bluuebunny/crossref_metadata_2025 huggingface dataset:
Towards Improving Aspect-Oriented Software Reusability Estimation
Authors: Magableh Aws A. , Saifan Ahmad A. , Rawashdeh Adnan , Ata Hana’a Bani
Published: July 2023

Nowadays, large numbers of organizations may prefer Aspect-Oriented Programming (AOP), which is an enhancement to Object-Oriented Programming (OOP). This is due to the concepts that have been added and helped in producing more flexible and reusable components. As a result, AOP has directed attention to software reuse, which is a significant topic for researchers and offers several advantages for organizations. Software reuse is based on reusability attributes which indicate the possibility of a component that was built to be reused in developing a new system. It is one of the most essential attributes to evaluate the quality of a system’s components. Many models have been built to estimate the reusability of the software but most of them are not dedicated to Aspect-Oriented Software (AOS). This study aims to establish a ground for AOS reusability estimation and measurement based on a new model and its associated equations depending on six attributes that impact AOS reusability negatively and/or positively. Four attributes of them have been included in previous studies which are coupling, cohesion, design size, and messaging. Two new attributes have been proposed in this study, which are complexity, and generality. Both of these attributes have been measured based on the metrics that have also been proposed in this study. A new equation to calculate AOS reusability has been proposed in this research work. Seven Aspect projects have been employed as a case study to apply the proposed equation.
Mitochondrial and cellular function in fibroblasts and reprogrammed neural cells: insights into major depression as a mitochondria-associated disease
Authors: Wetzel Christian , Cardon Iseline , Grobecker Sonja , Kücükoktay Selin , Bader Stefanie , Jahner Tatjana , Nothdurfter Caroline , Koschitzki Kevin-Thomas , Berneburg Mark , Stöhr Heidi , Weber Bernhard , Höring Marcus , Liebisch Gerhard , Braun Frank , Rothammer-Hampl Tanja , Riemenschneider Markus , Rupprecht Rainer , Milenkovic Vladimir
Published: July 2023

The neurobiological underpinnings of major depressive disorder (MDD) remain still elusive. Meanwhile, mitochondria and energy metabolism turn into focus as relevant pathomechanisms of MDD. To gain further insight on the role of mitochondria function in MDD, in the present work, we examined the functional cellular and mitochondrial properties in cells derived from two specific patients, diagnosed as suffering from a mild form of mitochondriopathy with unknown cause, and an antidepressant non-responding MDD patient and compared these patients to a cohort of MDD and control subjects. Using skin biopsies of the two patients as well as non-depressed healthy controls, we obtained dermal fibroblasts and generated iPSCs, neural progenitors, neurons, and astrocytes. Notably, we observed that cellular and mitochondrial functions and neuronal electrophysiology in the mitochondriopathy patient resembled findings in the MDD cohort. This included decreased respiration, mitochondrial membrane potential (MMP) and depolarized resting membrane potential, associated with smaller sodium currents. In contrast, cells derived from the non-responder MDD patient were affected in an opposite manner in many of the measured parameters, including increased respiratory rates, mitochondrial calcium, and lower resting membrane potential. However, in all patient cells we consistently observed a smaller cell size compared to healthy controls. Our findings revealed marked similarities between the mitochondriopathy patient and the MDD cohort, supporting the hypothesis that mitochondria play a significant role in the pathophysiology of depression. The overall opposite functional phenotype of the non-responder patient pointed towards distinct or counterregulatory mechanisms involved in the etiology and/or treatment resistance of depression in this patient and emphasized the importance of investigating depression-related phenotypes from different disease entities to gain a more comprehensive understanding of the pathology of MDD.
Routes of Introduction of Anopheles gambiae Into Remote Islands in the Indian Ocean
Authors: Ditter Robert E. , Campos Melina , Crepeau Marc W. , Pinto João , Toilibou Ali , Amina Yssouf , Lee Yoosook , Cornel Anthony J. , Lanzaro Gregory C.
Published: July 2023

The malaria vector Anopheles gambiae s.s., is a primary malaria vector throughout sub-Saharan Africa including the islands of the Comoros archipelago (Anjouan, Grande Comore, Mayotte and Mohéli). These islands are located at the northern end of the Mozambique Channel in eastern Africa. Previous studies have shown a relatively high degree of genetic isolation between island and mainland populations of A. gambiae, but the origin of the island populations remains unclear. Here, we analyzed phylogenetic relationships among island and mainland populations using complete mitochondrial genome sequences of individual A. gambiae specimens. We investigated the source population of A. gambiaefor each island, determined the number of introductions and estimated when they occurred, and explored evidence for contemporary gene flow between island and mainland populations. Phylogenetic analysis and haplotype networks were constructed from mitogenome sequences of 258 A. gambiae from the four islands. In addition, 112 individuals from seven countries across sub-Saharan Africa and Madagascar were included to identify potential source populations. Our results suggest that introduction events of A. gambiae into the Comoros archipelago were rare and recent events and that there is no evidence of contemporary migration between the islands and mainland Africa. This study further supports the suitability of these oceanic islands as appropriate sites for conducting field trial releases of genetically engineered mosquitoes (GEMs).
Decentralized Convex Optimization on Time-Varying Networks with Application to Wasserstein Barycenters
Authors: Yufereva Olga , Persiianov Michael , Dvurechensky Pavel , Gasnikov Alexander , Kovalev Dmitry
Published: July 2023

Inspired by recent advances in distributed algorithms for approximating Wasserstein barycenters, we propose a novel distributed algorithm for this problem. The main novelty is that we consider time-varying computational networks, which are motivated by examples when only a subset of sensors can make an observation at each time step, and yet, the goal is to average signals (e.g., satellite pictures of some area) by approximating their barycenter. We embed this problem into a class of non-smooth dual-friendly distributed optimization problems over time-varying networks, and develop a first-order method for this class. We prove non-asymptotic accelerated in the sense of Nesterov convergence rates and explicitly characterize their dependence on the parameters of the network and its dynamics. In the experiments, we demonstrate the efficiency of the proposed algorithm when applied to the Wasserstein barycenter problem.
A Reliable Cloud Communication System Using Attribute-Based Cryptography
Authors: CHANDRAKASAN BHARANIDHARAN , V SATHYA , SUBRAMANIAN MALATHI , M RAJAKUMARAN
Published: July 2023

Cloud communication systems are increasingly being used to store and exchange sensitive information. However, ensuring the confidentiality and integrity of data in the cloud remains a significant challenge. Attribute-based cryptography (ABC) has emerged as a promising solution for secure cloud communication. It allows data to be encrypted and accessed based on a set of user-defined attributes. This paper proposes a reliable cloud communication system that leverages attribute-based cryptography to provide secure and efficient data storage and retrieval.
The proposed system employs a hybrid encryption scheme, combining symmetric and attribute-based encryption, to achieve both efficiency and security. Data is first encrypted using symmetric encryption, ensuring fast and secure transmission to the cloud. Then, the symmetric key is encrypted using attribute-based encryption, which enables fine-grained access control and allows only authorized users with specific attributes to decrypt the data.
To enhance the reliability and availability of the system, data is replicated across multiple cloud servers using erasure coding. This redundancy ensures data durability and enables efficient data recovery in case of server failures or data corruption. Additionally, the system incorporates secure data deduplication techniques to optimize storage utilization and reduce network bandwidth consumption.
Circulating Tumor DNA-Based Copy-Number Profiles Enable Monitoring Treatment Effects During Therapy in High-Grade Serous Carcinoma
Authors: Nguyen Mai T.N. , Rajavuori Anna , Huhtinen Kaisa , Hietanen Sakari , Hynninen Johanna , Oikkonen Jaana , Hautaniemi Sampsa
Published: July 2023

Background
Circulating tumor DNA (ctDNA) analysis has emerged as a promising tool for detecting and profiling longitudinal genomic changes in cancer. While copy-number alterations (CNAs) play a major role in cancers, monitoring treatment effects using copy-number profiles has received limited attention compared to mutations. This is primarily due to the challenge of CNA analysis for real-life tumor-fraction ctDNA samples.
Method
Our study aimed to investigate the longitudinal copy number profiles of ctDNA and assess the role of ctDNA samples, even with low tumor fractions, in monitoring cancer treatment. We conducted copy-number analysis on 152 plasma samples collected from 29 patients diagnosed with high-grade serous carcinoma (HGSC). Our sequencing panel targeted more than 500 genes, enabling a comprehensive evaluation of genomic changes. Among the patients, 21 individuals had matched tissue and plasma samples collected at different time points, allowing us to assess the concordance between tissue and plasma and to evaluate the sensitivity of our approach using Kendall correlation values. Statistical comparisons were performed using the Wilcoxon rank test to ensure the robustness of the findings.
Result
Our approach successfully detected concordant CNA profiles in most plasma samples, even with tumor content as low as 3%. Additionally, highly amplified regions were identified in samples with approximately 1% tumor content. Longitudinal analysis revealed changes in CNA profiles in seven out of 11 patients with high tumor-content plasma samples at relapse. These changes included focal acquired or lost copy numbers, whereas the majority of the genome remained stable. Two patients displayed significant changes in their copy-number profile during therapy. Our analysis uncovered ctDNA-detectable subclonal selection resulting from surgery and chemotherapy.
Conclusion
Overall, our study demonstrated acquired and diminished CNAs at relapse compared with pre-treatment samples, highlighting the dynamic nature of CNA profiles during treatment. These findings provide compelling evidence for the potential of ctDNA analysis in tracking treatment responses and detecting genomic changes associated with relapse. Monitoring CNAs can serve as a complementary tool to understand cancer cell evolution and treatment efficacy.
Paclitaxel Suppressed N6-Methyladenosine of PUM1 offsets cetuximab resistance in colorectal cancer
Authors: Liu Qi-zhi , Yu Hai-rong , Zhou Min-jun , Chen Zhuo , Zhou De-hua , Chen Jun-yi , Zhang Nan , Huang Zhen-xing , xie yu-xiang , tu xiaohuang
Published: July 2023

Background
We have previously demonstrated that RNA-binding protein Pumilio-1 (PUM1) is ubiquitous in cetuximab-resistant colorectal cancer (CRC) cells. The role of the N6-methyladenosine modification of PUM1 influenced by paclitaxel (PTX) in modulating cetuximab-resistance in CRC cells was investigated in the current work.
Methods
PUM1 mRNA expression in CRC tissues and cells was measured by quantitative real-time PCR (qRT-PCR), and PUM1 protein expression was measured by immunohistochemistry (IHC). The involvement of PUM1 expression in CRC prognosis was evaluated by survival analysis. RNA immunoprecipitation (RIP) was performed to evaluate combination capability of PUM1 and YTHDF1. RNA m6A dot blot assays were conducted to investigate variations in the degree of the METTL3-induced N6-methyladenosine modification of PUM1. Patient derived tumor xenograft (PDX) models to investigate the regulatory role of paclitaxel inhibited N6-demethyladenosine modification of PUM1 and diminished PUM1 mRNA level.
Results
The N6-methyladenosine content of PUM1 was increased in CRC by cetuximab treatment and increased PUM1 mRNA stability (P < 0.05). PUM1 induced monocyte-to-macrophage differentiation of CRC cells during in vitro functional assays and activated the WNT axis by enhancing DDX5 expression (P < 0.05). Paclitaxel increased PUM1 N6-demethyladenosine levels and decreased PUM1 expression (P < 0.05), resulting in suppression of the WNT pathway. Paclitaxel also reduced PUM1-induced cetuximab-resistance in CRC cells. CRC xenografts from human patients had enhanced m6A modification of PUM1 in paclitaxel-treated samples (P < 0.05) shown by ex vivo studies. In clinic, high PUM1 levels in CRC patients correlated with elevated TAM content and poor survival (P < 0.05).
Conclusion
Inhibition of N6-methyladenosine modification of PUM1 is proposed as a novel therapeutic target to overcome cetuximab-resistance in CRC.
Human Postural Responses to Artificial Gravity Training
Authors: Saveko Alina , Koloteva Milena , Tomilovskaya Elena
Published: July 2023

Short-radius centrifugation (SRC) is a promising and economically feasible countermeasure in space flight and applies to gravity therapy in terrestrial medicine. The potential occurrence of undesirable orthostatic and vestibular reactions limits the use of this method. One way to minimize these risks is the ability of a human to adapt to the effects of overload. It is known that artificial gravity training may improve orthostatic tolerance. New data demonstrated that cardio-postural interactions and muscle-pump baroreflex activation are present during short-arm centrifugation. Based on previous studies, we hypothesized that repeated SRC in the interval training mode with angular velocities from 22 to 28 rpm may also improve postural tolerance. Six healthy male volunteers were observed before and immediately after five consecutive SRC sessions. The rest between SRC was at least three days. The SRC mode was an interval and included five 300-second platforms with 1.27 g at the feet and four 300-second platforms with 2.06 g at the feet. We registered the main postural characteristics and ground reaction forces data when the participant kept the center of pressure at a given point in a standing position with biofeedback and without this. After the first SRC session, there was a significant posture decondition. The SRC training effect was already noticeable after the second SRC session and was stable until the end of the experiment. The results demonstrate the development of postural tolerance to artificial gravity exposure in this mode and expand the understanding of sensorimotor adaptation capabilities.
Swarming magnetic surface microrollers enable directed locomotion in circular confinements
Authors: Bozuyuk Ugur , Han Mertcan , Sitti Metin
Published: July 2023

Microrobots are always envisioned to operate in confined spaces in the human body or microfluidic chips. Among the various microrobotic platforms, magnetic surface microrollers have emerged as versatile option due to their robust locomotion and ease of fabrication. Still, the locomotion of spherical magnetic surface microrollers is challenging in confinements as their rotational flows severely impede their translational locomotion. Particularly, their locomotion in circular confinements presents an even greater challenge, as their translational direction reverses when they function as individual microrollers. Nevertheless, their locomotion dynamics could differ whether they travel as a single or swarming unit. Swarming, in general, is known to render hydrodynamic advantages to microrobots which could also be useful for surface microrollers to locomote in confined spaces. Here, we investigated the locomotion of swarming microrollers in circular confined spaces in a computational fluid dynamics environment. We observed that a group of microrollers can locomote in desired translational locomotion direction, while a single microroller performs reverse locomotion. Furthermore, we performed a showcase experiment demonstrating the observed effect in computational fluid dynamics simulations. In summary, our research outcomes offer a profound understanding of the underlying physical mechanisms that govern the locomotion of surface microrollers.
Assessment of Corrosion Resistance Potentials in welded and tempered UNS G10400 Carbon steel in seawater environment
Authors: Okuma Silas Oseme , Oreko Benjamin Ufuoma
Published: July 2023

Welded joints sometimes exhibit poor corrosion resistance, due to variation in chemical composition at the weld surface or Heat Affected Zone (HAZ), induced stress and the microstructure formation. There is a need to enhance welds corrosion resistance and microstructural properties of such joints through post weld tempering (PWT). In this study, PWT effect on the corrosion resistance and microstructure properties of UNS G10400 carbon steel was investigated. The UNS G10400 samples, were cut to the desired dimensions, welded by means of electric metal arc welding process and subjected to PWT, at 550ºC, 650ºC, and 700ºC, for 1 h, respectively. The samples were immersed in seawater environment and its corrosion resistance and microstructure properties were then evaluated, using gravimetric technique, Open Circuit Potential (OCP), Potentiodynamic Polarization (PDP), Electrochemical Impedance Spectroscopy (EIS) and Scanning Electron Microscope (SEM)/ Energy-Dispersive X-ray Spectroscopy (EDX), respectively. The findings show that the post-weld tempered (PWT) samples exhibited higher corrosion resistance compared to the as-welded samples. The corrosion rate values are 0.1351, 0.06331, 0.06271 and 0.01578mm/year for as-welded, PWT-5500C, PWT-6500C and PWT-7000C samples respectively. The SEM/EDX images of PWT samples revealed an increased in grain size, forming a tempered martensite. These results are due to re-crystallization and grain growth resulting from post-weld tempering. Therefore, an appropriate post weld tempering for UNS G10400 carbon steel welded joints is recommended for advanced industrial applications.
Multi-Threshold Segmentation of Breast Cancer Images Based on Improve Dandelion Optimization Algorithm
Authors: Wang Zhenghong , Yu Fanhua , Wang Dan , Hu Rongjun
Published: July 2023

The complex structure and blurry cell boundaries in breast cancer histopathological tissue images under a microscope pose challenges for accurate segmentation using traditional thresholding methods. To address the problem of accurately separating lesion areas in breast cancer images, this study proposes a multi-threshold segmentation method based on the Enhanced Dandelion Optimization algorithm (IDO).The proposed method incorporates the concept of opposite-based learning and utilizes IDO to compute the maximum between-class variance (OTSU) as the objective function. It also establishes fallback strategies and a memory matrix while combining the golden jackal energy judgment mechanism to search for the optimal thresholds. Experimental comparisons are conducted by applying IDO algorithm along with Harris Hawks Optimization (HHO), Gorilla Troops Optimization (GTO), traditional Dandelion Optimization (DO), and Marine Predators Algorithm (MPA) using the same thresholds for image segmentation. The performance analysis is based on four metrics: Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), Feature Similarity Index (FSIM), and Mean Squared Error (MSE), as well as their fitness function curves.The experimental results demonstrate that the Enhanced Dandelion Optimization algorithm outperforms other algorithms in terms of PSNR, SSIM, FSIM, and MSE segmentation metrics. It exhibits faster convergence and effectively resolves the segmentation problem.
A Two-tier Multi-objective Service Placement in Container-based Fog-Cloud Computing Platforms
Authors: Dogani Javad , Yazdanpanah Ali , Zare Arash , Khunjush Farshad
Published: July 2023

Using cloud computing for Internet of Things (IoT) applications necessitates the transmission of all data to the centralized structure of the cloud, thereby leading to an increase in network traffic and service time. Consequently, cloud computing proves impractical for latency-sensitive IoT applications. Fog computing, acting as an intermediate layer between the cloud and IoT, ensures low latency for such applications. The service placement problem, an NP-hard problem that determines which node should host each service, represents one of the major challenges in the fog computing paradigm. While lightweight containers have emerged as a highly efficient virtualization approach, prior research predominantly employed traditional VM-based architecture for service placement in fog computing. Therefore, this study introduces a multi-objective optimization approach for dynamic service placement in container-based fog computing, accounting for cost, latency, and energy consumption. Specifically, we propose a two-tier framework for resource management in fog computing based on Kubernetes. The multi-objective non-dominated sorting genetic algorithm II (NSGA-II) algorithm balances conflicting performance objectives, such as latency, cost, and energy consumption. Empirical results demonstrate that the proposed method outperforms existing state-of-the-art methods.
Decisional conflict is associated with quality of life and mental health in patients with inflammatory bowel disease
Authors: 谢 华兵 , zhang jixiang , liu chuan , zhen junhai , yang bingxiang , gao yuanyuan , weiguo dong
Published: July 2023

Purpose
Inflammatory bowel disease (IBD) patients are usually provided with multiple treatment options with different risks and benefits. This study aimed to assess the quality of decision-making in IBD patients concerning treatments, investigate the relationship between Shared decision-making (SDM) and decision conflict and health outcomes in patients with IBD, and explore the possible factors related to high decisional conflict in patients with IBD.
Methods
We conducted a cross-sectional, multicenter study. Patients were grouped according to their actual decision-making role and the level of decisional conflict. Propensity score analysis matched the two groups of patients 1:1 according to different factors. The main measures assessed included decisional conflict, decision regret, compliance, quality of physician communication, satisfaction, quality of life, anxiety, depression, and sleep disturbance. Multiple logistic regression was used to evaluate the factors affecting decisional conflict.
Results
Patients in the SDM group had a high awareness of the disease, and the impact of decision conflict and disease on work and learning was also low. The actual decision roles, physician communication quality, and disease activity may be independent factors affecting the decisional conflict. DCS was negatively correlated with the patient’s compliance and satisfaction with physician explanations and treatment and positively correlated with DRS, anxiety, depression, sleep disturbance, and SHS (all P <0.05).
Conclusion: SDM is beneficial for improving the quality of decision making in patients with IBD. It is necessary to improve decisional conflict in IBD patients because it is closely related to patients' quality of life and mental health.
Incidence of stroke and its association with metabolic abnormalities in patients with atrial fibrillation: The Jordan Atrial Fibrillation (JoFib) study
Authors: Alkouri Osama , Khader Yousef , Qaladi Omar Aawadh , Jarrah Mohamad , Alawaisheh Raed , Alqarni Aidah Sanad , Gonzales Ferdinand , Ramadan Anoud , harbi Abdulhafith Al
Published: July 2023

Background Evidence regarding the concomitant impact of multiple metabolic comorbidities on stroke risk in patients with atrial fibrillation is still equivocal. Despite the high prevalence of these comorbidities in the Middle East, no studies were conducted to predict their combined effect on stroke risk in patients with atrial fibrillation. This study aimed at identifying stroke incidence and the association between metabolic abnormalities and one-year risk of stroke in patients with atrial fibrillation.
Methods: The study enrolled 2020 consecutive patients with atrial fibrillation. The incidence of stroke was compared across categories of different variables using the chi-square test. Two binary logistic regression models were developed to identify the significant predictors of stroke.
Results: The 1-year incidence of stroke was 3.1%. Only diabetes was significantly associated with increased odds of stroke (OR = 2.15; 95% CI: 1.26, 3.66; p = 0.005) after adjusting for significant predictors of stroke including age, past history of stroke, and CHA2DS2VAS score. The combination of metabolic abnormalities was significantly associated with increased odds of stroke. The odds ratio increased from 2.53 (95% CI 1.10-8.85, P=0.028) for patients with only one metabolic abnormality to 3.90 (95% CI 1.16-13.10, P=0.028) for patients who had two metabolic abnormalities to 4.95 (95% CI 1.47-16.71, P=0.041) for patients with three metabolic abnormalities.
Conclusion: Adequate glycemic control for patients with diabetes is crucial for patients with coexisting atrial fibrillation. Stroke prevention should focus on the concomitant impacts of multiple metabolic comorbidities rather than on a particular or single risk factor such as atrial fibrillation (AF). Comprehensive nursing assessment and management of coexisting metabolic abnormalities in patients with atrial fibrillation is substantial to minimize the stroke risk and prevent serious health complications. Nursing education helps patients with DM and hypertension to adhere to their treatment regimen, understand their condition, follow dietary restrictions, and seek medical attention if needed. Our findings postulate that the presence of multiple metabolic comorbidities may eliminate the effect of atrial fibrillation on stroke risk. Thus, further research is warranted to identify the coincident impact of multiple metabolic abnormalities on stroke risk in patients without atrial fibrillation.
Body image victimization and eating distress in young adult females
Authors: SINGH PRIYA , GUPTA AARZOO
Published: July 2023

Background
Eating distress syndrome (EDS) is characterized by distressing and conflicting thoughts about the body shape and eating behaviours accompanied by self-imposition of strict dietary and/or exercise regimes in the absence of any significant weight loss. EDS has prevalence of nearly 11% and is associated with psychological distress, internalizing and externalizing problems, lesser well-being, and reduced quality of life.
Methods
The study aimed to assess the relationship between eating-related messages, and body image victimization with eating distress syndrome in young adult females. Purposive sampling was employed to approach an estimated sample size of 151 young adults (18–26 years). The data was collected online by using e-consent through social media platforms such as Facebook, Twitter, Instagram, etc. via Google Form (GF). There was a total of 403 respondents to GF comprising of Caregiver Eating Messages Scale (CEMS), Body Image Victimisation Experience Scale (BIVES), Eating Disorder Examination - Questionnaire Short (EDE-QS). Total 151 were recruited from 403 as per defined criteria.
Results
Restrictive or critical messages (RCM) had a positive relationship and accounted 12% chance of occurrence of EDS. Frequency of experiences of body image victimization from peers (6%) had a greater predictive value than that from the parents (3%). Similarly, the impact of body image victimization by peers (9%) contributed more than that from the parents (4%) in the occurrence of EDS.
Conclusion
Remarks or comments related to eating and appearance tend to determine how an individual perceived oneself and the course of one’s food habits or choices.
Case study: modeling and robust control of two wheeled self-balancing mobile with µ approach
Authors: Delavar Abolfazl
Published: July 2023

Robots are one of the most useful tools in today’s world. They are widely used to move objects and perform everyday tasks. Segways are one of these tools that are commonly used nowadays for transportation and even entertainment. In this case study, the dynamical model of a two-wheeled self-balancing mobile device has been proposed. Additionally, a µ robust controller for the device has been designed. All necessary sources are available in the repository: https://github.com/abolfazldelavar/Two_wheeled_self_balancing_mu_approach_CS
Nonstandard approach to fixed point of 2nd-order orbit asymptotic contraction
Authors: Shi Jie
Published: July 2023

In this paper, the 2nd-order orbit asymptotic contraction is given. The local iterative fixed point problem of the new 2nd-order orbit asymptotic contraction is considered by nonstandard analysis methods. We have conducted further research based on the relevant achievements of some scholars. We obtained the results of the corresponding iterative sequence converging to the local iterative fixed point of the asymptotic contraction T without the continuity.
Mathematics Subject Classification (2010). Primary 47H10,54H25; Secondary 03H05,54J05.
Plasticity and not adaptation is the primary source of temperature-mediated variation in flowering phenology in North America
Authors: Ramirez-Parada Tadeo , Park Isaac , Record Sydne , Davis Charles , Ellison Aaron , Mazer Susan
Published: July 2023

Phenology varies widely over space and time because of its sensitivity to climate. However, whether phenological variation is primarily generated by rapid organismal responses (i.e., plasticity) or local adaptation remains unresolved. Here, we used 1,038,027 herbarium specimens representing 1,605 species to measure flowering time sensitivity to temperature over time (‘Stime’) and space (‘Sspace’). By comparing these estimates, we inferred how adaptation and plasticity historically influenced phenology along temperature gradients and how their contributions vary among species with different phenology and native climates, and among ecoregions differing in species composition. Sspace and Stime were highly positively correlated (r = 0.87), of similar magnitude, and more frequently consistent with plasticity than adaptation. Apparent plasticity and adaptation generated earlier flowering in spring, limited responsiveness in summer, and delayed flowering in fall in response to temperature increases. Nonetheless, ecoregions differed in the relative contributions of adaptation and plasticity, from consistently greater importance of plasticity (e.g., Southeastern USA Plains) to their nearly equal importance throughout the season (e.g., Western Sierra Madre Piedmont). Our results support the hypothesis that plasticity is the primary driver of flowering time variation along climatic gradients, with local adaptation having a widespread but comparatively limited role.
Hierarchical bionic neural network-like architecture towards high- performance microwave absorption and corrosion protection
Authors: Li Shuaizhen , Xie Tianwen , Ma Lin , Liu Daheng , Huang Nan , Liu Wei , Ma Song , Zhang Zhidong
Published: July 2023

It remains challenging to develop multifunctional electromagnetic wave (EMW) absorbers to enhance the environmental adaptability and survivability of target devices in harsh environment. Herein, this study innovatively constructs a three-dimensional (3D) hierarchical bionic neural network-like Ni3Fe@N-doped carbon nanotube@Carbon foam (Ni3Fe@NCNT@CF) composite via dip-coating and carbonization operation, realizing the integration of microwave absorption and corrosion protection. The optimal Ni3Fe@NCNT@CF composite demonstrates competitive EMW absorption with a minimum reflection loss of −51.5 dB and a maximum effective absorption bandwidth (EAB) of 6.4 GHz at 10 wt%, due to superior interlinked conductive channels (with flexible and adjustable conduction loss) and magnetic-dielectric matching of the 3D hierarchical bionic neural network, including 3D CF skeleton (matrical neural network), short CNTs network (enrich “dendrites”), and ultra-long CNTs network (enhance “axons”). Besides, Ni3Fe@NCNT@CF composite exhibits a reliable anti-corrosion performance with a low corrosion current density ~10-8 A·cm-2 after 30 days of immersion in corrosive medium, owing to the physical shield provided by the impermeable, inert CNT shells and carbon foam. Our findings may provide design inspiration of versatile EMW materials for applications in complicated environments.
Relationship Between Fear of Earthquakes and Sleep Quality in Patients with Hypertension Living in Istanbul
Authors: Koç Zeynep , Meterelliyoz Kumru Yaşar , Etlik Arzu Aksoy , Sürücü Merve , Vardal Tuba Olcay , Çetinavcı Dilara , Akın Seydahmet
Published: July 2023

Introduction:
It is known that emotional stress affects individuals with hypertension. Sleep quality is also associated with blood pressure regulation. In our study, we aimed to investigate the effect of Kahramanmaraş earthquakes on sleep quality in individuals with hypertension residing in Istanbul.
Method
This randomized and controlled study included hypertensive patients who visited the internal medicine outpatient clinic between March 7, 2023 and May 7, 2023. Individuals with hypertension consulted a psychiatrist for the presence of earthquake fear. The Pittsburg Sleep Quality Index (PSQI) was used to assess sleep quality.
Results
Seventy patients with hypertension aged 35–64 years, 35 with earthquake fear and 35 without, were included. While the mean PSQI sleep quality score of the group with earthquake fear was 7.26 ± 3.94, the mean score of the group without earthquake fear was 5.17 ± 3.89, which was higher (p = 0.013; p < 0.05). Based on the presence of earthquake fear, poor sleep quality was found in 71.4% (n = 25) of patients with earthquake fear and in 42.9% (n = 15) without, and a statistically significant difference was found (p = 0.016; p < 0 .05). The risk of impaired sleep quality in the earthquake-fear group was 3.333 times higher than that in the without earthquake-fear group (ODSS: 3.333; 95%CI 1.235–8.997).
Conclusion
Our study has shown that the sleep quality of individuals with hypertension residing in Istanbul is adversely affected by the fear of earthquakes. We believe that it may be useful to review the pharmacological treatments of individuals with hypertension whose sleep quality is impaired owing to the fear of earthquakes and provide close psychological support.
Landslide Hazard Mapping in Son La Province, Vietnam Under Climate Change Scenarios for 2025 & 2050
Authors: Tuan Le Canh , Khanh Nguyen Quoc , Giang Nguyen Khac Hoang
Published: July 2023

In recent years, landslides in mountainous provinces are increasing. Whenever the rainy season comes, landslides occur, causing casualties to people and damages to the infrastructure. Son La, a mountainous province in the North of Vietnam, has suffered significant damage from landslides. Therefore, the purpose of this research is to introduce an application of the analytic hierarchy process (AHP) method with the integration of representative concentration pathways (RCP) scenario 4.5 to study landslides in Son La province, Vietnam. With the integration of the digital elevation model (DEM) and collected data into ArcGIS software, we obtained different factor maps: Slope map, Aspect map, Cleavage density map, River density map, Rainfall map, Lithology map, Fault density map, Vegetation cover map, Distance to roads. These were the important input parameters for the AHP method. The data collected from 2009 to the present and the research documents of the authors based on the field investigations in 2018, 2019, 2020, and 2021 were the basis for us to complete this article. The landslide risk maps with the integration of maximum daily rainfall from the climate change scenario for 2025 and 2050 were produced. The results revealed that the landslide risk in Son La province increases with time. The results from this research will assist local authorities in land use planning, disaster control, and achieving sustainable development goals.
Functional Precision Medicine Enhances Clinical Outcomes of Relapsed/Refractory Pediatric and Adolescent Cancer Patients
Authors: Azzam Diana , Rocha Arlet Acanda de la , Berlow Noah , Fader Maggie , Coats Ebony , Saghira Cima , Espinal Paula , Galano Jeanette , Khatib Ziad , Abdella Haneen , Maher Ossama , Vorontsova Yana , Andrade-Feraud Cristina , Daccache Aimee , Reis Victoria , Holcomb Baylee , Ghurani Yasmin , Rimblas Lilliam , Guilarte Tomas , Hu Nan , Salyakina Daria , Jacome Alexa
Published: July 2023

Current genomics-driven precision oncology identifies actionable mutations in < 10% of cancer patients. Pediatric cancer is especially challenging due to limited mutations and fewer genomics-guided options. Functional precision medicine (FPM) addresses this by integrating genomic profiling with rapid, high-throughput functional ex vivo drug testing on live patient-derived cells. However, there is lack of FPM prospective data showing clinical utility in pediatric cancers. In this prospective, non-randomized, single-arm study (NCT03860376), we investigated feasibility and impact of FPM in pediatric/adolescent with refractory/relapsed solid and hematologic cancers. Of 25 patients, 19 (76%) had FPM data reviewed by the FPM tumor board within four weeks (FPMTB), meeting the primary outcome of the study. Additionally, six patients received FPM-guided treatment. Among these 6 patients, 83% (5 patients) experienced a greater than 1.3-fold improved progression-free survival compared to their previous therapy, and together demonstrated a significant increase in progression-free survival and objective response rate versus physician’s choice-treated patients (8 patients). Post-hoc analysis showed that patients with the same subtype of cancer do not cluster together, reinforcing the concept of optimizing cancer treatments one patient at a time (n-of-1 approach). Additionally, our study used a novel artificial intelligence/machine learning (AI/ML) platform that leveraged drug responses and sequencing data to identify novel biomarkers of drug efficacy and gain potential mechanistic insights within specific subsets of pediatric cancer patients. The findings from our proof-of-principle study illustrate the impact of FPM for relapsed/refractory pediatric/adolescent cancer patients, highlight future integrations of FPM and AI/ML, and support ongoing patient cohort expansion (NCT05857969).
Point-MDA: Progressive Point Cloud Analysis for Extreme Multi-scale Detail Activation
Authors: Li Manwen , Zhao Yanming , Wang Chun , Zhou Yun , Jiang Wei
Published: July 2023

The point cloud is a form of three-dimensional data that comprises various detailed features at multiple scales. Due to this characteristic and its irregularity, point cloud analysis based on deep learning is challenging. While previous works utilize the sampling-grouping operation of PointNet++ for feature description and then explore geometry by means of sophisticated feature extractors or deep networks, such operations fail to describe multi-scale features effectively. Additionally, these techniques have led to performance saturation. And it is difficult for standard MLPs to directly ``mine" point cloud. To address above problems, we propose the Detail Activation (DA) module, which encodes data based on Fourier transform after sampling and grouping. We activate the channels at different frequency levels from low to high in the DA module to gradually recover finer point cloud details. As training progresses, the proposed Point-MDA can uncover local and global geometries of point cloud progressively. Our experiments show that Point-MDA achieves superior classification accuracy, outperforming PointNet++ by 3.3\% and 7.9\% in terms of overall accuracy on the ModelNet40 and ScanObjectNN dataset, respectively. Furthermore, it accomplishes this without employing complicated operations, while exploring the full potential of PointNet++.
Whole-brain structural connectivity predicts cognitive deficits in pretreated glioma patients
Authors: Friedrich Michel , Filss Christian P. , Lohmann Philipp , Mottaghy Felix M. , Stoffels Gabriele , Lucas Carolin Weiss , Ruge Maximilian I. , Shah N. Jon , Caspers Svenja , Langen Karl-Josef , Fink Gereon R. , Galldiks Norbert , Kocher Martin
Published: July 2023

Purpose Glioma patients frequently suffer from cognitive dysfunction potentially caused by tumor invasion or treatment effects. We hypothesized that cognitive functioning in pretreated glioma patients critically depends on the maintained structural connectivity of multiple brain networks. Methods The study included 121 pretreated glioma patients (median age, 52 years; median ECOG score 1; CNS WHO grade 3 or 4) who had biopsy or resection plus chemoradiation. Cognitive performance was assessed by ten tests in five main cognitive domains 14 (1-214) months after therapy initiation. Hybrid amino acid PET/MRI using the tracer O-(2-[18F]fluoroethyl)-L-tyrosine, a network-based cortical parcellation, and advanced tractography methods were used to generate whole-brain fiber count-weighted connectivity matrices. The matrices were applied to cross-validated machine learning-based models to identify fiber connections and underlying networks predictive for cognitive performance in the evaluated domains. Results Compared to healthy controls (n = 121), the cognitive scores were significantly lower in nine cognitive tests. The models well predicted 7/10 scores (median correlation coefficient, 0.47; range, 0.39–0.57) from 24–230 (0.5–4.6%) of the possible connections/edges, 84% were between nodes of different networks. Critically involved cortical regions/nodes (≥ 10 adjacent predictive edges) included predominantly left-sided nodes of the visual, somatomotor, dorsal/ventral attention, and default mode networks. Highly critical nodes (≥ 15–20 edges) included the default-mode network’s left temporal and bilateral posterior cingulate cortex. Conclusions These results suggest that the cognitive performance of pretreated glioma patients is strongly related to structural connectivity between multiple brain networks and depends on the integrity of known network hubs also involved in other neurological disorders.
Wildfire Detection Via Transfer Learning: A Survey
Authors: Hong Ziliang , Hamdan Emadeldeen , Zhao Yifei , Ye Tianxiao , Pan Hongyi , Cetin Ahmet Enis
Published: July 2023

This paper presents a comprehensive survey of publicly available neural network models specifically designed for detecting wildfires using regular visible-range cameras positioned on hilltops or forest lookout towers. The surveyed models are first pre-trained on the ImageNet-1K dataset and then fine-tuned on a custom wildfire dataset to enhance their performance. Evaluations are conducted on diverse wildfire images, enabling a thorough assessment of their capabilities. The survey findings provide valuable insights for individuals interested in leveraging transfer learning techniques for wildfire detection. Among the examined models, Swin Transformer-tiny achieves the highest Area Under the Curve (AUC) value, indicating strong overall performance in distinguishing wildfire events. However, ConvNext-tiny stands out for its exceptional ability to detect all instances of wildfires while maintaining the lowest false alarm rate within our dataset. These results highlight the varying strengths of different neural network models and offer valuable guidance for selecting an appropriate model based on specific detection requirements and priorities.
Six-Month Post-Intensive Care Outcomes During High and Low Bed Occupancy due to the COVID-19 Pandemic: a Multicenter Prospective Cohort Study
Authors: Castro-Ávila Ana , Merino-Osorio Catalina , González-Seguel Felipe , Camus-Molina Agustín , Muñoz-Muñoz Felipe , Leppe Jaime
Published: July 2023

Purpose: The COVID-19 pandemic can be seen as a natural experiment to test how bed occupancy affects post-intensive care unit (ICU) patient's functional outcomes. Therefore, we compared by bed occupancy the frequency of mental, physical, and cognitive impairments in patients admitted to ICU during the COVID-19 pandemic.
Methods: Prospective cohort of adults mechanically ventilated >48 hours in one of 19 ICUs in seven Chilean public and private hospitals. Ninety per cent of nationwide beds occupied was the cut-off for low versus high bed occupancy. At ICU discharge, 3- and 6-month follow-up, we assessed disability using the World Health Organization Disability Assessment Schedule 2.0, quality of life, mental, physical, and cognitive outcomes following the core outcome set for acute respiratory failure.
Results: 252 eligible participants were enrolled, 103(41%) during low and 149(59%) during high occupancy. Patients treated during high occupancy were younger (P50[P25-P75]: 55[44-63] vs 61[51-71]; p<0.001), more likely to be admitted due to COVID-19 (126[85%] vs 65[63%]; p<0.001), and have higher education qualification (94[63%] vs 48[47%]; p=0.03). No differences were found in the frequency of at least one mental, physical or cognitive impairment by bed occupancy at ICU discharge (low vs high: 93% vs 91%; p=0.6), 3-month (74% vs 63%; p=0.2) and 6-month (57% vs 57%; p=0.9) follow-up.
Conclusions: There were no differences in post-ICU outcomes between high and low bed occupancy. Most patients had at least one mental, physical or cognitive impairment at ICU discharge, which remained high at 6-month follow-up.
Treatment of mine wastewater using a coal fly ash-based coagulant: Coagulation adsorption isotherm study
Authors: Apua Momboyo Clotilde , Simate Geoffrey S. , Bada Samson
Published: July 2023

The authors have requested that this preprint be removed from Research Square.
Effect of Climate fluctuation in Building construction
Authors: Hussein Abtehaj , Hasan Taha , Ibrahim Amer M.
Published: July 2023

The largest industry in America is construction, which accounts for 10% of jobs and 10% of the GNP. It has a high labor intensity, a low technology intensity, and has had mediocre profitability and competitiveness over the past 20 years. The purpose of the study is to look at the factors that contribute to temperature, humidity, and CO2 variations during building construction and how they affect such buildings.
Short and long range 2D 15N-15N NMR correlations among peptide groups by novel solid state dipolar mixing schemes
Authors: Wi Sungsool , Li Conggang , Pham Karen , Lee Woonghee , Frydman Lucio
Published: July 2023

A recently developed homonuclear dipolar recoupling scheme, Adiabatic Linearly FREquency Swept reCOupling (AL FRESCO), was applied to record two-dimensional (2D) 15N-15N correlations on uniformly 15N-labeled GB1 powders. A major feature exploited in these 15N-15N correlations was AL FRESCO’s remarkably low RF power demands, which enabled seconds-long mixing schemes when establishing direct correlations. These 15N-15N mixing schemes proved efficient regardless of the magic-angle spinning (MAS) rate and, being nearly free from dipolar truncation effects, they enabled the detection of long-range, weak dipolar couplings, even in the presence of strong short-range dipolar couplings. This led to a connectivity information that was significantly better than that obtained with spontaneously proton-driven, 15N spin-diffusion experiments. An indirect approach producing long-range 15N-15N correlations was also tested, relying on short (ms-long) 1HN-1HN mixings schemes while applying AL FRESCO chirped pulses along the 15N channel. These indirect mixing schemes produced numerous long-distance Ni-Ni±n (n correlations, that might be useful for characterizing three-dimensional arrangements in proteins. Once again, these AL FRESCO mediated experiments proved more informative than variants based on spin-diffusion-based 1HN-1HN counterparts.