bluuebunny/crossref_metadata_2025 huggingface dataset:
Climate and disease: tackling coffee brown‐eye spot with advanced forecasting models
Authors: de Oliveira Aparecido Lucas Eduardo , de Lima Rafael Fausto , Torsoni Guilherme Botega , Lorençone João Antonio , Lorençone Pedro Antonio , de Souza Rolim Glauco
Published: February 2024

Background

Climate influences the interaction between pathogens and their hosts significantly. This is particularly evident in the coffee industry, where fungal diseases like Cercospora coffeicola, causing brown‐eye spot, can reduce yields drastically. This study focuses on forecasting coffee brown‐eye spot using various models that incorporate agrometeorological data, allowing for predictions at least 1 week prior to the occurrence of disease. Data were gathered from eight locations across São Paulo and Minas Gerais, encompassing the South and Cerrado regions of Minas Gerais state. In the initial phase, various machine learning (ML) models and topologies were calibrated to forecast brown‐eye spot, identifying one with potential for advanced decision‐making. The top‐performing models were then employed in the next stage to forecast and spatially project the severity of brown‐eye spot across 2681 key Brazilian coffee‐producing municipalities. Meteorological data were sourced from NASA's Prediction of Worldwide Energy Resources platform, and the Penman–Monteith method was used to estimate reference evapotranspiration, leading to a Thornthwaite and Mather water‐balance calculation. Six ML models – K‐nearest neighbors (KNN), artificial neural network multilayer perceptron (MLP), support vector machine (SVM), random forests (RF), extreme gradient boosting (XGBoost), and gradient boosting regression (GradBOOSTING) – were employed, considering disease latency to time define input variables.

Results

These models utilized climatic elements such as average air temperature, relative humidity, leaf wetness duration, rainfall, evapotranspiration, water deficit, and surplus. The XGBoost model proved most effective in high‐yielding conditions, demonstrating high precision and accuracy. Conversely, the SVM model excelled in low‐yielding scenarios. The incidence of brown‐eye spot varied noticeably between high‐ and low‐yield conditions, with significant regional differences observed. The accuracy of predicting brown‐eye spot severity in coffee plantations depended on the biennial production cycle. High‐yielding trees showed superior results with the XGBoost model (R2 = 0.77, root mean squared error, RMSE = 10.53), whereas the SVM model performed better under low‐yielding conditions (precision 0.76, RMSE = 12.82).

Conclusion

The study's application of agrometeorological variables and ML models successfully predicted the incidence of brown‐eye spot in coffee plantations with a 7 day lead time, illustrating that they were valuable tools for managing this significant agricultural challenge. © 2024 Society of Chemical Industry.
Complex insoluble dietary fiber alleviates obesity and liver steatosis, and modulates the gut microbiota in C57BL/6J mice fed a high‐fat diet
Authors: Liu Zurui , Dai Juan , Liu Ruijia , Shen Ziyi , Huang Ai , Huang YuKun , Wang Lijun , Chen Pengfei , Zhou Zheng , Xiao Hang , Chen Xianggui , Yang Xiao
Published: February 2024

BACKGROUND

Obesity has been demonstrated as a risk factor that seriously affects health. Insoluble dietary fiber (IDF), as a major component of dietary fiber, has positive effects on obesity, inflammation and diabetes.

RESULTS

In this study, complex IDF was prepared using 50% enoki mushroom IDF, 40% carrot IDF, and 10% oat IDF. The effects and potential mechanism of complex IDF on obesity were investigated in C57BL/6 mice fed a high‐fat diet. The results showed that feeding diets containing 5% complex IDF for 8 weeks significantly reduced mouse body weight, epididymal lipid index, and ectopic fat deposition, and improved mouse liver lipotoxicity (reduced serum levels of alanine aminotransferase, aspartate aminotransferase, and alkaline phosphatase), fatty liver, and short‐chain fatty acid composition. High‐throughput sequencing of 16S rRNA and analysis of fecal metabolomics showed that the intervention with complex IDF reversed the high‐fat‐diet‐induced dysbiosis of gut microbiota, which is associated with obesity and intestinal inflammation, and affected metabolic pathways, such as primary bile acid biosynthesis, related to fat digestion and absorption.

CONCLUSION

Composite IDF intervention can effectively inhibit high‐fat‐diet‐induced obesity and related symptoms and affect the gut microbiota and related metabolic pathways in obesity. Complex IDF has potential value in the prevention of obesity and metabolic syndrome. © 2024 Society of Chemical Industry.
A pilot randomized controlled trial of online written exposure therapy delivered by peer coaches to veterans with posttraumatic stress disorder
Authors: McLean Carmen P. , Malek Nadia , Straud Casey L.
Published: February 2024

This pilot randomized clinical trial (RCT) sought to examine the preliminary efficacy of an internet‐based version of written exposure therapy delivered to veterans through an online program supported by peer coaches. Veterans (N = 124) with clinically significant posttraumatic stress disorder (PTSD) symptoms were randomly assigned to imaginal exposure either via writing (written exposure) or verbal recounting (verbal exposure). The online treatment involved four to eight sessions of imaginal exposure preceded and followed by an online chat with a peer coach. Participants completed assessments at baseline, posttreatment, and 3‐month follow‐up. Half of the participants never started treatment; among those who started treatment, the mean number of sessions completed was 4.92. At posttreatment, participants in both conditions reported clinically meaningful improvements in PTSD symptoms, d = 1.35; depressive symptoms, d = 1.10; and functioning, d = 0.39. Although participants in both treatment conditions demonstrated significant improvements in PTSD symptom severity, equivalence results were inconclusive, as the 95% confidence interval of the change score difference exceeded the specified margin and overlapped with 0. Estimated mean change scores demonstrated that both conditions showed significant reductions at posttreatment and follow‐up. Although engagement with the online program was a significant challenge, the findings suggest that written exposure therapy is effective for improving PTSD symptoms, depressive symptoms, and functioning when adapted for internet‐based delivery and facilitated by peer coaches. Using technology to deliver exposure therapy and task‐shifting the role of the therapist to peer coaches are promising strategies to increase access to effective PTSD care.
LEADING THROUGH DISASTERS AND DEPARTURES: HOW TO PREPARE FOR & SUCCEED WITH UNCERTAINTY AND CHANGE
Authors: Esposito Patrick
Published: February 2024

The author, who is both a Chief Executive Officer/CEO and an attorney, writes about disaster planning and succession planning to “achieve the goals and aspirations for your organization without stumbling along the way or falling victim to a complete collapse when disasters and difficulties strike and impact your operations or personnel.” This means dealing effectively with uncertainty and change, critical/strategic decision categories, and “Committing to a regularized process for examining how to manage uncertainty and potential changes.” He presents results from surveys he has conducted with a variety of leaders, each with the results to questions about the following, in his words 1. Do You Have Processes in Place for Assessing, Deciding on, Planning, and Implementing Change? 2. What Has Been Your Most Difficult Organizational Phase? 3. What will be your most challenging future issues? 4. How do you plan for managing disasters? He discusses his process/framework of assessing, deciding, planning, and implementing. Each of these has its own figure, visualizing the steps involved. As he notes in the conclusion, “The COVID‐19 pandemic probably taught you that you cannot predict everything you and your organization will face.”
1,3,4,5‐Tetrasubstituted Poly(1,2,3‐triazolium) Obtained through Metal‐Free AA+BB Polyaddition of a Diazide and an Activated Internal Dialkyne
Authors: Akacha Rania , Abdelhedi‐Miladi Imen , Serghei Anatoli , Ben Romdhane Hatem , Drockenmuller Eric
Published: February 2024

A tetra(ethylene glycol)‐based 1,3,4,5‐tetrasubstituted poly(1,2,3‐triazolium) is synthesized in two steps including: i) the catalyst‐free polyaddition of a diazide and an activated internal dialkyne and ii) the N‐alkylation of the resulting 1,2,3‐triazole groups. In order to provide detailed structure/properties correlations different analogs are also synthesized. First, parent poly(1,2,3‐triazole)s are obtained via AA+BB polyaddition using copper(I)‐catalyzed alkyne‐azide cycloaddition or metal‐free thermal alkyne‐azide cycloaddition (TAAC). Poly(1,2,3‐triazole)s with higher molar masses are obtained in higher yields by TAAC polyaddition. A 1,3,4‐trisubstituted poly(1,2,3‐triazolium) structural analog obtained by TAAC polyaddition using a terminal activated dialkyne and subsequent N‐alkylation of the 1,2,3‐triazole groups enables discussing the influence of the methyl group in the C‐4 or C‐5 position on thermal and ion conducting properties. Obtained polymers are characterized by 1H, 13C, and 19F NMR spectroscopy, differential scanning calorimetry, thermogravimetric analysis, size exclusion chromatography, and broadband dielectric spectroscopy. The targeted 1,3,4,5‐tetrasubstituted poly(1,2,3‐triazolium) exhibits a glass transition temperature of −23 °C and a direct current ionic conductivity of 2.0 × 10−6 S cm−1 at 30 °C under anhydrous conditions. The developed strategy offers opportunities to further tune the electron delocalization of the 1,2,3‐triazolium cation and the properties of poly(1,2,3‐triazolium)s using this additional substituent as structural handle.
3D Printing of Capacitive Pressure Sensors with Tuned Wide Detection Range and High Sensitivity Inspired by Bio‐Inspired Kapok Structures
Authors: Jin Qingxin , Wang Chengyun , Wu Han , Luo Xin , Li Jiaqi , Ma Guangmeng , Li Yu , Luo Chunyi , Guo Fawei , Long Yu
Published: February 2024

Flexible pressure sensors have drawn considerable attention for their potential applications as electronic skins with both sensitivity and pressure response range. Although the introduction of surface microstructures effectively enhances sensitivity, the confined volume of their compressible structures results in a limited pressure response range. To address this issue, a biomimetic kapok structure is proposed and implemented for constructing the dielectric layer of flexible capacitive pressure sensors employing 3D printing technology. The structure is designed with easily deformable concave and rotational structures, enabling continuous deformation under pressure. This design results in a significant expansion of the pressure response range and improvement in sensitivity. Further, the study purposively analyses crucial parameters of the devised structure that affect its compressibility and stability. These include the concave angle θ, height ratio d1/d2, rotation angle α, and width k. As a result, the ultimate pressure sensors demonstrate remarkable features such as high sensitivity (≈2.38 kPa−1 in the range of 0–10 kPa), broad detection range (734 kPa), fast response time (23 ms), and outstanding pressure resolution (0.4% at 500 kPa). This study confirms the viability of bionic structures for flexible sensors, and their potential to expand the scope of wearable electronic devices.
Further delineation of Wiedemann‐Rautenstrauch syndrome linked with POLR3A
Authors: Khan Amjad , Al Shamsi Bushra , Al Shehhi Maryam , Kashgari Amna A. , Al Balushi Aaisha , Al Dihan Fahad A. , Alghamdi Mohannad A. , Manal Abothnain , González‐Álvarez Ana C. , Arold Stefan T. , Eyaid Wafaa
Published: February 2024

Wiedemann‐Rautenstrauch Syndrome (WRS; MIM 264090) is an extremely rare and highly heterogeneous syndrome that is inherited in a recessive fashion. The patients have hallmark features such as prenatal and postnatal growth retardation, short stature, a progeroid appearance, hypotonia, facial dysmorphology, hypomyelination leukodystrophy, and mental impairment. Biallelic disease‐causing variants in the RNA polymerase III subunit A (POLR3A) have been associated with WRS. Here, we report the first identified cases of WRS syndrome with novel phenotypes in three consanguineous families (two Omani and one Saudi) characterized by biallelic variants in POLR3A. Using whole‐exome sequencing, we identified one novel homozygous missense variant (NM_007055: c.2456C>T; p. Pro819Leu) in two Omani families and one novel homozygous variant (c.1895G>T; p Cys632Phe) in Saudi family that segregates with the disease in the POLR3A gene. In silico homology modeling of wild‐type and mutated proteins revealed a substantial change in the structure and stability of both proteins, demonstrating a possible effect on function. By identifying the homozygous variants in the exon 14 and 18 of the POLR3A gene, our findings will contribute to a better understanding of the phenotype‐genotype relationship and molecular etiology of WRS syndrome.
Analytical approach to solving linear diffusion–advection–reaction equations with local and nonlocal boundary conditions
Authors: Rodrigo M. , Thamwattana N.
Published: February 2024

Initial–boundary value problems for a linear diffusion–advection–reaction equation are considered, with general nonhomogeneous linear boundary conditions and general linear nonlocal boundary conditions. Analytical solutions are obtained using an embedding method. The solutions are expressed in terms of time‐varying functions that satisfy coupled linear Volterra integral equations of the first kind. A boundary element method is applied to numerically solve the integral equations. Three examples are given to demonstrate the accuracy of the numerical solutions when compared with the analytical solutions. The embedding method is applicable to problems with bounded and unbounded spatial domains.
On the design of ideal pattern diversity antennas with low mutual coupling using the golden angle concept
Authors: Gudibandi Bharath Reddy , Nuthakki Venkata Rajashekar , Murugan Harish Adhithya , Damodaran Sriram Kumar
Published: February 2024

In this paper, we come up with a unique technique to generate the ideal pattern diversity with the help of 24 Vivaldi antennas. With the help of a mathematical concept called golden angle, the 24 antenna elements are arranged in such a way that the radiation patterns will never overlap and the mutual coupling will be very low. It is also verified from the simulations and the measured results that the envelope correlation coefficient is less than 0.01 in the 3–4.2 GHz which is a sub‐6 GHz band for 5G. This same concept can be extended to a greater number of antennas also.
Design of dispersion‐reconfigurable phaser using stepped‐impedance line
Authors: Lei Haoling , Huang Yi , Duan Chaijie , Zhang Qingfeng
Published: February 2024

This paper proposes a dispersion‐reconfigurable reflection‐type phaser based on the stepped‐impedance microstrip line structure. By configuring “ON” and “OFF” states of switches, the proposed phaser exhibits positive‐slope, negative‐slope, and zero‐slope linearly dispersive group delay responses. For proof‐of‐concept demonstration, we use line connection/disconnection to mimic the ON/OFF states of real switches. Three prototypes are hence fabricated to represent the three different states. The experimental results agree well with the expected responses, which finally validate the proposed concept.
High pain reported at 3 months post‐total knee arthroplasty often persists for the next 3 years and is associated with reduced function and quality of life
Authors: Johns Nathan , Naylor Justine , McKenzie Dean , Brady Bernadette , Olver John
Published: February 2024

Background and Aims

Five to ten percent of people having a knee arthroplasty for osteoarthritis continue to experience high pain levels more than 3 months after surgery. The primary aim of this study was to determine the relative risk (RR) of having high pain at 12 and 36 months based on the presence of high pain at 3 and 12 months, respectively.

Methods

A retrospective analysis of data from a prospective study of participants who had a total knee arthroplasty for osteoarthritis. A score of ≤14 on the Oxford Knee Pain Subscale was defined as ‘High Pain’, and RRs were calculated comparing those with high or low pain.

Results

There were 718 participants and 13.8% reported high pain at any time point, 2.5% reported high pain at all time points and 10.3% and 4.7% and 6.6% reported high pain at 3‐, 12‐ and 36‐months, respectively, post‐surgery. For participants with high pain at 3 months, 33.8% had high pain at 12 months with a RR of 24.2 (95% CI 11.7–49.8, p < 0.001) and 35.1% had high pain at 36 months with a RR of 10.8 (95% CI 6.4–18.2, p < 0.001). For participants with high pain at 12 months, 67.6% had high pain at 36 months, with a RR of 19.3 (95% CI 12.2–30.4, p < 0.01).

Conclusions

Although high pain rates are low overall following knee arthroplasty, once high pain is established there is an elevated RR of it persisting at 12‐ and 36 months post‐surgery.

Trial registration

The data were collected in the Evidence‐based Processes and Outcomes of Care (EPOC) study, ClinicalTrials.gov Identifier: NCT01899443.
The impact of myasthenia gravis severity on work and daily activities
Authors: Pesa Jacqueline , Choudhry Zia , de Courcy Jonathan , Barlow Sophie , Chatterton Emma , Thomas Owen , Gibson Gregor , Hahn Bethan , Govindarajan Raghav
Published: February 2024

Introduction/Aims

People with myasthenia gravis (MG) experience impaired quality of life. However, the impact of MG symptoms on work productivity has not been well‐studied. We aimed to evaluate this impact and to examine associations between disease severity and the degree of impairment.

Methods

Data were drawn from the Adelphi MG Disease‐Specific Programme™, a multinational (USA, France, Germany, Italy, Spain, UK) survey completed by physicians and their patients with MG in 2020. Patient‐reported measures included the Work Productivity and Activity Impairment (WPAI): Specific Health Problem questionnaire.

Results

The WPAI questionnaire was completed by 330 patients. Among those currently employed, the mean percentage of work time missed (absenteeism) was 13.3% (N = 116), percentage impairment of productivity at work (presenteeism) was 26.7% (N = 121), and overall work impairment was 30.0% (N = 110). Across all patients, impairment of non‐work‐related activities due to health problems (ADL impairment) was 39.2% (N = 330). Regression analysis indicated that impairment differed according to MG Foundation of America (MGFA) class (p = .0147, p < .0001, p < .0001 and p < .0001 for absenteeism, presenteeism, overall work impairment and ADL impairment, respectively). Being MGFA class III/IV was a predictor of presenteeism, overall work impairment and ADL impairment in a predictor model.

Discussion

Patients with MG experience substantial work impairment particularly those with more severe symptoms, highlighting an important way in which patient quality of life is negatively affected. More effective treatment strategies would enable patients to lead more productive lives and could impact decisions relating to work and career.
Enhanced methods for the weight constrained shortest path problem
Authors: Ahmadi Saman , Tack Guido , Harabor Daniel , Kilby Philip , Jalili Mahdi
Published: February 2024

The classic problem of constrained pathfinding is a well‐studied, yet challenging, network optimization problem with a broad range of applications in various areas such as communication and transportation. The weight constrained shortest path problem (WCSPP), the base form of constrained pathfinding with only one side constraint, aims to plan a cost‐optimum path with limited weight/resource usage. Given the bi‐criteria nature of the problem (i.e., dealing with the cost and weight of paths), methods addressing the WCSPP have some common properties with bi‐objective search. This article leverages the recent state‐of‐the‐art techniques in both constrained pathfinding and bi‐objective search and presents two new solution approaches to the WCSPP on the basis of A* search, both capable of solving hard WCSPP instances on very large graphs. We empirically evaluate the performance of our algorithms on a set of large and realistic problem instances and show their advantages over the state‐of‐the‐art algorithms in both time and space metrics. This article also investigates the importance of priority queues in constrained search with A*. We show with extensive experiments on both realistic and randomized graphs how bucket‐based queues without tie‐breaking can effectively improve the algorithmic performance of exhaustive A*‐based bi‐criteria searches.
Solving the probabilistic drone routing problem: Searching for victims in the aftermath of disasters
Authors: Almeida Coco Amadeu , Duhamel Christophe , Santos Andréa Cynthia , Haddad Matheus Nohra
Published: February 2024

Several major industrial disasters happen each year around the world. They usually involve limited accessibility, poor ground conditions, and toxic wastes. As a consequence, this reduces the efficiency of humanitarian operations. In such a context, flying drones may be a viable alternative: faster, no dependency on ground conditions, and larger areas scanned. They are also better suited for following the population and the crisis dynamic. For such a purpose, various issues have to be addressed such as defining and optimizing the drone's routes, their energy consumption, choosing the relay points for recharging equipment, among others. In this study, several additional features from existing works are considered: first, a probability of identifying individuals is defined. Thus, each node can be scanned several times in order to improve the observation. In addition, the nodes are prioritized according to a given heatmap. The probabilistic drone routing problem (PDRP) consists of finding a route, that is, a sequence of trips, for each drone such that the sum of the expected number of identified individuals on all routes is maximized. Constraints on energy consumption, collision avoidance and drone‐base assignment are considered. We propose a heuristic and metaheuristics based on the adaptive large neighborhood search for the PDRP. The methods are tested on theoretical instances, as well as on a case study of the Beirut Port explosion on August 4, 2020, in order to analyze the performance of the proposed methods.
Accelerating structural dynamics simulations with localised phenomena through matrix compression and projection‐based model order reduction
Authors: Agathos Konstantinos , Vlachas Konstantinos , Garland Anthony , Chatzi Eleni
Published: February 2024

In this work, a novel approach is introduced for accelerating the solution of structural dynamics problems in the presence of localised phenomena, such as cracks. For this category of problems, conventional projection‐based Model Order Reduction (MOR) methods are either limited with respect to the range of system configurations that can be represented or require frequent solutions of the Full Order Model (FOM) to update the low‐dimensional spaces, in which solutions are represented. In the proposed approach, low‐dimensional spaces, constructed for the healthy structure, are enriched with appropriately selected columns of the flexibility matrix of the system. It can be shown that these spaces contain the solution to the original problem for the static case, while their dimension is much smaller. In order to allow their online construction for arbitrary localised features, the full flexibility matrix of the system should be available. To this end, a hierarchical representation is used for the matrices involved, allowing to compute the flexibility matrix efficiently and with reduced memory requirements. The resulting method offers significant speedups, without sacrificing the flexibility and accuracy of the full order model. The performance and limitations of the approach are studied through a series of examples in structural dynamics.
Longitudinal reduction in brain volume in patients with schizophrenia and its association with cognitive function
Authors: Yamazaki Ryuichi , Matsumoto Junya , Ito Satsuki , Nemoto Kiyotaka , Fukunaga Masaki , Hashimoto Naoki , Kodaka Fumitoshi , Takano Harumasa , Hasegawa Naomi , Yasuda Yuka , Fujimoto Michiko , Yamamori Hidenaga , Watanabe Yoshiyuki , Miura Kenichiro , Hashimoto Ryota
Published: February 2024

Establishing a brain biomarker for schizophrenia is strongly desirable not only to support diagnosis by psychiatrists but also to help track the progressive changes in the brain over the course of the illness. A brain morphological signature of schizophrenia was reported in a recent study and is defined by clusters of brain regions with reduced volume in schizophrenia patients compared to healthy individuals. This signature was proven to be effective at differentiating patients with schizophrenia from healthy individuals, suggesting that it is a good candidate brain biomarker of schizophrenia. However, the longitudinal characteristics of this signature have remained unclear. In this study, we examined whether these changes occurred over time and whether they were associated with clinical outcomes. We found a significant change in the brain morphological signature in schizophrenia patients with more brain volume loss than the natural, age‐related reduction in healthy individuals, suggesting that this change can capture a progressive morphological change in the brain. We further found a significant association between changes in the brain morphological signature and changes in the full‐scale intelligence quotient (IQ). The patients with IQ improvement showed preserved brain morphological signatures, whereas the patients without IQ improvement showed progressive changes in the brain morphological signature, suggesting a link between potential recovery of intellectual abilities and the speed of brain pathology progression. We conclude that the brain morphological signature is a brain biomarker that can be used to evaluate progressive changes in the brain that are associated with cognitive impairment due to schizophrenia.
Service load analysis and ply stacking optimization for composite tool of aerospace cryogenic tank
Authors: Guan Chenglong , Chi Tongming , Zhan Lihua , Yao Shunming , Chen Junhao , Xie Liping , Xiao Yu
Published: February 2024

The integrated manufacturing of aerospace composite cryogenic tanks is crucial for enhancing payload efficiency, reducing costs, and leading the aerospace industry upgrade. Composite segmented tool, which balances internal support and mold surface, must not only meet the requirements of disassembly and demolding but also ensure sufficient stiffness without deformation under loads like winding tension and curing shrinkage during tank formation. This article addresses the challenge faced by composite tool with uniformly thick ply stacking schemes, where the weight increases significantly with the rocket body diameter, rendering functions such as disassembly and demolding unfeasible. A global–local optimization approach aimed at achieving variable‐thickness ply stacking designs for composite tooling was proposed. Starting with a defined segmented tool design for the Φ3.35 m tank, models for calculating winding tension under complex service conditions and finite element models for curing shrinkage were established. Optimization of ply shapes, dimensions, and sequences using OptiStruct was conducted, which achieved a weight reduction of 34.48% while ensuring that deformations under loading met design standards. Subsequently, the engineering trials for the composite melon petal and wallboard corresponding to the Φ600 mm tank were conducted based on the optimized scheme. The maximum deformations for the two components were 0.43 mm and 0.15 mm, respectively, meeting the manufacturing requirements for engineering applications. The results provide a lightweight, high‐stiffness, and detachable tool design scheme for achieving the integrated manufacturing of extra‐large (Φ10 m) composite tanks.

Highlights

The external load was analyzed through theoretical and simulation approaches.

The weight of composite tool was significantly reduced after optimization.

The engineering prototypes of the segmented tools were achieved.
A double‐expanded polytetrafluoroethylene fabrication method for increased mechanical compliance in tubular vascular graft applications
Authors: Chen Edward , Turng Lih‐Sheng
Published: February 2024

A novel manufacturing technique has been developed to enhance the compliance of expanded polytetrafluoroethylene (ePTFE) for vascular graft applications. This new method involves modifying the existing processing procedures by introducing an additional expansion step while using a lower temperature during the first expansion stage. The new process results in the production of highly compliant ePTFE grafts without the need for supplementary additives or inherent material alterations. Tensile testing in both the longitudinal and circumferential directions as well as cyclical tensile testing were conducted to characterize the mechanical properties of double‐expanded ePTFE grafts prepared using varying expansion ratios. The double‐expanded ePTFE grafts consistently outperformed the prevailing, single‐expanded counterparts in both tensile stress tests and cyclical assessments of its elastic compliance. Notably, the double‐expanded ePTFE samples exhibited the desirable, biomimetic “toe‐region” and an elastic strain capacity of up to 50%, comparable to native vascular materials. Scanning electron microscopy (SEM) imaging was used to examine the morphological characteristics of the wavy fibers within the double‐expanded PTFE samples, which contributed to the enhanced compliance that is needed for vascular graft applications.

Highlights

A new process has been developed for expanded polytetrafluoroethylene (ePTFE).

This new process involves an additional expansion step at a lower temperature.

This new process results in the production of highly compliant ePTFE grafts.

Double‐expanded D‐ePTFE grafts outperform the single‐expanded counterparts.

D‐ePTFE grafts exhibit an elastic strain capacity similar to native vasculature.
The role of monomer geometry on the properties of polyolefins: A numerical study
Authors: Vargas‐Lara Fernando , Lopez‐Barron Carlos , Rodriguez George
Published: February 2024

We explore the role of monomer geometry on the structural, dynamic, and thermodynamic properties of polyolefis by employing all‐atom molecular dynamic simulations. Specifically, we compare properties of atactic polyolefins in the molten state including polypropylene (aPP), a short‐chain branched polymer: poy(1‐hexene) (aPH), and a polymer having cyclic olefins: poly(vinyl cyclobutane) (aPVCB). We find polymers having the same chain mass and atom composition (hydrocarbon‐based molecules), but having different monomer architecture differ strongly in material properties. In particular, the polymer glass transition () and bulk modulus () show higher values for aPVCB in comparison to aPP and aPH. This increase is caused by having the carbon atoms in a cyclic structure, making aPVCB achieve higher mass and energy densities. By contrast, adding linear short side chains to polymer backbones causes a reduction in and , since side chains make backbones displace each other reducing their packing and thus their mass and energy densities. More broadly, our numerical results suggest that the incorporation of VCB monomers to linear polyolefins will enhance their properties, opening the possibility for designing a new set of materials.
Adaptive stabilization of stochastic systems with polynomial nonlinear conditions, unknown parameters, and dead‐zone actuator
Authors: Xue Lingrong , Liu Zhen‐Guo , Zhang Weihai
Published: February 2024

Many practical dynamic models always suffer from complex nonlinearities, parameter uncertainties and random noises. Such kind of models are always characterized by uncertain stochastic nonlinear systems. Besides, many factors will lead to dead‐zone actuator, which further adds more challenges to control engineering. This paper studies stabilization issue of stochastic systems with polynomial nonlinear conditions, unknown parameters and dead‐zone actuator. An adaptive control approach is proposed by exploring homogeneous domination control and using dynamic‐gain‐based adaptive design strategy. It shows that all the signals are bounded almost surely and the system states converge to the origin almost surely. The presented method is successfully applied to the mass spring mechanical system.
Multi‐event‐triggered adaptive dynamic programming for non‐zero‐sum game of unknown nonlinear system
Authors: Zhu Qi , Zhang Kun , Xie Xiangpeng
Published: February 2024

In this article, a multi‐event‐triggered (MET) near‐optimal tracking control algorithm is developed for a discrete‐time (DT) nonlinear non‐zero‐sum game (NZSG). Firstly, the iterative dual heuristic dynamic programming (DHP) approach is utilized to obtain the optimal tracking control set. Subsequently, distinct independent triggering conditions are formulated for control inputs to improve the utilization efficiency of resources and ensure that the independence between them and the closed‐loop system has an excellent control performance. Meanwhile, input‐to‐state stability (ISS) is proven for the MET tracking plant. Additionally, neural networks (NNs) are designed in the iterative DHP algorithm to construct the model module, the critic module and the action modules, with aims to identify the unknown system, approximate costate function and estimate optimal tracking control strategy set, respectively. Finally, two numerical experimental simulations are conducted to verify the effectiveness of the proposed scheme.
Using photographs and deep neural networks to understand flowering phenology and diversity in mountain meadows
Authors: John Aji , Theobald Elli J. , Cristea Nicoleta , Tan Amanda , Hille Ris Lambers Janneke
Published: February 2024

Mountain meadows are an essential part of the alpine–subalpine ecosystem; they provide ecosystem services like pollination and are home to diverse plant communities. Changes in climate affect meadow ecology on multiple levels, for example, by altering growing season dynamics. Tracking the effects of climate change on meadow diversity through the impacts on individual species and overall growing season dynamics is critical to conservation efforts. Here, we explore how to combine crowd‐sourced camera images with machine learning to quantify flowering species richness across a range of elevations in alpine meadows located in Mt. Rainier National Park, Washington, USA. We employed three machine‐learning techniques (Mask R‐CNN, RetinaNet and YOLOv5) to detect wildflower species in images taken during two flowering seasons. We demonstrate that deep learning techniques can detect multiple species, providing information on flowering richness in photographed meadows. The results indicate higher richness just above the tree line for most of the species, which is comparable with patterns found using field studies. We found that the two‐stage detector Mask R‐CNN was more accurate than single‐stage detectors like RetinaNet and YOLO, with the Mask R‐CNN network performing best overall with mean average precision (mAP) of 0.67 followed by RetinaNet (0.5) and YOLO (0.4). We found that across the methods using anchor box variations in multiples of 16 led to enhanced accuracy. We also show that detection is possible even when pictures are interspersed with complex backgrounds and are not in focus. We found differential detection rates depending on species abundance, with additional challenges related to similarity in flower characteristics, labeling errors and occlusion issues. Despite these potential biases and limitations in capturing flowering abundance and location‐specific quantification, accuracy was notable considering the complexity of flower types and picture angles in this dataset. We, therefore, expect that this approach can be used to address many ecological questions that benefit from automated flower detection, including studies of flowering phenology and floral resources, and that this approach can, therefore, complement a wide range of ecological approaches (e.g., field observations, experiments, community science, etc.). In all, our study suggests that ecological metrics like floral richness can be efficiently monitored by combining machine learning with easily accessible publicly curated datasets (e.g., Flickr, iNaturalist).
Surface acoustic wave spectroscopy for non‐destructive coating and bulk characterization at temperatures up to 600°C enabled by piezoelectric aluminum nitride coated sensor
Authors: Makowski Stefan , Zawischa Martin , Schneider Dieter , Barth Stephan , Schettler Sebastian , Hoang Thanh‐Tung , Bartzsch Hagen , Zimmermann Martina
Published: February 2024

Surface acoustic wave spectroscopy has been established as non‐destructive and fast method for characterization of mechanical properties of surfaces and bulk materials in both research and industry. The present work shows that by application of a novel and robust aluminum nitride (AlN) coated piezoelectric contact sensor the advantages of the method can be extended from room temperature to at least 600°C. An overview of sensor concepts and applications of the method is discussed first, followed by theoretical and practical considerations for design and coating of a novel temperature stable contact sensor. After fabrication of such a sensor using magnetron sputtering, it was tested in a modified surface acoustic wave spectroscopy setup with an incorporated heating table concerning signal amplitude and frequency range. The AlN coated sensor was found to perform well up to 600°C, with temperature limited by the specification of the heating table. At room temperature, performance was acceptable when compared with a conventional contact sensor using a PVDF piezoelectric foil. Application of the high temperature capabilities of the setup was demonstrated by measuring temperature stability of hydrogen‐free amorphous carbon coatings (a‐C and ta‐C) depending on their sp3 carbon ratio. In another example, high precision temperature dependent measurement of Young's modulus for ultrasonic fatigue test specimen was taken, achieving an accuracy better than 1%. Use of the developed sensor opens up new possibilities in material science for in situ study of temperature depending mechanical properties for coatings and surfaces.
Recent Advances on Sustainable Synthesis of Furocoumarins
Authors: Borah Pallabi , Roy Subhasish , Saikia Pallabi , Yadav Lovely , Kharbteng Ophilia
Published: February 2024

Being an important constituent of naturally occurring heterocyclic compounds with a myriad of interesting biological activities, the furocoumarin motif has claimed vast interest in synthetic and medicinal research. Designing organic synthesis following a green and sustainable approach finds special importance in terms of energy efficiency, and cost‐effectiveness and hence becoming an important domain of research in the recent past. The methodologies for the sustainable synthesis of furocoumarin presented here particularly include the strategies developed under microwave irradiation, solvent‐free conditions or uses of green solvent, metal‐free routes, room temperature mediated and following one‐pot MCR reactions. This review article attempts to highlight the recent advances in the sustainable synthesis of furocoumarins along with general aspects like natural occurrence, and biological activities of this particular heterocyclic scaffold.
Effects of Metal Ions on Antioxidant Activity of Red Wine
Authors: Yao Song‐Po , Wang Wen‐Zhu , Li Xue‐Ying , Liu Xin‐Yu , Han Rui‐Min , Zhang Jian‐Ping
Published: February 2024

The biological properties of red wine are attributed to potent antioxidants and the antiradical activity of polyphenols. Recently, it has been noted that metal ions can substantially alter the reactivity of polyphenols. In this study, we observed that the radical scavenging activity of red wine increases when Cu(II), an exemplar of transition metal ions, is either removed or chelated. However, Conversely, the elimination of alkaline earth metal ions such as Mg(II) and Ca(II), representing main group elements, has negligible impact on this activity. We explored the interactions between Cu(II), Mg(II), and Ca(II) with three most abundant phenolic substances –gallic acid, catechin, and caffeic acid – and analyzed the corresponding radical scavenging kinetics in a uniform buffer solution at pH 7.2. Cu(II) formed 1 : 1 complexes with these three polyphenols, substantially diminishing their inherent radical scavenging potential. In accordance with the effect in red wine, Ca(II) and Mg(II) displayed no significant influence on the radical scavenging kinetics of these three polyphenols within the buffer solution. Our findings suggest that the removal of Cu(II), and potentially other transition metal ions, during the wine production process could enhance the antioxidant activity of red wine.
Designable Synthesis of Layered Silicates and Tunable Interlayer Expanded to Zeolites
Authors: Wang Ya , Peng Rusi , Sun Weihao , Li Shiqing , Wu Shitao , Xu Hao , Jiang Jingang , Chen Shifu , Wu Peng
Published: February 2024

Layered zeolitic silicates and corresponding interlayer‐expanded porous materials exhibit attractive application potential in wide fields. Nonetheless, designable synthesis and structure analysis of layered silicates remain challenging. Herein, two kinds of layered silicates are synthesized using different di‐quaternary ammonium‐type organic structure‐directing agents (OSDAs). Their crystal structures are analyzed and verified by 3D electron diffraction (3D ED) and high‐resolution TEM imaging. The suitable configurations of OSDA can lead to desirable interlayer states. Additionally, two new zeolite structures both with 12‐membered ring (MR) channels intersected by 8 MR channels and larger interlayer spaces are constructed from layered silicate precursors by interlayer silylation. The new zeolitic material exhibits potential application in adsorption of organic pollution and catalytic reaction. This study is expected to develop versatile ways for the design and synthesis of layered silicates even zeolites and provide references in characterizing layered materials and zeolites as well.
A Dendritic Architecture‐Based Deep Learning for Tumor Detection
Authors: Dong Shibo , Liu Zhipeng , Li Haotian , Lei Zhenyu , Gao Shangce
Published: February 2024

Brain tumor detection typically involves classifying various tumor types. Traditional classifiers, based on the McCulloch‐Pitts model, have faced criticism due to their oversimplified structure and limited capabilities in detecting brain tumor images with complex features. In this study, we propose a multiclassification model inspired by dendritic architectures in neurons, which leverages synaptic and dendritic nonlinear information processing capabilities. Experimental results using brain tumor detection datasets demonstrate that our proposed model outperforms other state‐of‐the‐art models across all evaluation metrics. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.
Improved Compound Vibration Suppression Control for Magnetic Levitation Motor
Authors: Zhang Dan , Wang Baonan
Published: February 2024

The magnetic levitation motor is high efficiency, energy saving and environmental protection, which integrates magnetic levitation bearing and permanent magnet motor into the traditional motor. Two key technologies of its stable operation are vibration suppression control of magnetic bearing and speed sensorless chattering suppression control of motor. The innovative research has been studied from the perspective of control systems. First, in order to form the vibration suppression controller, the traditional proportional integral differential control has been improved by adding incomplete differential time constant. In addition, the method using linear variable structure sliding mode observer (SMO) is proposed to achieve speed identification, which can solve the chattering problem caused by the discontinuous high frequency switching signal compared to the traditional SMO. Finally, the experimental platform is built to verify the correctness of the proposed control methods. When the motor operates in speed sensorless mode, the rotor vibration is within the effective range. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.
Do women with severely diminished ovarian reserve undergoing modified natural‐cycle in‐vitro fertilization benefit from earlier trigger at smaller follicle size?
Authors: Lawrenz B. , Kalafat E. , Ata B. , Melado L. , Del Gallego R. , Elkhatib I. , Fatemi H.
Published: February 2024

Objective

To evaluate whether trigger and oocyte collection at a smaller follicle size decreases the risk of premature ovulation while maintaining the reproductive potential of oocytes in women with a severely diminished ovarian reserve undergoing modified natural‐cycle in‐vitro fertilization.

Methods

This was a retrospective cohort study including women who had at least one unsuccessful cycle (due to no response) of conventional ovarian stimulation with a high dosage of gonadotropins and subsequently underwent a modified natural cycle with a solitary growing follicle (i.e. only one follicle > 10 mm at the time of trigger). The association between follicle size at trigger and various cycle outcomes was tested using regression analyses.

Results

A total of 160 ovarian stimulation cycles from 110 patients were included in the analysis. Oocyte pick‐up (OPU) was performed in 153 cycles and 7 cycles were canceled due to premature ovulation. Patients who received their trigger at smaller follicle sizes (≤ 15 mm) had significantly lower rates of premature ovulation and thus higher rates of OPU (98.9% vs 90.8%; odds ratio, 9.56 (95% CI, 1.58–182.9); P = 0.039) compared with those who received their trigger at larger follicle sizes (> 15 mm). On multivariable analysis, smaller follicle sizes at trigger (> 10 to 13 mm, > 13 to 15 mm, > 15 mm to 17 mm) were not associated significantly with a lower rate of cumulus–oocyte complex (COC) retrieval, metaphase‐II (MII) oocytes or blastulation when compared to the > 17‐mm group. On sensitivity analysis including only the first cycle of each couple, the maturity rate among those with COC retrieval was highest in follicle sizes > 15 to 17 mm (92.3%) and > 13 to 15 mm (91.7%), followed by > 10 to 13 mm (85.7%) and lowest in the > 17‐mm group (58.8%). During the study period, five euploid blastocysts developed from 48 fertilized MII oocytes with follicle sizes of 12 mm (n = 3), 14 mm (n = 1) and 16 mm (n = 1) at trigger. Of those, four were transferred and resulted in two live births, both of which developed from follicles with a size at trigger of 12 mm.

Conclusions

The ideal follicle size for triggering oocyte maturation may be smaller in women with a severely diminished ovarian reserve managed on a modified natural cycle when compared to conventional cut‐offs. The risk of OPU cancellation was significantly higher in women triggered at follicle size > 15 mm and the yield of mature oocytes was not adversely affected in women triggered at follicle size > 13 to 15 mm compared with > 15 to 17 mm. Waiting for follicles to reach sizes > 17mm may be detrimental to achieving optimal outcome. © 2024 International Society of Ultrasound in Obstetrics and Gynecology.