors.
Environmental Mapping of Underwater Structures Based on Remotely Operated Vehicles with Sonar System
Authors: Ma Bochen , Du Tiancheng , Miyoshi Tasuku
Published: August 2023

Recently, underwater robotics has rapidly developed, and is often used in open-water exploration and underwater operations in known environments. However, there are still several problems in exploring the interiors of complex underwater environments, which are essential for scientific exploration and industrial applications, such as caves and shipwrecks. This study aims to complete the exploration of the environment of structures under water bodies. A real-time manipulative small underwater robot was designed and developed. The robot’s autonomous depth control and linear motion-assisted control are also realized by real-time sensor data processing, which provides stability and operability to move in small areas and complex environments. The sonar system is used to construct a submap for small-area scanning. Finally, by combining the odometer algorithm and contour extraction, the submaps are stitched together to construct a complete map of the internal underwater environment.
Implementation Study of an Adhesion Hand with Stefan Adhesion
Authors: Higa Shoi , Inoue Yuki
Published: August 2023

The field of robotics involves extensive knowledge and skills related to numerous fields, and the World Robot Summit benchmarks technical skills in service robotics through competition. While grasping and moving a wide variety of objects, we examine a new method for handling objects using a suction mechanism. Notably, the proposed mechanism utilizes the adhesion force resulting from Stefan adhesion, which occurs when a solid plate detaches from a smooth surface. Experiments are conducted to evaluate the performance of the adhesion hand, and the obtained results demonstrate its effectiveness.
 
 The 2020 Paul T. Hiser Exemplary Publication Award Recipients 
Authors: Editors JOTS
Published: August 2023

Scott R. Bartholomew, Greg J. Strimel, Anne M Lucietto, and Mesut, "Reinventing High School: Understanding the Challenges and Successes of Transforming Education to Meet Student, Society, and Industry Needs"
Improving Reproductive and Maternal Healthcare Uptake in India: An Evaluation of Project Ujjwal Public-Private Partnership Program
Authors: Lokhande Anagha
Published: August 2023

Background and Objective: Project Ujjwall was a public private partnership established to improve maternal and child health (MCH) outcomes in Bihar and Odisha in India. This paper examines whether Project Ujjwal meaningfully increased the usage of family planning methods and maternal health services to determine whether the Ujjwall program model should be expanded in India. This is the first attempt to establish the causal impact of Project Ujjwal on access to reproductive healthcare in India.
Methods: Data were obtained from the National Family Health Survey of India. A difference-in-differences strategy and linear probability models were used to estimate the likelihood of ever having encountered family planning information or ever having used contraceptives, antenatal care, etc.
Results: The sample size for Odisha was 4,540; the sample size for Bihar was 3,818; the total sample size for all states in the control group was 24,922. Within Odisha and Bihar, Project Ujjwal increased the likelihood of ever having used any contraceptive by 8.9%, increased the likelihood of having ever accessed antenatal care from a licensed doctor or nurse by 2.5% and increased the likelihood of having ever encountered family planning media by 5.1%. However, most results seem differentially driven by the success of the program in either Odisha or Bihar: among all results, only the odds that a woman received delivery assistance (2.8%) and the odds that a woman will have used oral contraceptives by (9.3%) increased statistically significant in both states.
Conclusion and Implications for Translation: These results are promising and show Project Ujjwal may have been more effective than existing government programs. Limitations of this analysis include a lack of information about the demand generation tactics and an inability to include state-level fixed effects due to over-specification concerns. Disparities in the impact of Project Ujjwal on Bihar and Odisha and the lack of specific information about latent demand both suggest the need for further investigation.
 
Copyright © 2023 Lokhande. Published by Global Health and Education Projects, Inc.This is an open-access article distributed under the terms of the Creative Commons Attribution License CC BY 4.0.
Ultrastrong Magnon-Magnon Coupling and Chiral Symmetry Breaking in a 3D Magnonic Metamaterial
Authors: Dion Troy , Stenning Killian , Vanstone Alex , Holder Holly , Sultana Rawnak , Alatteili Ghanem , Martinez Victoria , Kaffash Mojtaba , Kimura Takashi , Kurebayashi Hidekazu , Branford Will , Iacocca Ezio , Jungfleisch M. Benjamin , Gartside Jack
Published: August 2023

Strongly-interacting nanomagnetic arrays are ideal systems for exploring the frontiers of magnonic control. They provide functional reconfigurable platforms and attractive technological solutions across storage, GHz communications and neuromorphic computing. Typically, these systems are primarily constrained by their range of accessible states and the strength of magnon coupling phenomena.
Increasingly, magnetic nanostructures have explored the benefits of expanding into three dimensions. This has broadened the horizons of magnetic microstate spaces and functional behaviours, but precise control of 3D states and dynamics remains challenging.
Here, we introduce a 3D magnonic metamaterial, compatible with widely-available fabrication and characterisation techniques. By combining independently-programmable artificial spin-systems strongly coupled in the $\hat{z}$-plane, we construct a reconfigurable 3D metamaterial with an exceptionally high $16^N$ microstate space and intense static and dynamic magnetic coupling.
The system exhibits a broad range of emergent phenomena driven by high-intensity inter-layer dipolar interaction, including ultrastrong magnon-magnon coupling with normalised coupling rates of $\frac{\Delta \omega}{\gamma} = 0.57$ and magnon-magnon cooperativity up to $C = 126.4$, GHz mode shifts in zero applied field and chirality-selective magneto-toroidal microstate programming and corresponding magnonic spectral control.
Extreme “Catapult” ruptures of the Çardak Fault in the 6 February 2023 Mw 7.6 earthquake in Türkiye
Authors: YALTIRAK CENK , TARI UFUK , DİKBAŞ AYNUR , ÖZCAN ORKAN , ELİTEZ İREM
Published: August 2023

During a Mw 7.6 magnitude earthquake on the Çardak Fault, extreme sinistral displacements occurred along 10 segments representing a 98 km-long surface rupture. The length of the segments ranges between 3.5 and 23.0 km. The surface rupture of the earthquake extends along a narrow deformation zone that is at least 10 cm-wide in places. In the step-over zones of the segments, the coseismic slip is distributed on numerous echelon ruptures where ≥0.5 m of left-lateral displacement is measured in a 1.3 km-wide zone and occasionally becomes completely undetectable. The most important feature of this earthquake is the measured maximum left-lateral displacement along the 98 km-long surface rupture, making it one of the seven earthquakes in the literature with the most extreme displacement (10.0-12.6 m), considering the earthquake magnitudes and fault lengths observed during the instrumental period.
SARS-CoV-2 Spike protein peptides displayed in the Pyrococcus furiosus RAD system preserve epitopes antigenicity, immunogenicity, and virus-neutralizing activity of antibodies
Authors: Cioffi Victor Bolsanelli , Castro-Amarante Maria Fernanda , Lulla Aleksei , Andreata-Santos Robert , Cruz Mario Costa , Moreno Ana Carolina Ramos , Silva Mariangela de Oliveira , Peres Bianca Miranda , Freitas-Junior Lucio Holanda Gondim , Moraes Carolina Borsoi , Durigon Edison Luiz , Gordon Nicola Coker , Hyvonen Marko , Ferreira Luís Carlos Souza , Balan Andrea
Published: August 2023

Concerning the potential contribution of protein or peptide-display systems to study epitopes with relevant immunological features, the archaeal RAD display system stands out as a highly stable scaffold protein that allows the presentation of constrained target peptides. Here, we employed the RAD display system to present peptides derived from the SARS-CoV-2 Spike protein (S) as a tool to detect specific serum antibodies and to generate polyclonal antibodies capable of inhibit the virus infectivity in vitro. Initially, 44 selected linear S-derived peptides were genetically fused with the RAD scaffold (RAD-SCoV-epitopes), which were subsequently screened for antigenicity with sera collected from COVID-19-infected patients. In a second step, selected RAD-SCoV-epitopes were employed to immunize mice and generate antibodies. Based on phenotypic screening techniques, some of these antibodies were able to recognize replicating viral particles in VERO CCL-81. Notably, seven selected RAD-SCoV-epitopes induced antibodies capable of neutralizing viral infection. Our findings highlight the RAD display system as an useful platform for the immunological characterization of peptides and might be a valuable strategy for the design of antigens aiming peptide-based vaccines, epitope-specific antibody mapping, and development of antibodies for diagnostic and therapeutic purposes.
c-Myc Knockout as a Model for Gene Editing for Training Healthcare Professional Students
Authors: Rao Prema S. , Rao U. Subrahmanyeswara
Published: August 2023

Correction of genetic errors, commonly known as gene editing, holds promise to treat diseases with unmet medical needs. However, several gene therapy trials have encountered unwanted outcomes, because of the incomplete understanding of the disease states and gene therapy processes. This situation encourages a concept that healthcare professionals receiving laboratory research will not only identify inadequacies in basic biomedical knowledge in gene therapy but also provide tangible refinements. We thus have undertaken the PharmD student-training program in gene editing in a basic research laboratory setting. As a model, MYC gene was chosen for knockout using CRISPR-Cas9 method in HT29 and OVCAR8 cells. Students were involved in the design of MYC-specific gRNAs, subcloning into Cas9-carrying plasmid, and selection of knockout clones from the transfected cells. Students were involved in the genomic DNA isolation, analysis of DNA sequences from the clones using online bioinformatics tools, western blotting, cell proliferation and cell division cycle, to characterize the knockout clones. Observations made during this training are presented. In this process, students have gained a better understanding of the disease mechanisms, gene therapy protocols, limitations of gene therapies, abilities to evaluate the literature and transfer laboratory training to the practice of gene therapies in clinic.
Visible Light-Enabled Switching of Soft Material Properties Based on Thioindigo Photoswitches
Authors: Truong Vinh , Walden Sarah , Nguyen Phuong , Le Minh , Loh Xian Jun , Barner-Kowollik Christopher
Published: August 2023

Thioindigos are visible light responsive photoswitches with excellent spatial control over the conformational change between their trans- and cis- isomers. However, they possess extremely limited solubility in all conventional organic solvents and polymers, hindering their application in soft matter materials. Herein, we introduce a strategy for the covalent insertion of thioindigo units into polymer main chains, enabling thioindigos to function within crosslinked polymeric hydrogels. We overcome their solubility issues by developing a thioindigo bismethacrylate linker able to undergo radical initiated thiol-ene reaction for step-growth polymerization, generating indigo-containing polymers. The optimal wavelength for the reversible trans-/cis- isomerisation of thioindigo was elucidated by constructing a detailed photochemical action plot of their switching efficiencies at a wide range of monochromatic wavelengths. Critically, indigo-containing polymers display significant photoswitching of the materials’ optical and physical properties in organic solvents and water. Furthermore, the photoswitching of thioindigo within crosslinked structures enables visible light induced modulation of the hydrogel stiffness. Both the thioindigo-containing hydrogels and photoswitching processes are non-toxic to cells, thus offering opportunities for new and advanced applications in soft matter materials and biology-related research.
Enhancing Salient Product Detection: A HybridApproach Incorporating Salient Object Mask and Visual Explanations Heatmap
Authors: Saraçlar Beyzanur , Delil Selman , Kuyumcu Birol
Published: August 2023

In online marketplaces, managing product images can be challenging due to the large volume of images and products available. To capture customers’ attention and promote sales, it is essential to effectively highlight and position the selling product in the ad image. In this paper, we propose a hybrid method for detecting salient product regions in images, which combines salient object detection with visual explanation techniques. Our approach leverages the strengths of two state-of-the-art models: U2-Net for generating high-quality salient object masks, and Ablation-CAM for generating visual explanation heatmaps that highlight the most discriminative regions for classification. According to the experimental results, the hybrid model reduces the number of images that require manual evaluation for determining the suitability between product categories and ad images from 5500 to 250. Furthermore, we demonstrate the interpretability of our method by visualizing the salient regions and explanation heatmaps, which can provide insights into the model’s decision-making process and help users understand why certain regions are important for classification. Overall, our approach offers an effective solution for automating the process of identifying and highlighting the most relevant product regions in ad images, thereby saving time and effort for online marketplace sellers.
Sustainable Land Use Planning in Developing Countries Using GIS and Multi-criteria Analysis: A Case Study of Lalitpur District, Nepal
Authors: Thapa Narayan , Pant Pragya , Prasai Ritika , Mahata Aayush , Dulal Sujan
Published: August 2023

Rapid urbanization in Nepal is leading to unplanned land development and use. This study conducted a comprehensive land use suitability analysis for urban development in Lalitpur District, Nepal, using Geographic Information System (GIS) and Multi-criteria Analysis (MCA) techniques. By studying factors such as existing infrastructure which include land cover, population density, flood sensitivity, slope, digital elevation model (DEM), road network, education and health facility, distance to brick factory and land fill site, the study identified suitable areas for urban development in Lalitpur District. The study identified four suitability classes for urban development: highly suitable, moderately suitable, marginally suitable, and not suitable. Highly suitable areas are typically flat, have low population densities, and are close to infrastructure, far away from landfill site, flood region and brick factory. Moderately suitable areas are typically hilly, have higher population densities, and are farther from infrastructure. Marginal suitable areas are in floodplains, have steep slopes, and are near to industrial areas. Not suitable areas are too steep, highly prone to flood, too close to industrial areas, and have high population density.
The study found that 0.0234 sq.km of the study area is highly suitable for urban development, 146.0344 sq.km is moderately suitable, 214.7742 sq.km is marginally suitable, and 36.0680 sq.km is not suitable. Central and western parts of the district are the most suitable for urban development and northern and southern corner being the least suitable. The findings of the analysis emphasize the importance of considering environmental factors in land use planning and urban development. It highlights the need to preserve green spaces, protect water bodies, and ensure the long-term well-being of residents. The results provide valuable insights for decision-makers and urban planners, enabling them to make informed decisions and allocate resources effectively.
Trends in polypharmacy and excessive polypharmacy: a retrospective national database analysis (2012-2021)
Authors: Linden Lorenz Roger Van der , Tournoy Jos
Published: August 2023

Background
Polypharmacy is a growing concern in healthcare systems worldwide, impacting patient safety and healthcare costs. Monitoring its prevalence and trends is essential for effective healthcare management.
Aim
This study aimed to assess the prevalence and trends of polypharmacy and excessive polypharmacy in Belgium over a decade.
Methods
Utilizing the Belgian Intermutualistic agency database, reimbursed medication data were analyzed from 2012 to 2021. Polypharmacy (≥ 5 medications) and excessive polypharmacy (≥ 10 medications) were evaluated, with prevalence calculated per 1000 inhabitants. Linear regression was employed to examine temporal trends.
Results
In 2021, polypharmacy affected 135/1000 and excessive polypharmacy 31/1000 Belgians. Both entities exhibited a notable increasing trend over the 10-year period, with excessive polypharmacy rising more prominently. Prevalence was significantly higher in older adults (≥ 65 years), reaching 434/1000 for polypharmacy and 106/1000 for excessive polypharmacy. Regional variations were observed, with prevalence highest in the Walloons region. Age and time were identified as independent predictors for both polypharmacy and excessive polypharmacy (p < 0.001).
Conclusion
This comprehensive analysis highlights concerning increases in polypharmacy and excessive polypharmacy over a decade in Belgium, particularly among older adults. Efforts to monitor, manage, and optimize medication use are imperative to ensure safe and effective healthcare delivery.
Long-term survival and development of chronic graft dysfunction after donor lung perfusion repair in isolated lungs-a meta-analysis
Authors: Wang Zihan , Zhang Jin , Yu Qiduo , Chen Fangjun , Xiao Fei , Liang Chaoyang
Published: August 2023

Background
EVLP is deemed successful in enhancing the pool of candidates for lung transplantation subject to a reevaluation of the donor lung’s physiological and biological performance, in addition to an increased preservation period, and aids in healing damaged lung. This meta-analysis aimed to evaluate the impact of EVLP on long-term patient outcomes compared to conventional lung transplantation.
Methods
The data about conventional lung transplantation without ELVP and lung transplantation with EVLP repair were collected. The data were subjected to analysis like receptor baseline values and surgical outcomes, while OR, MD, and HR were employed as effect sizes.
Results
Among the collected literature, ten publications were deemed qualified for incorporation into the study, comprising one prospective cohort and nine retrospective cohort studies, with 5471 donors and 5464 receivers. Those subjects with marginal donor lungs examined and treated with EVLP exhibited equivalent overall and CLAD-free survival compared to those with conventional donor lungs. Moreover, donors in the EVLP group had higher chest X-ray abnormalities and lower P/F. The two groups had no significant difference in developing grade 3 PGD3 post 72 hours of surgery, but the EVLP group required a more extended ICU stay. Other postoperative results for the two groups were comparable.
Conclusions
The donor lung’s quality was lower in the ELVP group; however, those with donor lung EVLP screening and therapy had comparable overall and CLAD-free survival to those who underwent conventional donor lung.
Directional transport of drug droplets based on structural and wettability gradients
Authors: Lin Jing , Yao Zhen , Hua Zihan , Xiong Minmin , Hu Fei , Wei Xinchuan , Huang Songyin
Published: August 2023

The failure of wound healing is majorly attributed to uncontrolled bleeding and bacterial infections. However, developing a wound plaster that can stop bleeding, resist blood extravasation, and realize directional transportation of drugs to promote wound healing remains a significant challenge. Herein, we developed a superhydrophilic/hydrophobic PVA/CS/Ag@TPU Janus membrane with structural and wettability gradients. In this newly developed membrane, water is absorbed from blood via the superhydrophilic layer, which is attached to the wound, and the charge interactions between platelets and the introduced chitosan (CS) promote blood clotting. The capillary pressure resistance (∆p > 0) of the superhydrophilic layer toward the hydrophobic layer prevents blood permeation, thereby reducing blood loss. The favorable ∆p (< 0) of the membrane based on its structural and wettability gradients can realize the directional transportation of drugs that promote wound healing from the hydrophobic to the superhydrophilic layer. The incorporation of CS and silver endows the Janus membrane with intrinsic antibacterial properties (99.9%). The formation of the hydrated layer on the hydrophilic layer imparts a resisting effect, further endowing the membrane with antiadhesion and antibacterial properties. Experiments involving mice with full-thickness skin wounds revealed that the wound-healing rate increased from 87.65% to ~ 100% when the Janus membrane was loaded with the prehealing drug. Moreover, the dressing accelerated wound healing, regenerated epidermal and granulation tissues, promoted collagen formation, and reduced scar size. Thus, this gradient design strategy opens an avenue for the development of next-generation wound dressings.
Reliability and usefulness of ChatGPT for inflammatory bowel diseases:An analysis for patients and healthcare professionals
Authors: Cankurtaran Rasim Eren , Polat Yunus Halil , Aydemir Neslihan Gunes , Umay Ebru , Yurekli Oyku Tayfur
Published: August 2023

Purpose
We aimed to evaluate the performance of ChatGPT within the context of IBD, which is expected to become an increasingly significant health issue in the future. Additionally, the objective of the study was to assess whether ChatGPT serves as a reliable and useful resource for both patients and healthcare professionals.
Methods
For this study, specific 20 questions were identified for the two main components of IBD, which are Crohn's Disease (CD) and Ulcerative Colitis (UC). All the questions for each disease were divided into two categories, directed towards patients and healthcare professionals. The responses were evaluated with seven-point Likert-type reliability and usefulness scales.
Results
The highest scores in both reliability and usefulness were obtained from professional sources (mean 5.00 ± SD 1.21 and mean 5.15 ± SD 1.08, respectively). The ranking in terms of reliability and usefulness, respectively, was as follows: CD (mean 4.70 ± SD 1.26 and mean 4.75 ± SD 1.06) questions, and then UC (mean 4.40 ± SD 1.21 and mean 4.55 ± SD 1.31) questions. The reliability scores of the answers for the professionals were significantly higher than those for the patients (Both raters, p = o.o32).
Conclusion
Despite its realism and usability in IBD diseases, ChatGPT still has some deficiencies and errors. The rectification of ChatGPT's deficiencies and its improvement by developers with more detailed and up-to-date information could make it an important source of information for both patients and medical professionals.
Temperature Anomalies in the Northern and Southern Hemispheres. Evidence of Persistence and Trends
Authors: Gil-Alana Luis Alberiko , Carmona-González Nieves
Published: August 2023

Northern and southern hemisphere temperature anomalies along with the difference between the two have been examined in this paper in order to estimate the time trend coefficients and the degrees of persistence in the data. Looking at the overall sample period (from 1880m1 to 2021m10) the results indicate higher degrees of persistence and more accentuated trends in the case of the northern hemisphere temperatures. We also observe some degree of persistence and a positive trend for the differenced series. Finally, observing the evolution of these two characteristics over the last 50 years, we notice that in the northern temperatures, both the degree of persistence and the time trend have increased across time but these increases are not observed in the case of the southern temperatures.
JEL Code: C22; Q53; Q54
A dynamic online nomogram for predicting renal outcomes of idiopathic membranous nephropathy
Authors: Wang Feng , Xu Jiayi , Wang Fumei , Yang Xu , Xia Yang , Jiao Congcong , Su Xuesong , Zhang Beiru , Zhou Hua , Wang Yanqiu
Published: August 2023

Background
Idiopathic membranous nephropathy (IMN) is the most common cause of nephrotic syndrome in nondiabetic adults. The natural course of IMN is variable, 30% of patients may progress to end-stage renal disease in 10 years. Hence there is an increasing need to develop a dynamic online nomogram for predicting the prognosis of IMN.
Methods
All the data were obtained from the newly diagnosed IMN patients enrolled in 3 hospitals in Liaoning Province. The nomogram prognostic model was developed by independent risk factors of multivariate logistic regression. The prognostic performance was evaluated using the ROC, calibration and decision curves.
Results
A total of 130 patients were in the training cohort and 102 patients in the validation cohort. Course ≥ 6 months (OR, 0.225; 95% confidence interval (CI) 0.081, 0.628; P = .004), UTP (OR, 1.140; 95% CI 1.029, 1.262; P = .012), D-Dimer (OR, 1.001; 95% CI 1.000, 1.002; P = .009), and sPLA2R-Ab (OR, 1.005; 95% CI 1.001, 1.008; P = .006) were independently associated with the IMN progression. The nomogram model showed good calibration with a concordance index (C-index) of 0.835 in the training cohort and 0.874 in the validation cohort, with excellent calibration ability and clinical utility.
Conclusions
We developed a dynamic online nomogram model that can be used to predict the risk of progression in IMN, showing good discrimination and calibration ability.
Association between Vitamin E and myopia in a cross- sectional study of the United States population
Authors: Zheng Tianli , Qu Yaohui , Fu Weiwei , Zhang Hongxing , Yang Xiaodong
Published: August 2023

Although studies have indicated that Vitamin E has a protective effect against glaucoma and cataracts in middle-aged and elderly populations, and that myopia has a relationship with the incidence of glaucoma and cataracts in middle-aged and older adults, no studies on the relationship between Vitamin E and myopia have been reported. Therefore, the objective of this study was to investigate the association between Vitamin E levels and myopia in the American population. This cross-sectional study included participants from the 1999–2008 National Health and Nutrition Examination Survey. Vitamin E was the exposure factor and myopia was defined as spherical equivalent ≤ -0.5 diopters in the right eye. Multivariate logistic regression analysis was performed to evaluate the association between Vitamin E levels and myopia. In total, 16,924 participants were included, and the prevalence of myopia was 51.9%. Compared to individuals with lower Vitamin E absorption Q1 (< 3.48 mg/day), the adjusted odds ratios for Vitamin E absorption in Q2 (3.48–5.45 mg/day), Q3 (5.45–8.23 mg/day), and Q4 (≥ 8.23 mg/day) were 0.98, 1.04, and 0.98, respectively. In a sample of adults in the United States, Vitamin E levels were not associated with either a decreased or increased risk of myopia.
Effectiveness of High-resolution T2-weighted Mri in Restaging Rectal Cancer After Neoadjuvan Chemoradiotherapy
Authors: Topal¹ Ümmihan , Yırgın² Hakan , Gündüz³ Nermin , Kara Yasin , Yilmaz² Serhan , Somuncu² Erkan , Yılmaz Gülseren , Şahin Ayça Sultan , Kocataş² Ali
Published: August 2023

Objective: The technical success of high-resolution T2-weighted magnetic resonance imaging (hT2W-MRI) sequence in restaging locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy (nCRT) was investigated.
Materials and methods: Nineteen patients with an age mean 56 ( range of 37-76) who received nCRT for rectal cancer, had MRI for the rectum and underwent surgical operation between 2020-2022 were included in the study. MRI results were compared with relevant histopathological studies after definitive surgery .
Results: hT2W-MRI correctly predicted all tumors with pathological stage T3 100% (5/5). hT2W-MRI predicted correctly in 3 of 4 patients with pathological stages T4a and T4b (75%). Considering lymph node positivity, the prediction rate of hT2W-MRI was 42.1%(8/19). hT2A-MRI correctly predicted all tumors with circumferential resection margin (CRM), peritoneal reflection involvement, and extramural venous invasion (EMVI). The success of hT2W-MRI in predicting the pathological response (residual tumor) was high (89.5%, 17/19).
Conclusion: Staging of rectal cancer after nCRT is important for treatment planning. Functional assessment with diffusion-weighted MRI and perfusion MRI play a role in predicting tumor aggressiveness, likelihood of response to treatment, and size of tumor remaining after treatment. An accurate and practical radiological identification is important, as the findings on MRI after nCRT are related to the patient's prognosis and survival, and the tumor stage is based on the depth of invasion of the rectal wall and the involvement of adjacent organs. It would be beneficial to include the hT2A-MRI sequence in standard pelvic MRI examination sequences in staging of rectal cancer after nCRT and in demonstrating the presence of residual tumor.
Can Botulinum Toxin Injection be considered a First-Line Treatment for the Management of Chronic Anal Fissure? A Prospective Controlled Study with 5-years Follow-up.
Authors: Ascanelli Simona , Rossin Eleonora , Aisoni Filippo , Sette Elisabetta , Chimisso Laura , Valpiani Giorgia , Carcoforo Paolo , Feo Carlo
Published: August 2023

Purpose
Botulinum Toxin effectiveness for treatment of chronic anal fissure has been widely proven, but there is lack of evidence about treatment standardization and long-term follow-up. The purpose of this study was to evaluate the short- and long-term efficacy and safety of Botulinum Toxin treatment compared with close lateral internal sphincterotomy, with 5-years follow-up.
Methods
This was a prospective, case-control, single-center study conducted at Ferrara University Hospital, Italy. The primary outcome was fissure healing at 1 month.
Results
59 patients received the Botulinum Toxin injection, and 32 patients underwent lateral internal sphincterotomy. At 1 month after treatments postoperative pain decreased faster and significantly more in the Botox group (30 mm vs 60 mm, p < 0.001); fissure re-epithelization was observed in 59.4% of surgical group compared to 25.4% in Botox group (p = 0.0001); anal sphincter pressures decreased more in surgical group (p = 0.044) and severe anal incontinence was present only in surgical group (6.2% of patients, p = 0.041). Patient satisfaction was better in Botox group (p < 0.001). Adverse Events occurred more frequently in surgical group (46.9% vs 8.5%, p < 0.001). Fissure recurrence at 6 months was observed in 16.9% of patients in Botox group vs 3.2% in surgical group (p = 0.053). At 12 months the overall healing rate improved to 100% in the two groups persisting in all patients in both groups after 5 years with high patient satisfaction despite the presence of mild anal incontinence in 21.8% of patients of surgical group (p < 0.05).
Conclusion
Botox injection can be considered as a first-line treatment for chronic anal fissure.