bluuebunny/crossref_metadata_2025 huggingface dataset:
Towards the development of sensation-enabled skin substitutes
Authors: Moradikhah Farzad , Farahani Mojtaba , Shafiee Abbas
Published: May 2024

Innervation is a critical step in functional skin repair. Current study highlights the regenerative approaches to restore skin sensation after trauma.
Cross-acyloin condensation of aldehydes catalysed by transketolase variants for the synthesis of aliphatic α-hydroxyketones
Authors: Arbia Giuseppe , Gadona Camille , Casajus Hubert , Nauton Lionel , Charmantray Franck , Hecquet Laurence
Published: May 2024

Transketolase variants catalyse a promiscuous acyloin condensation of aliphatic aldehydes leading in one step to unsymmetrical α-hydroxyketones while offering green advances compared to previous enzymatic and chemical ways.
Exploiting residual cocoa biomass to extract advanced materials as building blocks for manufacturing nanoparticles aimed at alleviating formation-induced oxidative stress on human dermal fibroblasts
Authors: Girón-Hernández Joel , Rodríguez Yeison Barrios , Corbezzolo Noemi , Blanco Dayana Orozco , Gutiérrez Carlos Carranza , Cheung William , Gentile Piergiorgio
Published: May 2024

Revalorising cocoa pod-husk biomass to extract biomolecules as building blocks for developing Layer-by-Layer functionalised-nanoparticles to alleviate formation-induced oxidative stress on human dermal fibroblasts.
A NASICON-type Na3.67Cu0.17Fe0.5V1.33(PO4)3 cathode with multi-electron reaction for high-energy sodium-ion battery
Authors: Chen Changliang , Fan Hao , Wang Zhaojian , Wang Mengyao , Zhang Yu , Hu Ping , Zhou Liang
Published: May 2024

A NASICON structured Na3.67Cu0.17Fe0.5V1.33(PO4)3 (NCFVP) sodium-ion battery cathode material with multi-electron redox reaction has been designed. The obtained NCFVP demonstrates a high capacity, high energy density, and ideal cyclability.
Theoretical insights into lanthanide rare earth single-atom catalysts for electrochemical CO2 reduction
Authors: Liu Jing , Sun Lei , Sun Yuying , Sun Jikai , Pan Yuwei , Xu Mengqian , Lang Yunjie , Zhai Dong , Deng Weiqiao , Li Yamin , Yang Li
Published: May 2024

This study comprehensively investigated the catalytic performance of lanthanide rare earth metals (REMs) anchored into Salen for CO2RR in terms of stability, selectivity, and activity using density functional theory (DFT).
Machine learning assisted layer-controlled synthesis of MoS2
Authors: Lu Mingying , Ji Haining , Chen Yongxing , Gao Fenglin , Liu Bin , Long Peng , Deng Cong , Wang Yi , Tao Jundong
Published: May 2024

Machine learning, one of the most powerful data-driven methods, has been developed to optimize layer-controlled synthesis of MoS2 for electronic and optoelectronic devices.
The effect of oxygen on NiO as a back buffer layer in CdTe solar cells
Authors: Hunwick Nicholas , Liu Xiaolei , Togay Mustafa , Walls John M. , Bowers Jake , Isherwood Patrick J. M.
Published: May 2024

Oxygen content during sputtering affects the characteristics of nickel oxide and was studied as a back buffer layer in cadmium telluride solar cells. Simulated valence band offsets outline ideal value range and are compared to measurements.
Pixel-wise attention driven infrared small target detection network
Authors: WANG Xiaolin , FANG Houzhang , LI Xueting , WU Chenxing , WANG Liming
Published: May 2024

Infrared small target detection has been widely used in the military and civil fields. The detection difficulties lie in small target size, few details and complex background interference. Existing classic deep learning detection methods are commonly suitable for generic target detection, but have poor adaptability to infrared small targets. To handle these problems, this article build a new infrared small target detection network based on U-shaped attention block and pixel-wise attention block. Firstly, a residual U-shaped attention block to extract multi-scale features through local U-shaped subnetworks in a single layer level and extract multiscale features to enrich the representation of small-scale target features is designed, so as to enhance the network′s ability to discriminate small-scale targets. Then, small target information is further preserved through dense fusion method to alleviate the semantic gap feature fusion between different layers and reduce the miss detection rate. Finally, the pixel-wise attention in space and channel dimensions is applied to the fused feature map to enhance small targets and suppress complex background interference. The experimental results show that the present network outperforms the latest benchmark method in the intersection over union, detection probability and false alarm rate of two infrared small target data sets NUDT-SIRST and IRSTD-1k. Moreover, the present network also achieves a good balance between the detection accuracy and the efficiency.
Research on the generation method of missing data for soft measurement based on GAN
Authors: JIANG Dongnian , WANG Renjie
Published: May 2024

To solve the problem of low precision in soft sensor models caused by sensor data loss in industrial processes, a new method of sensor data generation based on generative adversarial nets (GAN) is proposed. Firstly, the missing area of sensor data is detected by the isolated forest algorithm. Secondly, conditional generative adversarial nets (CGAN) are training using the attributes of missing data. By adding random sequences to the input conditions of CGAN as additional information, the data is generated iteratively in CGAN. The wasserstein generative adversarial nets gradient penalty (WGAN-GP) cost function is used to improve the stability of network training. Finally, a sampler is introduced to fill the sampled data into the missing region and form a complete data set to improve the accuracy of the soft sensing model. In this paper, the temperature sensor data of a nickel flash furnace is used as the target variable for soft-sensing modelling, and the feasibility and effectiveness of the proposed method to improve the accuracy of the soft-sensing model are verified.
Prediction models and multi-objective optimization of the single deposited tracks in laser direct metal deposition of 316L stainless steel
Authors: Doan Tat Khoa , Le Van Thao , Duong Van Nguy
Published: May 2024

Laser direct metal deposition (LDMD) is a metal additive manufacturing process, which uses a laser source to melt metal powder and deposit the molten metal into the part layer-by-layer through a nozzle. With suitable process parameters and setting conditions, a component can be fabricated with a full density. In this process, the shape of single tracks is a key indicator, which directly prescribes the quality of the process and the fabricated component. To fabricate a complex component, especially that with thin-wall structures with free of defects, controlling the single tracks' geometry and the understanding on the effects of the process parameters are essential. Therefore, this article focuses on studying the effects of process variables on single tracks' attributes in the LDMD process of SS316L and identifying the optimum variables for the deposition of SS316L thin wall structures. The observed results indicated that, among the process parameters (the scanning speed Vs, the laser power Pl, and the powder feed rate fp), Pl exhibits the highest impact contribution to the models of the deposited track width w and the deposited track penetration p with a contribution of 71.83% and 87.68%, respectively. Vs exhibits the highest contribution to the models of the deposited track height h a contribution of 49.86%. On the other hand, fp shows an insignificant impact contribution to the w and p models. All the developed models feature a high prediction accuracy with the values of determination coefficients R2 of 97.89%, 97.08%, 99.11% for w, h, and p, respectively, indicating that they can be used to prediction w, h, and p with high confidence and precision levels. Moreover, the optimization results achieved by different methods (i.e., GRA, TOPSIS, and PSO+TOPSIS) demonstrated that the PSO and TOPSIS combination can be used to find out the most optimal process parameters (i.e., Vs = 6 mm/s, Pl = 263.63 W, and fp = 18 g/min) to build thin-walled structures in SS316L by LDMD.
Distally Based Lymphatic Microsurgical Preventive Healing Approach—A Modification of the Classic Approach
Authors: Wong Allen Wei-Jiat , Sim Nadia Hui Shan , Thing Coeway Boulder , Xu Wenxuan , Chua Hui Wen , Ngaserin Sabrina , Loh Shermaine , Kok Yee Onn , Feng Jia Jun , Pearlie Tan Woon Woon , Tan Benita Kiat-Tee
Published: May 2024

The treatment of breast cancer has seen great success in the recent decade. With longer survivorship, more attention is paid to function and aesthetics as integral treatment components. However, breast cancer-related lymphedema (BCRL) remains a significant complication. Immediate lymphatic reconstruction is an emerging technique to reduce the risk of BCRL, the Lymphatic Microsurgical Preventive Healing Approach (LYMPHA) being the most widely used approach. Despite promising results, it is often difficult to find suitably sized recipient venules and perform the microanastomoses between mismatched vessels deep in the axilla. Moreover, high axillary venous pressure gradients and potential damage from radiotherapy may affect the long-term patency of the anastomoses. From an ergonomic point of view, performing lymphaticovenular anastomosis in the deep axilla may be challenging for the microsurgeon. In response to these limitations, we modified the technique by moving the lymphatic reconstruction distally—terming it distally based LYMPHA (dLYMPHA). A total of 113 patients underwent mastectomy with axillary clearance in our institution from 2018 to 2021. Of these, 26 underwent subsequent dLYMPHA (Group 2), whereas 87 did not (Group 1). In total, 17.2% (15 patients) and 3.84% (1 patient) developed BCRL in Groups 1 and 2, respectively (p = 0.018). Lymphatics and recipient venules suitable for anastomoses can be reliably found in the distal upper limb with better size match. A distal modification achieves a more favorable lymphaticovenular pressure gradient, vessel match, and ergonomics while ensuring a comparably low BCRL rate.
Prevalence and Predictors of Anxiety and Depression among Perinatal Women in Tertiary Care Hospital: A Cross-Sectional Study
Authors: Ruban Jenose Asmila , Santhosh Abinesh , Velmurugan Madhunisha , Selvaraj Lavanya , Leela Krishnapriya , Subbarayan Latha Maheswari
Published: May 2024

Introduction The perinatal period is a critical time in a woman's life. The impact of perinatal mental disorders includes new evidence of an increase in their prevalence among young pregnant women. Perinatal mental disorders are one of the most common and undertreated morbidities. Early detection of perinatal mental illness may be supported by evidence on risk factors. Our study aimed to identify the prevalence and risk factors of anxiety and depression and to determine the association between them.

Materials and Methods A prospective observational questionnaire-based study was conducted in the obstetrics and gynecology department of a tertiary care hospital for a duration of 6 months. With random sampling, 741 participants were recruited for the study based on inclusion and exclusion criteria. The data were analyzed using SPSS version 28.

Results The prevalence of perinatal anxiety and depression was found to be 48.5 and 32.2%, respectively. We discovered a substantial link between perinatal depression and anxiety, with an odds ratio of 3.9. The predictors are gestational age, postpartum age, comorbid conditions, morning sickness, sleep disturbance, sleep duration, loss of appetite, loss of interest in their favorite food, type of family, and presence of risk in their pregnancy.

Conclusion Early screening and intervention may drastically and significantly reduce mental disorders existing in the pregnant population. So as health care professionals, we suggest that screening and counseling for depression and anxiety could be included as routine processes in antenatal care.
Requests as macro-speech act motivators in Qur’anic dialogues
Authors: Khafaga Ayman
Published: May 2024

Besides their linguistic nature of directivity that necessitates a verbal and/or physical response, requests can also function as linguistic motivators of macro-speech acts. Based on this assumption, this paper explores the extent to which requests in some Qur’anic dialogues not only elicit a response but also motivate a sequence of ancillary speech acts that forms a macro-speech act communicating one macro-proposition. This objective is primarily pursued in light of an eclectic framework constituting van Dijk’s (1977) concept of macro-speech acts, Thornburg and Panther’s (1997) illocutionary scenarios, contributions on speech act theory and requests (e.g., Austin, 1962; Searle, 1979), and Blum-Kulka et al.’s (1989) categorization of modification strategies of requests. Three main findings are revealed in this paper: first, in some Qur’anic dialogues, requests are employed not only to create a position for a response or fulfillment on the part of addressees but also to motivate a sequence of other ancillary speech acts constituting one macro-speech act and profiling a shared logic-semantics representation. Second, unlike ordinary requests, macro-speech act requests (MSARs) in Qur’anic dialogues exhibit a high degree of contingency and a low degree of entitlement. Third, MSARs in Qur’anic dialogues are structured around three illocutionary scenarios, are modified internally and externally, and are illocutionary polysemous.
Urbanization inequality: evidence from vehicle ownership in Chinese cities
Authors: Duan Linlin , Song Lulu , Wang Wanjun , Jian Xiaomei , Heijungs Reinout , Chen Wei-Qiang
Published: May 2024

Unequal outcomes resulting from urbanization can pose a significant challenge to sustainable development. Vehicles are an important urbanization dimension as a critical component of urban infrastructure by providing mobility and accessibility to social services. China’s vehicle ownership (referred to as in-use vehicle stocks) has been growing quickly since 2000, but its per capita stocks are still much lower than that in developed economies. This raises the question of whether and when China’s vehicle stocks will reach a peak level close to that in the developed countries. By analyzing vehicle stocks in 283 Chinese cities during 2001–2018, we have the following findings: (1) vehicle stocks are predominantly distributed in northern and eastern coastal cities and provincial capital cities; (2) inequality in vehicle ownership rates between cities shows a declining trend at both national and region scales; (3) the growth of vehicle ownership rates follows an S-shape curve and most cities are still at the early stage of motorization; (4) China is likely to have a lower saturation level of vehicle ownership rate. These results could help to accurately forecast future vehicle demand in China, estimate the resulting environmental impacts, and explore strategies to achieve carbon neutrality in transportation.
Role of collaborative governance in unlocking private investment in sustainable projects
Authors: Bai Yiran , Lu Chunxian , Dong Ximiao , Li Yinan
Published: May 2024

This scholarly investigation scrutinizes the involvement of the private sector in environmentally sustainable projects, employing the cross-sectional autoregressive distributed lag methodology on yearly data spanning from 2000 to 2020 across 11 low and lower-middle-income Asian nations. It specifically assesses the influence of the good governance index. Findings indicate a notable correlation, where a 1% enhancement in the index corresponds to a 0.34% increase in private engagement in green projects in the short term and a 0.64% increase in the long term. The study underscores the significance of economic stability; a 1% escalation in uncertainty leads to a 0.56% short term and 0.73% long-term reduction in private participation. It underscores the driving role of gross domestic product growth and the proliferation of small and medium-sized enterprises, emphasizing the necessity for tailored financial instruments to stimulate private investment in green projects. Moreover, it explores practical policy avenues such as e-government services, information and communication technology-driven digital transformation, sustainable corporate governance, and issuance of state-backed green bonds to foster private-sector participation in eco-friendly initiatives. Future research avenues encompass examining the repercussions of the pandemic on private green investments and evaluating the efficacy of the public-private partnership model in green projects across these economies.
3-level inverter based compensator for power quality enhancement using proposed Trianguzoidal PWM technique
Authors: Agrawal Nikhil , Agarwal Anshul , Kanumuri Tirupathiraju
Published: May 2024

In today’s scenario, the integration of a grid-connected load system with a hybrid energy system (HES) is encouraged to improve the reliability of the system. With the stunning rise in nonlinear loads in HES over the last two decades, the power quality (PQ) of the system has emerged as a paramount concern in contemporary times. The power quality problems include the injection of harmonics in the source current, low input power factor, poor voltage regulation, the burden of reactive power, etc. So, to mitigate these power quality problems in a single-phase distribution system, a 3-level Cascade H-bridge (CHB) inverter-based shunt active power filter (SAPF) is employed alongside a proposed Trianguzoidal pulse width modulation (TRZ PWM) strategy. The single-phase distribution system with SAPF is simulated in fixed and dynamic load conditions to check the system’s efficacy. The proposed PWM techniques for SAPF are compared with conventional PWM techniques, i.e., level shift, phase shift, and hybrid PWM techniques. Results indicate satisfactory performance of the proposed PWM techniques, exhibiting low harmonic distortion in source current, well within IEEE 519 limits, and high active filtering efficiency (AFE) compared to conventional PWM methods. Furthermore, this paper provides detailed comparisons of conventional and proposed PWM techniques in the context of active & reactive power supplied or delivered by load, source, and compensator, input power factor, harmonics in source or grid current, AFE, and individual harmonic components concerning fundamental component of source current.
Laser-based synthesis of silver nanoparticles embedded in cellulose paper for catalytic reduction of azo dyes and SERS sensing of pesticides
Authors: Malik Ammara , Hussain Shafqat , Al-Ahmadi Ameenah N , Abdel-Aty Abdel-Haleem , Ur Rehman Zia , Qayyum Hamza
Published: May 2024

In this study, highly reactive bare silver nanoparticles (Ag NPs) are synthesized using the Pulsed Laser Ablation in Liquid (PLAL) technique. Ag NPs are then coated on the filter paper using the dip coating method. This process converts filter paper into a versatile substrate for catalysis and surface-enhanced Raman Spectroscopy (SERS) based sensing. The successful synthesis of spherical Ag NPs and their effective embedding into the filter paper was confirmed using UV–visible absorption spectroscopy, scanning electron microscopy (SEM), and Energy Dispersive x-ray analysis (EDX). SEM images revealed that the Ag NPs were embedded in the filter paper and attached to the cellulose fibers. The use of Ag NPs embedded filter paper as a catalyst substrate for the reduction of both cationic and anionic dyes demonstrated that higher concentrations of Ag NPs on the filter paper resulted in a faster reduction. In particular, filter paper impregnated with 52 μg of Ag NPs demonstrated a complete reduction of methylene blue and methyl orange in less than a minute and 4 min, respectively. To demonstrate the practical sensing capability of the Ag NPs embedded filter paper, it was utilized as a SERS substrate. This enabled the detection of trace levels of Rhodamine 6G (R6G) and the pesticide molecule chlorpyrifos, demonstrating its potential real-world applications.
Comparison of the effect of C doping on the photovoltaic properties of the defect state transition metal sulfur compounds MX2 (M = Mo, W; X = S, Te): a first-principles study
Authors: Dai Ying , Liu Guili , He Jianlin , Yang Zhonghua , Zhang Guoying
Published: May 2024

Two-dimensional layered materials are widely used due to their favorable electrical and optical properties. In this paper, the electronic structure, DOS, charge transfer, and optical properties of the defect state C-MX2 system of transition state metal-sulfur compounds are investigated using first-principle calculations. The electronic structure, DOS, charge transfer and optical properties of three systems, MoS2, MoTe2 and WS2, are systematically compared and analyzed. The results show that MoS2, MoTe2, and WS2 are all direct band-gap semiconductors. After the occurrence of vacancy defects, MoTe2 and WS2 are transformed from direct band-gap to indirect band-gap, while MoS2 still maintains the direct band-gap. We chose C atoms to dope the defective state MX2 system. After doping with a low concentration of C atoms, the Fermi energy level decreases, the valence band shifts upward, and the system undergoes a semiconductor-to-metal transition. In terms of density of states, the Mo-d and W-d orbitals as well as the S-p and Te-p orbitals are gradually enhanced under the effect of defect states and C doping, with the contribution of MoTe2 > MoS2 > WS2. In terms of optical properties, the absorption and reflection peaks of all three systems are blue-shifted after the change of defect states and C doping.
DC and RF performance analysis of enhancement mode fin-shaped tri-gate AlGaN/GaN HEMT and MOSHEMT with ultra-thin barrier layer
Authors: Chakrabarty Ashutosh , Sahoo Narayan , Panigrahy Asisa Kumar , Sreenivasulu Vakkalakula Bharath , Swain Raghunandan
Published: May 2024

The DC and RF assessment of critical barrier-AlGaN/GaN nano channel tri-gate fin-shaped High Electron Mobility Transistor (FinHEMT) is investigated for Enhancement-mode (E-mode) operation. We propose and analyze critical barrier layer (CBL) and critical-strained barrier layer (CSBL) FinHEMT for a fixed fin-shaped channel width (W

fin
= 160 nm) and height (H

fin
= 70 nm). The CBL FinHEMT ensures an E-mode operation by depleting two-dimensional electron gas (2DEG) near the channel region between AlGaN and GaN hetero-junction. The extracted threshold voltage (V

T
) in CBL FinHEMT is 0.4 V as compared to −0.2 V obtained in CSBL FinHEMT. However, increased gate leakage current density and poor gate voltage swing in CBL FinHEMT is improved through a metal-oxide-semiconductor FinHEMT (FinMOSHEMT) structure by the incorporation of Al2O3 gate oxide layer between the tri-gate and CBL AlGaN layer. It results in a stable positive VT of 0.5 V due to the negatively charged Al2O3/barrier interface fixed charge density (

N

Al

2

O

3

). The proposed CBL FinMOSHEMT has also been studied for different atomic layer deposition Al2O3 process-dependent variations in

N

Al

2

O

3

.

The maximum on-state drain current and transconductance of 1.01 A mm−1 and 430 mS/mm have been extracted respectively with

N

Al

2

O

3

of −9.2 × 1012 cm−2. Further, the RF analysis of the proposed CBL FinMOSHEMT structure with the same dimension exhibits improved f

T
and f
max responses with 27 GHz and 90 GHz respectively over CBL FinHEMT. The results of the frequency responses obtained for the proposed design make it suitable for power electronics applications.
Proxy-based robust deep metric learning in the presence of label noise
Authors: Mohammed Neamah Farah , Aghdasi Hadi S , Salehpour Pedram , Sokhandan Sorkhabi Alireza
Published: May 2024

Real-world datasets contain label noise data that can deteriorate the performance of a deep learning model. Cleaning annotations manually requires substantial efforts from experts and is not practical in large datasets. Therefore, many methods are proposed to enhance the robustness of deep models in the presence of label noise. However, these methods are primarily developed for classification tasks and cannot be directly applied to Deep Metric Learning (DML) applications. To bridge this gap, we present a proxy-based deep metric learning method to detect wrong labels through the estimation of the posterior distribution for observed and true labels. Specifically, we model the distribution of the observed annotations as a mixture of two components: one component represents the clean label distribution and the other denotes the noisy labels. Besides, we present an EM-like algorithm that precisely identifies label noise data jointly with the similarity learning method. We also exploit information of the identified noisy labeled data by utilizing state-of-the-art semi-supervised learning (SSL) techniques. The results of the extensive experiments on datasets with real or synthetic label noise indicate that our method consistently outperforms the state-of-the-art methods by a large margin. Moreover, the proposed method accurately detects noisy labeled data and generates correct pseudo labels for them after only a few epochs.
Symmetry quantification and segmentation in STEM imaging through Zernike moments
Authors: Dan Jiadong , Zhang Cheng , Zhao 赵 Xiaoxu 晓续 , Duane Loh N.
Published: May 2024

We present a method using Zernike moments for quantifying rotational and reflectional symmetries in scanning transmission electron microscopy (STEM) images, aimed at improving structural analysis of materials at the atomic scale. This technique is effective against common imaging noises and is potentially suited for low-dose imaging and identifying quantum defects. We showcase its utility in the unsupervised segmentation of polytypes in a twisted bilayer TaS2, enabling accurate differentiation of structural phases and monitoring transitions caused by electron beam effects. This approach enhances the analysis of structural variations in crystalline materials, marking a notable advancement in the characterization of structures in materials science.
Osteo-immunomodulatory effects of macrophage-derived extracellular vesicles treated with biphasic calcium phosphate ceramics on bone regeneration
Authors: Chen Fuying , Liu Jiajun , Liu Keting , Tian Luoqiang , Li Xiangfeng , Zhu Xiangdong , Chen Xuening , Zhang Xingdong
Published: May 2024

Literature on osteoimmunology has demonstrated that macrophages have a great influence on biomaterial-induced bone formation. However, there are almost no reports clarifying the osteo-immunomodulatory capacity of macrophage-derived extracellular vesicles (EVs). This study comprehensively investigated the effects of EVs derived from macrophages treated with biphasic calcium phosphate (BCP) ceramics (BEVs) on vital events associated with BCP-induced bone formation such as immune response, angiogenesis, and osteogenesis. It was found that compared with EVs derived from macrophages alone (control, CEVs), BEVs preferentially promoted macrophage polarization towards a wound-healing M2 phenotype, enhanced migration, angiogenic differentiation, and tube formation of human umbilical vein endothelial cells, and induced osteogenic differentiation of mesenchymal stem cells. Analysis of 15 differentially expressed microRNAs (DEMs) related to immune, angiogenesis, and osteogenesis suggested that BEVs exhibited good immunomodulatory, pro-angiogenic, and pro-osteogenic abilities, which might be attributed to their specific miRNA cargos. These findings not only deepen our understanding of biomaterial-mediated osteoinduction, but also suggest that EVs derived from biomaterial-treated macrophages hold great promise as therapeutic agents with desired immunomodulatory capacity for bone regeneration.
Harnessing oriented arrangement of collagen fibers by 3D printing for enhancing mechanical and osteogenic properties of mineralized collagen scaffolds
Authors: Zhou Yi , Lian Xiao-Jie , Lu Yi , Zhu Qi , Fu Tong , Feng Hao-Nan , Lei Qi , Huang Di
Published: May 2024

As the structural basis of connective and load-bearing tissues, collagen fibers with orientation play an important role in the mechanical properties and physiological and biochemical functions of the tissues, but viable methods for preparing scaffolds with highly oriented collagenous structure still need to be further studied. In this study, pure collagen was used as printing ink to 3D printing. Harnessing oriented collagen fiber structure by 3D printing for promoting mechanical and osteogenic properties of scaffolds. The scaffolds with different printed angles and thicknesses were prepared to fit the bone defect site and realize personalized customization. The orientation assembly of collagen fibers was promoted by shear force action of 3D printing, the regular arrangement of collagen fibers and stabilization of fiber structure were promoted by pH adjustment and glutaraldehyde cross-linking, and the collagen fibers were mineralized by cyclic mineralization method. The microscopic morphology of fiber arrangement in the scaffolds were investigated by scanning electron microscopy. Results demonstrated that collagen fibers were changed from non-oriented to oriented after 3D printing. And the tensile modulus of the scaffolds with oriented collagen fibers was nine times higher than that of the scaffolds with non-oriented fibers. Moreover, the effects of oriented collagen fibers on the proliferation, differentiation and mineralization of MC3T3-E1 cells were studied by CCK-8 assay, live/dead cell staining, alkaline phosphatase activity test, and Alizarin red staining. The results indicated that cell proliferation, differentiation and mineralization were significantly promoted by oriented collagen fibers, and the cells proliferated directionally in the direction of the fibers. Taken together, mineralized collagen fiber scaffolds with oriented collagen fibers have great potential in bone tissue engineering applications.
Exosome-loaded hydrogels for craniofacial bone tissue regeneration
Authors: Liu Xiaojie , Liu Chang , Lin Qingquan , Shi Ting , Liu Guanying
Published: May 2024

It is common for maladies and trauma to cause significant bone deterioration in the craniofacial bone, which can cause patients to experience complications with their appearance and their ability to function. Regarding grafting procedures’ complications and disadvantages, the newly emerging field of tissue regeneration has shown promise. Tissue -engineered technologies and their applications in the craniofacial region are increasingly gaining prominence with limited postoperative risk and cost. MSCs-derived exosomes are widely applied in bone tissue engineering to provide cell-free therapies since they not only do not cause immunological rejection in the same way that cells do, but they can also perform a cell-like role. Additionally, the hydrogel system is a family of multipurpose platforms made of cross-linked polymers with considerable water content, outstanding biocompatibility, and tunable physiochemical properties for the efficient delivery of commodities. Therefore, the promising exosome-loaded hydrogels can be designed for craniofacial bone regeneration. This review lists the packaging techniques for exosomes and hydrogel and discusses the development of a biocompatible hydrogel system and its potential for exosome continuous delivery for craniofacial bone healing.
Development of a tobramycin-loaded calcium alginate microsphere/chitosan composite sponge with antibacterial effects as a wound dressing
Authors: Ma Ruixia , Shi Xingyan , Wang Xiaoyan , Si Chenchen , Gong Yuwei , Jian Wei , Zhou Chen , Yang Hui , Xu Lihua , Zhang Hualin
Published: May 2024

Traditional dressings exhibit several disadvantages, as they frequently lead to bacterial infections, cause severe tissue adhesion and perform a relatively single function. Therefore, in this study, a composite sponge dressing with antibacterial properties and excellent physicochemical properties was developed. Six groups of tobramycin-loaded calcium alginate microspheres were prepared by changing the amount of tobramycin added, and the optimal group was selected. Then, seven groups of tobramycin-loaded calcium alginate microsphere/chitosan composite sponges were fabricated via a solvent blending process and a freeze-drying method. The surface morphology, physicochemical properties, in vitro degradation properties, in vitro drug release properties, antibacterial properties and cytotoxicity of the composite sponges were examined. Group 3.0 contained the best microspheres with the largest drug loading capacity, good swelling performance and cumulative drug release rate, obvious and sustained antibacterial activity, and good cytocompatibility. The tobramycin-loaded calcium alginate microsphere/chitosan composite sponges exhibited three-dimensional porous structures, and their porosity, swelling rate, water absorption and water retention rates and water vapor transmission rate met the standards needed for an ideal dressing. The comprehensive performance of the sponge was best when 20 mg of drug-loaded microspheres was added (i.e. group 20). The cumulative drug release rate of the sponge was 29.67 ± 4.14% at 7 d, the diameters of the inhibition zones against the three bacteria were greater than 15 mm, and L929 cell proliferation was promoted. These results demonstrated that the tobramycin-loaded calcium alginate microsphere/chitosan composite sponge with 20 mg of tobramycin-loaded microspheres shows promise as a dressing for infected wounds.
Optimization of Tertiary Irrigation Network Using A Linear Program at D.I. Panggak Darat in Lingga District
Authors: Zefri R , Isrami F , Budi E S , Irfan
Published: May 2024

The Panggak Darat Irrigation Area in Lingga Regency can irrigate 134.05 ha of rice fields. The problem that often occurs is that irrigation areas are not fully optimal for agricultural product productivity, so that an effort can be made to minimize the shortage of irrigation water and/or minimize the deviation of water release that can result from an optimal pattern of irrigation operations. The purpose of this study is to obtain an optimal operating pattern with better operating performance than the existing (planning). The analytical method used is an optimization technique using the LINDO program (linear programming). The objective function is to minimize the shortage of irrigation water. Evaluation of the operational performance of the optimized and existing reservoirs is carried out using simulation techniques. The results showed that the optimal operating pattern was obtained from the Objective Function with an average total release of reservoir water of 3.20 million m3, which can meet 100% of the irrigation water Requirements of an area of 134.05 ha of irrigation area that must be irrigated. The reliability of the optimization results is in the form of 100% irrigation reliability with a planting intensity of 300% with a rice-rice cropping pattern where the existing (planning) is a rice-rice-bero cropping pattern or a rice-bero cropping pattern with a cropping intensity of 200%. Optimization results from the objective function of minimizing the shortage of irrigation water provide better operating performance than the existing conditions, so as to increase agricultural productivity.
Application of Tropical Rainfall Measuring Mission (TRMM) Data for Flood Estimation in Lack Data Catchment
Authors: Tunas I G , Herman R. , Arafat Y.
Published: May 2024

Providing real-time hydrological data for the design, development and management of water resources is a fundamental issue that is still being faced by hydrologists and practitioners. This data limitation is not only caused by the uneven distribution of hydrological measuring instruments, but also due to the inability of measuring instruments to present the data in real time. This paper aims to evaluate hydrological data, especially spatial-based rainfall data known as Tropical Rainfall Measuring Mission (TRMM) data as an alternative to rainfall data to predict flood hydrographs in a catchment with limited data. The study was initiated by selecting pairs of automatic rainfall data (ARG) and water level (AWLR) and combined with TRMM rainfall data for the same time series. These two types of rainfall data are then used as input for the HEC-HMS hydrological model involving a number of catchment parameters, such as: basin area, stream network, land use/land cover (LULC), soil characteristics and several other parameters. Three analytical methods are assigned to determine the shape of the hydrograph which include: Snyder UH (transformation method), SCS-CN (loss method), and recession (baseflow method). Discharge data converted from water level data is input at the catchment outlet as a reference for setting calibration parameters which are evaluated with the RMSE error indicator. The simulation results show that the predicted discharge deviation from TRMM rainfall data is higher than the predicted discharge from ARG rainfall data with RMSE 0.979 and 1.731 respectively. However, basically this TRMM data can be an alternative data by validating it with ARG rain data to be applied to lack of catchment data.
Analysis of Land Cover Changes Impact on Design Flood Estimation Case study: Upper Cimanuk Watershed in Garut City
Authors: Kamanda A , Anggraheni E , Kuncoro D A
Published: May 2024

The unexpected flooding events that occurred in the years 2021 and 2022 in the city of Garut became unforeseen incidents. According to the National Disaster Management Agency (BNPB), the flood disasters were caused by several factors, one of which was changes in land cover. Based on this background, this research is conducted to examine the causes of changes in flood discharge that have occurred in the city of Garut due to land cover changes from the years 2000, 2010, and 2020. The evaluation of the factors causing the flood magnitude is performed by conducting a hydrological analysis in the Cimanuk Watershed. An analysis of land cover changes using the ArcGIS application to create land cover samples and HEC-HMS application was conducted to determine the percentage increase in discharge and to understand the percentage of land cover changes that occurred in the Cimanuk Watershed. The data used included satellite image maps, digital elevation models (DEM), rainfall intensity, and cross-sectional data. The accuracy of the simulation was assessed using the Nash-Sutcliffe Efficiency (NSE). The simulation results show an increase in the inflow discharge into Garut city ranging from 23.7% to 32.2% for each return period. The NSE value obtained for the model was 0.83, indicating that the HEC-HMS hydrological model performed well.
Impact of Landuse Change on The Inundations in The Ciberes Watershed
Authors: Briandy D , Anggraheni E , Kuntcoro D A
Published: May 2024

Whenever the rainy season approaches, the Ciberes River always inundates a number of regions. This research was conducted to determine the effect of land use change on the inundation in the Ciberes Watershed, given the aforementioned context. Using land cover change data from 2000 to 2023, a hydrological and hydrodynamic analysis of the Ciberes Watershed is conducted to determine the impact of landuse change. This investigation employs HEC-HMS for hydrological modeling and HEC-RAS for 1D and 2D hydrodynamic modeling. The simulation results demonstrate that the change in CN value is directly proportional to the flood discharge, and the flood discharge is directly proportional to the height of the flood inundation. Based on these findings, it can be concluded that the river’s cross section can accommodate flood discharges with a return period of 50 years, except in coastal areas. whereas the floods that occurred in 2018 and 2022 have a 10-year return period. It can be concluded that the topographical condition of the river in the downstream segment, which has a higher elevation than the surrounding land and flat soil conditions, is the primary cause of inundation in the Ciberes Watershed.
Evaluation of Sabo Infrastructure Using UAV/Drone Technology for Monitoring and Inspection Data (Case Study: Sabo Dam Bakalan, Cangkringan District, Sleman)
Authors: Munir M D , Yusrizal M S , Eka N A , Elvira O N
Published: May 2024

The sabo dam serves as a structure positioned along a river branch, intended to manage and contain sediment for either a temporary or permanent duration, functioning as a system to combat potential disasters caused by erosion and sedimentation. Given the significance of sabo infrastructure in mitigating sediment- related calamities, it is essential to uphold and advance these structures through continuous monitoring, necessitating timely access to detection data. However, the inspection and monitoring of sabo buildings present considerable challenges, including the extensive coverage area of the river and the difficulty in accessing various building locations.To address these challenges, alternative approaches are being employed for the inspection and monitoring of sabo buildings. One such approach involves the utilization of drone-based asset survey technology. This technology enables the recording of precise object geometries and the generation of structural information that can be validated on-site, particularly in the context of infrastructure conditions related to sabo dams. By integrating drone technology, it is anticipated that the process of inspecting and monitoring buildings and land areas surrounding sabo dams can be expedited, with increased precision and enhanced safety measures.
Ciujung river basin flood risk assessment due to climate change and its countermeasure
Authors: Putriasri A E , Eliasta L , Amatullah S I , Sandi C , Pahlevi A R , Hikmat S N , Jaya I , Kosasih B , Rahmawati A , Hermawan Y
Published: May 2024

Ciujung River is experiencing recurrent flooding, which was caused by climate change factor and extensive land use change. Therefore, this study carried out risk assessment in this basin area. First, hydrology analysis was carried out using HEC-HMS software to obtain flood discharge hydrograph, with obtained peak discharge of 3534.3 m3/s for 25-year return period. This hydrograph was then modeled into an inundation map using HEC-RAS two-dimensional model to calculate hazard index. Meanwhile, the vulnerability and capacity index were calculate using the demographic data. Finally, the risk index was calculated by combining hazard, vulnerability, and capacity index using raster calculator on Arc-GIS. Overall, the flood risk analysis shows a medium level. The results shown that hazard index is the most contributing factor in causing a high risk index. Thus, in this study we proposed a structural approach to reduce the hazard index. An embankment with a length of 50.37 km was applied and remodeled to analyze its effectiveness. The modeling results show high effectiveness with a significant reduction in inundation area. The reduction of inundated area reached 39.6%, while the reduction of affected buildings reached 49.9%. Hopefully, the result of this study can provide theoretical support and recommendations for future development.
River Morphological Change and Sedimentation Countermeasures Analysis in Miu River
Authors: Dewi Q , Ramdhani H
Published: May 2024

One major floods problem in Miu River is huge amount of sediment which transported along the river channel. The decreasing of river capacity has been analysed and some channel courses changes also detected. These problems caused river morphological change and it is necessary to find comprehensive solution which not only decreasing the flood damage but also consider appropriate approach to natural environment. The complexity of these problems and possible solutions to overcome flood and sedimentation problem were investigated. Increasing of river capacity by channel excavation, protecting riverbank with revetment and construction of sediment control facilities were proposed as main solution. However, it is necessary to evaluate the effectiveness of these efforts by analysed sediment control facilities location and dimension of the structures. Some alternatives were investigated in order to find most effective solution to solve flood and sedimentation problem in Miu River.
Quantum kernels for classifying dynamical singularities in a multiqubit system
Authors: Tancara Diego , Fredes José , Norambuena Ariel
Published: May 2024

Dynamical quantum phase transition is a critical phenomenon involving out-of-equilibrium states and broken symmetries without classical analogy. However, when finite-sized systems are analyzed, dynamical singularities of the rate function can appear, leading to a challenging physical characterization when parameters are changed. Here, we report a quantum support vector machine algorithm that uses quantum Kernels to classify dynamical singularities of the rate function for a multiqubit system. We illustrate our approach using N long-range interacting qubits subjected to an arbitrary magnetic field, which induces a quench dynamics. Inspired by physical arguments, we introduce two different quantum Kernels, one inspired by the ground state manifold and the other based on a single state tomography. Our accuracy and adaptability results show that this quantum dynamical critical problem can be efficiently solved using physically inspiring quantum Kernels. Moreover, we extend our results for the case of time-dependent fields, quantum master equation, and when we increase the number of qubits.
Lyapunov analysis of data-driven models of high dimensional dynamics using reservoir computing: Lorenz-96 system and fluid flow
Authors: Kobayashi Miki U , Nakai Kengo , Saiki Yoshitaka
Published: May 2024

We computed the Lyapunov spectrum and finite-time Lyapunov exponents of a data-driven model constructed using reservoir computing. This analysis was performed for two dynamics that exhibit a highly dimensionally unstable structure. We focused on the reconstruction of heterochaotic dynamics, which are characterized by the coexistence of different numbers of unstable dimensions. This was achieved by computing fluctuations in the number of positive finite-time Lyapunov exponents.
Synergistic effect between Co single atoms and Pt nanoparticles for efficient alkaline hydrogen evolution
Authors: Shu Chengyong , Cao Jingwen , Gan Zhuofan , Qiu Peixi , Chen Zhixu , Guanwu Lian , Chen Zhongxin , Deng Chengwei , Tang Wei
Published: May 2024

In the pursuit of sustainable energy solutions, the efficiency of the hydrogen evolution reaction (HER) in alkaline conditions has been a significant challenge, primarily due to the sluggish dissociation of water molecules on platinum (Pt) catalysts. Addressing this critical issue, our study introduces an innovative Pt-Co@NCS catalyst. This catalyst synergistically combines Pt nanoparticles with Co single atoms on a nitrogen-doped carbon scaffold, overcoming the traditional bottleneck of slow water dissociation. Its unique porous concave structure and nitrogen-enriched surface not only provide abundant anchoring sites for Co atoms but also create a conducive hydrophilic environment around the Pt particles. This design leads to a drastic improvement in the water dissociation process, as demonstrated by CO stripping and deuterium labeling experiments. Achieving an outstanding current density of 162.8 mA cm−2 at −0.1 V versus RHE, a Tafel slope of 26.2 mV dec−1, and a superior nominal mass activity of 15.75 mA μgPt
−1, the Pt-Co@NCS catalyst represents a significant step forward in enhancing alkaline HER efficiency, indicating promising advancements in the field.