bluuebunny/crossref_metadata_2025 huggingface dataset:
Twisted metamaterials for mechanical optical switch
Authors: Yang Wenlei , Tie Yuanhao , Pantke Klaus , Biczo Andras , Feng Ning , Guo Ronghui , Li Le
Published: January 2025

The emergence of twisted metamaterials opens up an avenue for research in metamaterials. However, the current emphasis primarily lies in mechanics, rendering it intriguing to explore the application of compression-torsion coupling effect in optics. This present study introduces a thin-walled circular tube (TWCT) structure, characterized by a pronounced twisting angle of up to 59.5°, achieved only through a single-layer TWCT configuration. We demonstrate a significant compression-torsion coupling phenomenon, surpassing the findings of previous research endeavors. TWCT's deformation mechanism is harnessed in optical imaging through the integration of experimental, theoretical, and finite element approaches. The information stored in TWCT can be gradually projected through optical imaging when the elastic strain stimulates TWCT. These findings presented herein introduces a straightforward and valid approach to employ TWCT as a reliable mechanical switch for optical imaging, thereby showcasing its potential in the fields of cryptographic techniques, information storage, and transmission via optical imaging.
Time-resolved vibronic spectra with nuclear–electronic orbital time-dependent configuration interaction
Authors: Garner Scott M. , Upadhyay Shiv , Li Xiaosong , Hammes-Schiffer Sharon
Published: January 2025

Time-resolved spectroscopy is an important tool for probing photochemically induced nonequilibrium dynamics and energy transfer. Herein, a method is developed for the ab initio simulation of vibronic spectra and dynamical processes. This framework utilizes the recently developed nuclear–electronic orbital time-dependent configuration interaction (NEO-TDCI) approach, which treats all electrons and specified nuclei quantum mechanically on the same footing. A strategy is presented for calculating time-resolved vibrational and electronic absorption spectra from any initial condition. Although this strategy is general for any TDCI implementation, utilizing the NEO framework allows for the explicit inclusion of quantized nuclei, as illustrated through the calculation of vibrationally hot spectra. Time-resolved spectra produced by either vibrational or electronic Rabi oscillations capture ground-state absorption, stimulated emission, and excited-state absorption between vibronic states. This methodology provides the foundation for fully ab initio simulations of multidimensional spectroscopic experiments.
Recent trends in electro-microfluidic devices for wireless monitoring of biomarker levels
Authors: Fande Sonal , Pavar Sai Kumar , Goel Sanket
Published: January 2025

Wireless monitoring has emerged as a promising approach that enables real-time tracking of health, disease progression, and fitness, unlocking new possibilities for personalized healthcare. The review focuses on integrating electro-microfluidic (EM) devices with wireless technologies, revealing the potential for miniaturized, portable, and cost-effective systems. EM devices can noninvasively detect critical disease biomarkers such as metabolites, proteins, and pathogens. These advancements address the growing demand for accessible diagnostics, especially in resource-limited settings. Advancements in microfabrication techniques and biocompatible materials have enhanced the sensitivity, specificity, and ability of the devices to detect multiple biomarkers simultaneously, ensuring reliable performance in diverse applications. Incorporating Internet of Things frameworks further bridges the gap between laboratory diagnostics and point-of-care testing, enabling seamless data transmission and remote monitoring. Additionally, implementing flexible materials such as polymers, paper-based platforms, and textile-integrated designs has expanded the scope of devices to wearable applications, providing user comfort and convenience. These devices improve diagnostic accuracy and patient safety by enabling continuous health monitoring and early disease detection. The review highlights a comprehensive overview of the cutting-edge advancements in EM devices, emphasizing their transformative potential in making healthcare more accessible, efficient, and personalized.
Why the universal threshold for primordial black hole formation is universal
Authors: Kehagias Alex , Perrone Davide , Riotto Antonio
Published: January 2025

We show why the threshold for primordial black hole formation is universal (independent from the shape of the perturbation) when expressed in terms of the volume averaged compaction function. The proof is rooted in the self-similarity of the gravitational collapse phenomenon at criticality.
Planck’s constant from Stefan’s radiation law: a study of gray radiations of tungsten filament bulb
Authors: Rawal Ishpal
Published: January 2025

This study introduces a straightforward approach to determine Planck’s constant in an undergraduate course at the college or university level through the analyses the current–voltage (I–V) characteristic of a tungsten filament bulb. Unlike conventional methods, this analysis does not require the use of a color filter or an additional photodiode to select a specific wavelength or measure the emitted energy density from the filament. The temperature of the filament was computed by measuring the resistance of the filament. The obtained temperature and the input power of the filament are then used to estimate the emissivity of the filaments using Stefan–Boltzmann’s law, which is found to be lower than that of a perfect black body, i.e. unity. Therefore, the radiation emitted from the tungsten filament can be classified as gray radiation. The maximum energy density (intensity) of the emitted radiation is determined by calculating the consumed power of the filament. Finally, the obtained values of temperature, Stefan’s constant, and the intensity of the emitted radiations are used to calculate Planck’s constant. The calculated value of Planck’s constant is found to be 6.102 × 10−34 Js, which closely matches the standard value of Planck’s constant (6.626 × 10−34 Js). This close correlation between the two values validates the effectiveness of the present method.
Corrigendum: Unique reconstruction of the potential for the interior transmission eigenvalue problem for spherically stratified media (2020 Inverse Problems 36 035017)
Authors: Wei Zhaoying , Wei Guangsheng
Published: January 2025

We correct theorems 3.2 and 4.1 in the above paper.
Applying stochastic Langevin function with coupled Brownian–Néel relaxations to study the dynamic magnetizations of nanoparticle tracers in magnetic particle imaging
Authors: Azizi Ebrahim , Mostufa Shahriar , Rezaei Bahareh , Xin Shumin , Sun Jiajia , Shi Zongqian , Gómez-Pastora Jenifer , Wu Kai
Published: January 2025

Magnetic particle imaging (MPI) is a new imaging technique that utilizes biologically safe iron oxide nanoparticle tracers for medical imaging. Although in the preclinical stage, MPI has shown strong potential for applications such as cell tracking, angiography, cancer imaging, etc. With the ever-growing research interest in MPI and the increasing desire to apply it in clinical medical imaging, the design of tracers, MPI systems, image reconstruction algorithms, and other related components has become increasingly critical. To date, most of the theoretical studies in MPI rely on the static Langevin function to describe the magnetization responses of superparamagnetic iron oxide nanoparticle (SPION) tracers. However, under a fast-changing excitation field (usually tens of kHz), the magnetic relaxation time of SPION tracers is no longer negligible, thus, the static Langevin function is inaccurate in explaining the tracers’ magnetic signals in MPI. Herein, we apply a stochastic Langevin function with coupled Brownian–Néel relaxation models to study the dynamic magnetization responses of SPION tracers in MPI. The time domain magnetization responses (M–t curve), dynamic magnetization-field hysteresis loops (M–H curve), and point spread functions are modeled for different SPION tracer designs with varying physical and magnetic properties. Our results show that larger magnetic core sizesreduce the MPI spatial resolution. Conversely, thicker non-magnetic coatings on tracers do not significantly affect the spatial resolution. The increased anisotropy diminishes the MPI resolution, and a higher saturation magnetization favors higher MPI resolution.
The surface termination of a Fe (III) spin crossover molecular salt
Authors: Zaz M Zaid , Tamang Binny , McElveen Kayleigh , Mishra Esha , Viswan Gauthami , Chin Wai Kiat , Subedi Arjun , N’Daiye Alpha T , Lai Rebecca Y , Dowben Peter A
Published: January 2025

From a comparison of the known molecular stoichiometry and x-ray photoemission spectroscopy, it is evident that the Fe(III) spin crossover salt [Fe(qsal)2Ni(dmit)2] has a preferential surface termination with the Ni(dmit)2 moiety, where qsal = N(8quinolyl)salicylaldimine, and dmit2− = 1,3-dithiol-2-thione-4,5-dithiolato. This preferential surface termination leads to a significant surface to bulk core level shift for the Ni 2p x-ray photoemission core level, not seen in the corresponding Fe 2p core level spectra. A similar surface to bulk core level shift is seen in Pd 3d in the related [Fe(qsal)2]2Pd(dmit)2. Inverse photoemission spectroscopy, compared with the x-ray absorption spectra at the Ni-L3,2 edge provides some indication of the density of states resulting from the dmit2− = 1,3-dithiol-2-thione-4,5-dithiolato ligand unoccupied molecular orbitals and thus supports the evidence regarding surface termination in the Ni(dmit)2 moiety.
MFFOD: multidomain feature fusion object detector for infrared images
Authors: Xu Wenxiao , Yin Qiyuan , Xu Cheng , Zhao Zhe , Li Yao , Huang Daqing
Published: January 2025

Infrared imagery surpasses the limitations of visible light images and finds widespread applications in fields such as military reconnaissance and security surveillance. Recent studies on infrared target detection aim to preserve local features and global representations to the greatest extent. However, compared to visible light images, infrared images exhibit inherent challenges such as insufficient texture information and coarse boundaries, which introduce new difficulties to this research. To address these issues, this paper introduces additional information cues from the perspective of enriching feature map information. Specifically, we propose a multidomain feature fusion object detector (MFFOD), whose backbone feature extraction network consists of a convolutional branch and a fast Fourier transform branch. This hybrid domain representation enables the extraction of both domain-specific information and global high-frequency and low-frequency information with minimal computational overhead. Furthermore, in the intermediate layers of the network, we have carefully designed a feature injection module that enables comprehensive interaction between channel features and spatial features within a single feature map. Experimental results demonstrate that MFFOD achieves average detection accuracies of 88.97%, 90.32%, and 99.25% on three significant infrared scene datasets, outperforming existing target detection methods. We hope that this general detection algorithm will provide a robust reference for future infrared target detection research.
ST-CIRL: a reinforcement learning-based feature selection approach for enhanced anxiety classification
Authors: Shikha  , Sethia Divyashikha , Indu S
Published: January 2025

Objective. To propose and validate the SMOTETomek-correlated interactive reinforcement learning (ST-CIRL) framework for anxiety classification using physiological signals, addressing class imbalance, and optimizing feature selection to enhance classification accuracy. Approach. The proposed framework integrates SMOTETomek to handle class imbalance and employs meta-descriptive statistics to refine feature representation. Interactive reinforcement learning (IRL) is used for feature selection through collaboration among multiple agents. Dimensionality is further reduced by pruning redundant features. Machine learning classifiers, including random forest (RF), support vector machine (SVM), K-nearest neighbor (KNN), and light gradient boosting machine (LGBM), are optimized using the optuna approach to enhance performance. Main Results. The ST-CIRL framework achieved a maximum accuracy of 95.35% and an F1-score of 95.49% using the LightGBM classifier, outperforming state-of-the-art methods. These results demonstrate the effectiveness of SMOTETomek and the innovative reinforcement learning based feature optimization approach. Significance. This study highlights the potential of reinforcement learning in advancing human-computer interaction (HCI) systems by improving anxiety classification accuracy. The proposed framework’s methodology provides a robust foundation for future research in intelligent system design and its application to physiological signal analysis.
Highly tunning of dielectric and photocatalytic properties of crystalline ZnO semiconductor: functionality of Ba additives
Authors: Massoudi Imen
Published: January 2025

In the present work, the concentration of Ba-additive played a significant role in advancing the dielectric properties and photo-removal activity of ZnO semiconductor for methylene blue dye. Ba doped ZnO semiconductor with different doping concentrations (Zn1−xBaxO, x = 0.003, 0.005, 0.007 and 0.009 wt%) were grown by solid-state reaction route. The x-ray diffraction (XRD) data confirmed the formation of the wurtzite structure of ZnO along with the presence of BaO-based secondary phase (SP). The XRD peak intensity related to the SP was found to increase with the increase of Ba concentration. Microstructural analyses through scanning electron microscope (SEM) images and energy-dispersive x-ray analysis (EDS) showed that with the addition of Ba, a gradual increase in the grain size was observed. Furthermore, SP segregated at the grain boundary and showed an increasing trend with doping. The emergence of secondary phases with Ba concentration was confirmed with the help of supplementary spectroscopic characterizations including Fourier transform infrared spectroscopy (FTIR) and UV–vis diffuse reflectance. The presence of BaO secondary phase has shown a benefit effect on the dielectric and photodegradation properties of ZnO material. The remarkable resistance reduction suggested that the higher Ba concentrations significantly enhance charge carrier mobility. For wastewater treatment uses, BZO9 photocatalyst exhibited a perfect degradation efficiency of 90.1% for methylene blue (MB) removal after 210 min of visible light illumination.
Bifacial perovskite/silicon tandem solar cell with Ag nanoparticles as an intermediate layer
Authors: Abbasiyan Amin , Golmohammadi Saeed
Published: January 2025

This study investigates a four-terminal (4T) bifacial Perovskite/Silicon (PVK/Si) tandem solar cell using 3D finite element method (FEM) simulation. An intermediate layer containing Ag nanoparticles (NPs) is introduced between the sub-cells which the NP radius of 47.5 nm has shown the suitable performance, balancing the top and bottom cell absorption. The main purpose of using Ag NPs at the intermediate layer is to enhance the absorption and improve the electrical characteristics of PVK top cell. Implementing of the optimized NPs results an improvement of the top cell’s Jsc by 4.7% (reached to 19 mA.cm−2) also, the power conversion efficiency (PCE) has been increased by 11% (reached to 18.27%) in comparison with the cell without NPs. Following the optimization of the intermediate layer, the structural parameters of the bottom cell’s interdigitated back contact (IBC) have been investigated under the global albedo reflection (0.3 × AM1.5G). The optimized configuration for the bottom cell has been achieved at Λ = 1 mm and G/W = 2, resulting the Jsc and PCE of 20.78 mA.cm−2 and 11.5%, respectively. The final optimized structure exhibited a total PCE of 31.1%, representing an 11.5% improvement compared to the cell without albedo reflection.
Effect of Refugia Plant Combination with Biopesticide Application on Population and Attack Intensity of Spedoptera exigua (Hubner) (Lepidoptera; Noctuidae)
Authors: Rezki A A , Sjam S , Tamrin
Published: January 2025

Spodoptera exigua is an insect that is an essential pest in shallot plants. Spedoptera exigua is generally controlled with chemical insecticides, which can impact the environment and natural enemy populations. Using a combination of flowering plants and applying plant extracts is one of the environmentally friendly alternatives to reduce population and damage. This study was conducted in Enrekang Regency in South Sulawesi using an RCBD with five treatments and three replications. The treatments are flower, plant extract, flower and plant extract, farmer’s method, and control. Flowering plants were planted at the edge of the bed. Observations were made visually and using a sweepnet. The application of plant extracts and observations were made seven times weekly. Observations were made on the parameters of egg groups, larval populations, attack intensity, and natural enemy populations. The results showed that the treatment refugia plant and plant extract reduced the egg population by 76.64% and the larval population by 92.59%. It increased the population of natural enemies by 72.26%. The farmer treatment reduced the intensity of the attack by 65.03%, which was not significantly different from the flower treatment with plant extracts, with a percentage reduction of 59.38%.
Occupational Health and Safety Risk Control at X Teaching Factory
Authors: Adhyatma M. , Julianto Suyoso Gandu Eko , Rahagiyanto Angga , Azhar Faruq Avero , Vestine Veronika
Published: January 2025

UHT (Ultra High Temperature) milk factories are complex environments with numerous inherent risks due to the high-temperature processes, sophisticated machinery, and extensive use of chemicals. These factors create a hazardous workplace where managing occupational safety and health is crucial to prevent accidents, protect worker health, and maintain production efficiency. The primary objective of this study is to identify and control the hazard in the UHT milk facility of X Teaching Factory (Tefa). The data collected by walkthrough survey, observation and interview. The team then conducted a literature review to map out the types of hazards, sources of hazards, potential impacts, analyze the risk and provide risk control recommendations. The study identified five types of workplace hazards: explosion and fire hazards, physical hazards, chemical hazards, ergonomic hazards, and slips, falls and trips hazards. Among these, The highest risks present at the X Tefa were fall, slip, and trip hazards as well as fire and explosion hazards. The recommended controls focused on substitution, engineering controls, administrative controls, and personal protective equipment, as it was not feasible to eliminate the machines/materials/processes used at X Tefa. Although X Tefa is not yet operational, it is crucial to implement risk control measures as early as possible to prevent workplace accidents and occupational diseases once X Tefa becomes fully operational.
Effect of Low Temperature on Physical Characteristics of Chicken (Gallus domesticus) Meat During Storage
Authors: Risnawati H , Triani R , Purwandoko P B , Mayasti N K I , Susanti N D , Novianti F , Aprianto I F , Litaay C , Kuala I S , Indriati A , Pristianto E J , Rahman A N , Kurniawan E D
Published: January 2025

Chicken meat is highly perishable and requires special handling because it spoils quickly during the metabolic processes after slaughter. Poor handling and storage methods can lead to a decline in meat quality. Storing chicken at low temperatures, such as in a refrigerator at 4°C, helps extend its shelf life and preserve its qualities. This study aimed to examine the changes in the physical properties of raw chicken meat stored at 4°C. The research was conducted using a Completely Randomized Design (CRD) with five storage periods: day 0, day 2, day 4, day 6, and day 8. The physical characteristics observed were pH, color, aroma, texture, and drip loss. The length of storage at 4°C significantly affected the chicken’s pH, color, texture, water loss, and aroma quality (P<0.05). The color analysis showed that the lightness (L*) and greenness (a*) values increased, while the yellowness (b*) values also increased. The texture, including hardness, springiness, cohesiveness, gumminess, chewiness, and resilience, decreased over time. Prolonged storage at low temperatures (4°C) reduced pH, increased water loss, and changes in color, aroma, and texture. Overall, storage time significantly impacted the physical characteristics of raw chicken meat stored at 4°C.
Effect of Seed Biopriming with Pseudomonas fluorescens for Increasing Seed Quality of Kenaf (Hibiscus cannabinus L.) Cultivar KR 14
Authors: Azizah M , Cahyaningrum DG , Utami CD , Rohman F , Dinata GF
Published: January 2025

Kenaf is a seasonal plant that produces fiber with biomass that has the potential to be developed as animal feed at the Animal Feed Tefa of Jember State Polytechnic. The quality of seed that planted can affect crop yield and quality. Seed priming can stimulate germination to overcome the problem of low physiological quality of kenaf seeds due to storage. Trichoderma is one of the biological agents that can be used as a seed priming material. This study aims to determine the effect of biological agents for seed priming on increasing the quality of kenaf seeds. The research was conducted from June to August 2024 at Seed Technology Laboratory of Jember State Polytechnic. The research was arranged using a nonfactorial completely randomized design. The treatment applied was control (without soaking agent), 1 hour seed soaking with Pseudomonas fluorescens isolate, 2 hours seed soaking with P. fluorescens isolate, and 3 hours seed soaking with P. fluorescens isolate. The observations made were Seed Germination (%), Growth Rate (%), Vigor Index (%), sprout shoot length (cm) and root length (cm). The results showed that seed biopriming using P. fluorescens increasing seed germination and seed vigor percentage. The recommended seed soaking treatment for seed priming kenaf seeds with low initial viability is soaking for 1 hour.
Effect of acetic acid concentration on physicochemical characteristics of collagen from mackerel fish waste (Euthynnus affinis)
Authors: Budiati T , Suryaningsih W , Ardiyansyah M , Cahyani A B D , Utami M M D
Published: January 2025

Utilization of mackerel fish waste from the fish processing industry into collagen can increase the value of by-products. The aim this study was to investigate the effect of acetic acid concentration on physicochemical characteristics of collagen from mackerel fish waste (Euthynnus affinis). Different concentration of acetic acid (0.1, 0.5, 0.9, 1.5 M) was carried out to extract collagen. The water content was ranging from 1.06 to 1.42%, ash content was ranging from 5.27 to 5.86%, protein content was ranging from 75.22 to 80.87%, white degree was ranging from 73.60 to 81.08%. Amino acids contents were alanine, glutamic acid, glycine, leucine, lysine, methionine, proline, valine, tyrosine, aspartate acid. The best treatment was found on 1.5 M of acetic acid.
Yield test of oriental melon in Tasikmalaya, West Java
Authors: Wahyudi Anung , Sari Siska Yunita , Pandu Pradana Onny Chrisna
Published: January 2025

Melon plants (Cucumis melo L) are horticultural commodities cultivated in Indonesia. This study aims to describe five oriental melon genotypes in Tasikmalaya (500 meters above sea level) as a multilocation test. The research was carried out from December 2023 to February 2024. Multilocation testing is one of the stages of plant breeding before the release of new superior varieties. The genetic material used in this research is Ginsen Makuwauri; F1 MM 0201-02; Ougan Makuwauri; F1 MM 0102-16; and Golden Langkawi (comparison variety). This research design used a Randomized Block Design (RBD) with five treatments and three replications to obtain 15 experimental units. Observation of research data uses the standards of the International Union for the Protection of Plants (UPOV), the International Plant Genetic Resources Institute (IPGRI), and the Decree of the Indonesian Minister of Agriculture. Data were analyzed using the F-test and continued with a LSD test at the 5% level. The results showed that there was a diversity of quantitative and qualitative characteristics from all the genotypes tested. Based on the diversity of quantitative and qualitative characteristics of the five genotypes tested, three superior genotypes were selected, namely F1 MM 0201-02; F1 MM0102-16; and Ougan Makuwauri. Genotype F1 MM 0201-02 has superior quantitative characters in the parameters of internode length (7.33 cm), fruit weight per plant (151.28 g), fruit length (9.21 cm), fruit width (5.30 cm), and the fruit flesh is thicker (1.17 cm) than the comparison variety.
Application of Combined Coffee Skin Husk Biochar and Rice Husk Charcoal as Planting Media to Improve on the Growth Seedling Coffee
Authors: Rosdiana E , Nugroho S A , Wardana R , Salim A , Ali F Y
Published: January 2025

Coffee is a plantation commodity in great demand and has a fairly good economic value. One way to get good coffee is to see good cultivation methods, especially in its nursery. Good nurseries can utilize Biochar coffee skin and rice husks. This study aims to obtain quality coffee seeds by creating an alternative biochar planting media formulation derived from coffee skin waste and rice husk charcoal. The main ingredients for making biochar are agricultural and plantation wastes such as rice husk charcoal and coffee fruit skin. This study used a non-factorial completely randomized design (CRD). The treatment factor used was a mixture of rice husk charcoal media with coffee husk biochar comprising 5 treatment levels. Each treatment was repeated 5 times, so there were 25 experimental units. The experimental analysis used was the Analysis of variance. The further test used the LSD test. The results showed that the treatment of a mixture of coffee husk and rice husk biochar affected the stem diameter plant and the number of leaf plants.
Physical characteristics of various green feed crackers as a small-ruminant supplement
Authors: Syahniar TM , Andriani M , Nurkholis  , Ningsih N , Lestari D
Published: January 2025

Purposes of this research were to evaluate dimensions and physical characteristics of various green feed crackers as a small-ruminant supplement. It was made using Odot grass (T1), Gliricidia leaves (T2), Leucaena leaves (T3), mixture of Gliricidia and Leucaena (T4), and 2 other formulations of legume mixture with other feed ingredients (T5 and T6). They were designed using a pattern of Completely Randomized Design (CRD) into 6 treatment levels with 3 replications. Each level treatment was mixed with molasses, homogenized, molded using a quadrangle-shaped mold containing 9 pieces with pressure, then baked in the oven of 60°C overnight. Green feed crackers were analysed the physical characteristic which using parameters observed on dimension, specific density, bulk density, tapped bulk density, and hardness. Data were assessed using ANOVA and followed using DMRT to identify significant differences between treatment levels. Each piece of green feed crackers was ranged 20-27 g/piece with dimensions average of (61*61*11) mm. Results denoted that the treatment affected (P<0.0001) dimensions, bulk density and tapped bulk density of green feed crackers however presented similar number on the specific density and hardness. It was implied that the variation and properties of feedstuffs used influenced physical characteristics of the green feed crackers.
Potential Loss of Body Weight in Bull Transportation and the Effect of Adding Acacia mangium Bark Extract During Recovery Period
Authors: Sujarnoko TUP , Budiono D , Sholeha NA , Siskandar R , Syahniar TM , Andriani M , Prastujati AU
Published: January 2025

The transportation process of the bull can induce stress, affecting decreasing body weight and causing a loss for farmers. This study focuses on body loss affected by transportation from Magetan to Bogor and recovery after transportation. This research used 10 cross-breed bulls from Magetan East Java and transported them to Bogor West Java for 16 hours. The bull weighed on Magetan before being transported and Bogor after a 10-hour recovery. The first experiment compares transported bulls and non-transported Bulls. The second experiment focused on recovery after transportation with treatment on the ransom (T0: Control, T1: Control + 0.4% Acacia extract) The experimental design was a randomized block design with two treatments and a tree block based on body weight. The parameters tested included body weight loss, blood metabolism, economic loss, Average daily gain, and opportunity recovery using acacia extract. Results showed that transportation decreased body weight until 9.47±0.76% or Rp. 473,507.00/tail. The transportation significantly increased blood urea nitrogen (p<0.05) and did not affect cholesterol, creatinine, or Uric acid p>0.05. Added acacia extract of 4% significantly decreased body losses and creatinine after 10 days of recovery time (P<0.05). The added extract did not affect cholesterol, uric acid, and blood urea nitrogen (p>0.05). In conclusion, transportation caused the loss, and adding 0.4% Acacium mangium bark with a pressure hot water extraction method improved the body recovery of the Bull after transportation.
Development Strategy of Agribusiness Teaching Factory Pilot at PSDKU Sidoarjo using SWOT Analysis and Lean Canvas Business Model
Authors: Slamet A H H , Mutmainah D N , Brillyantina S , Wulandari S A , Dhandy R , Julianti S E N
Published: January 2025

The Teaching Factory is a strategic initiative of Politeknik Negeri Jember for the year 2020-2024, implementing the one department, one teaching factory policy. The TEFA most suitable for establishment at Campus 4 is TEFA Agribusiness. This teaching factory adopts the structure of a minimarket, encompassing all aspects of agribusiness operations from processing to product marketing. The objective of this research was to develop a TEFA Agribusiness design strategy using the lean canvas business model and SWOT analysis. The research findings indicated that PSDKU Sidoarjo’s agribusiness teaching factory pilot has significant viability for development. The SWOT analysis classified the teaching factory startup as being in cell I, which represents growth and build. The techniques for implementation include intense operations (market penetration, market development, and product creation) and integrative approaches (backward integration, forward integration, and horizontal integration).
Bioethanol Production with Semi Continue Fermentation Distillation Equipment using Sacharomyces Cerevisiae
Authors: Ayu Febriani Siti Diah , Susmiati Yuana , Subagja Hariadi , Qanitah  , Afianah Nuzula , Faqih Abdilah
Published: January 2025

Ethanol produced from fermentation of biomass that consist of carbohydrates, cellulose or glucose with the aid of microorganisms namely Bioethanol. This research was to developing a bioethanol production tool with a fermentation and semi continue distillation using a stirred bioreactor and evaluate the productivity of bioethanol fermentation with saccharomyces cerevisiae that capable of concentration ethanol to support development activities at Teaching Factory (TEFA) Renewable Energy as the Bioenergy competency testing center. The method of the research using an experimental method use system of semi continue with the research stages included the design, fabrication, installation of sensors and final functional testing of the equipment. The research was carried out ethanol production were observed every 12-hours interval during 72 hours fermentation time. The results showed that process of semi continue fermentation done only for 72 hours when the brix concentration is 20 (start). Based on the research it is known that reducing sugar concentration (brix) and pH will decrease as fermentation time increase. The fermentation process carried out produced 66,49% bioethanol.
Fast correction method for the translation position error of ptychography
Authors: Dou Jiantai , Li Xu , Hu Youyou
Published: January 2025

Translation position errors in ptychography can significantly reduce the reconstruction quality. It is crucial to obtain the accurate translation positions between the probe and the object. Current methods for correcting the translation position error are applied into the iterative process of ptychography that will increase the computation time of a single iteration, and take much time to correct the translation position error and obtain a high reconstruction quality. A sub-pixel block matching method is proposed to ultrafast correct the translation position errors and greatly reduce the correction time. This method is applied in the preprocessing stage before iterations that does not increase the computational burden of a single iteration in ptychography and can quickly correct the translation position error. Simulations and experiments demonstrate that our method can significantly improve computational efficiency with ensuring correction accuracy.
Atomically thin metallenes at the edge
Authors: Abidi Kameyab Raza , Bagheri Mohammad , Singh Sukhbir , Koskinen Pekka
Published: January 2025

Atomically thin metallenes are a new family of materials representing the ultimate limit of a thin free-electron gas for novel applications. Although metallene research has gained traction, limited attention has been paid to the properties of their ubiquitous edges. Here, we use density-functional theory simulations to investigate various edges of Mg, Cu, Y, Au, and Pb metallenes with hexagonal and buckled honeycomb lattices. Investigating relaxations, energies, stresses, and electronic structures at the edge, we find that some properties have clear trends while others are sensitive to both element and lattice type. Given that edge properties are fundamental to metallene stability and interactions in lateral heterostructures, their detailed understanding will help guide the development of metallene synthesis and applications.
Three-dimensional phloretin-functionalized graphene aerogel for high-performance supercapacitors and phase change materials
Authors: Yang Jingjing , Gong Xiaobin , Su Tianyu , Chen Hong , Han Yongle , Li Yanan , Bao Jinxiao , Ge Xin , Pan Gaofei , Xing Ruiguang
Published: January 2025

Graphene aerogels have attracted considerable attention owing to their significantly higher electrical and thermal conductivity compared with conventional materials. To further enhance the surface functionality of graphene aerogels, we prepared three-dimensional multi-functional aerogels via hydrothermal treatment and freeze-drying using natural green organic small-molecule compound phloretin and graphene oxide. This aerogel has excellent electrochemical properties, with a specific capacitance as high as 433 F g−1 (at a current density of 1 A g−1). In addition, symmetrical supercapacitors (SCs) assembled with this electrode material exhibit excellent energy storage performance with an energy density of 13.33 W h kg−1, power density of 399.9 W kg−1 and capacitance retention rate of 88% after 10 000 cycles. Furthermore, a phase change material prepared using the aerogel and pure paraffin wax shows significantly higher energy conversion efficiency than sole paraffin wax and exhibits good thermal stability. Overall, owing to its unique physicochemical properties and environmental friendliness, the prepared multi-functional aerogel has good application prospects in the fields of SCs and thermal management.
A comparison of different machine learning classifiers in predicting xerostomia and sticky saliva due to head and neck radiotherapy using a multi-objective, multimodal radiomics model
Authors: Khajetash Benyamin , Hajianfar Ghasem , Talebi Amin , Ghavidel Beth , Mahdavi Seied Rabi , Lei Yang , Tavakoli Meysam
Published: January 2025

Background and Purpose. Although radiotherapy techniques are a primary treatment for head and neck cancer (HNC), they are still associated with substantial toxicity and side effects. Machine learning (ML) based radiomics models for predicting toxicity mostly rely on features extracted from pre-treatment imaging data. This study aims to compare different models in predicting radiation-induced xerostomia and sticky saliva in both early and late stages HNC patients using CT and MRI image features along with demographics and dosimetric information.

Materials and Methods. A cohort of 85 HNC patients who underwent radiation treatment was evaluated. We built different ML-based classifiers to build a multi-objective, multimodal radiomics model by extracting 346 different features from patient data. The models were trained and tested for prediction, utilizing Relief feature selection method and eight classifiers consisting eXtreme Gradient Boosting (XGBoost), Multilayer Perceptron (MLP), Support Vector Machines (SVM), Random Forest (RF), K-Nearest Neighbor (KNN), Naive Bayes (NB), Logistic Regression (LR), and Decision Tree (DT). The performance of the models was evaluated using sensitivity, specificity, area under the curve (AUC), and accuracy metrics.

Results. Using a combination of demographics, dosimetric, and image features, the SVM model obtained the best performance with AUC of 0.77 and 0.81 for predicting early sticky saliva and xerostomia, respectively. Also, SVM and MLP classifiers achieved a noteworthy AUC of 0.85 and 0.64 for predicting late sticky saliva and xerostomia, respectively.

Conclusion. This study highlights the potential of baseline CT and MRI image features, combined with dosimetric data and patient demographics, to predict radiation-induced xerostomia and sticky saliva. The use of ML techniques provides valuable insights for personalized treatment planning to mitigate toxicity effects during radiation therapy for HNC patients.
Carbon fiber tow incorporated with carbon slurry for structural power composite electrodes
Authors: So Byeong Jun , Shin Gilyong , Choi Yuseung , Lee Hoyeon , Jeon Jei Gyeong , Kang Tae June
Published: January 2025

Structural power composites are multifunctional materials that store electrical energy while supporting mechanical loads. Herein, we present mechanically robust and electrochemically high-performance electrodes for structural power composites, achieved by incorporating a carbon slurry into a carbon fiber (CF) tow. The carbon slurry consisted of activated carbon as the active material for electrochemical double-layer charging, carbon black as the electrical path, and polyvinylidene fluoride (PVDF) as the binder that are typical components used in double-layer supercapacitors. N-methyl-2-pyrrolidone (NMP) was used as the solvent. The composition of the carbon slurry was adjusted to evaluate the bond strength between the electrode materials and CFs using peel tests, followed by evaluation of the specific capacitance per unit weight of the corresponding electrode materials using cyclic voltammetry. The CF electrodes were fabricated by adjusting the amount of the NMP solvent in the slurry to ensure a high electrode material content while achieving uniform infiltration and coating of the slurry components within the CF tow. The electrodes were used to fabricate structural supercapacitors by coating them with polyvinyl alcohol (PVA) gel electrolytes containing potassium acetate and then sandwiching two such electrodes. The fabricated supercapacitors exhibited a specific capacitance of 24 F g−1 and a tensile strength of ∼390 MPa. In addition, series and parallel connections of the supercapacitors were demonstrated to demonstrate the scalability of the electrodes in terms of voltage and power output.
Investigation on the optimized curing cycle of epoxy resin for enhancing thermal and mechanical properties of glass fiber reinforced plastic applications
Authors: Kang Seung In , Son Seung Mo , Heo Su Jeong , Seong Dong Gi
Published: January 2025

Understanding the thermal and mechanical behavior of epoxy resins under varying curing conditions is critical for optimizing the performance of fiber-reinforced plastics (FRP) in industrial applications. This study investigates the influence of curing temperature and post-curing stages on key epoxy properties, including heat distortion temperature (HDT), glass transition temperature (Tg), and crosslinking density, and evaluates their impact on the performance of glass FRPs (GFRPs). Two epoxy resin systems with distinct Tg were examined using differential scanning calorimetry to asses curing behavior and dynamic mechanical analysis to evaluate HDT, Tg, and crosslinking density. As curing temperature increased, the 1050/1056 epoxy resin system exhibited improvements in HDT, Tg, and crosslinking density (up to 69 °C, 78.3 °C, and 1674.6 mol m−3 respectively) with further enhancements observed after post-curing. Similarly, under the same conditions, the 1800/1805 epoxy resin system demonstrated changed value (up to 97 °C, 108.9 °C, 2287.6 mol m−3 respectively) with further improvements observed after post-curing. These changes in properties were validated through GFRP performance metrics, with tensile strength reaching up to 558.5 MP and shore A hardness up to 92.5 under optimized curing conditions. These findings reveal how curing conditions significantly affect both the thermal and mechanical properties of epoxy and epoxy-based composites, offering valuable insights for tailoring performance in applications such as molds, structural components, and high-precision industrial systems.
Introduction of 3D-printed porous structures with interconnected porosities via rotation of each layer around a normal axis: Investigating the effects of annealing and printing parameters on the compressive strength and modulus of the structures
Authors: Safi Jahanshahi Amin , Akhoundi Behnam
Published: January 2025

This study introduces 3D-printed porous structures made of polylactic acid (PLA) with interconnected porosities for tissue engineering as an alternative to bone scaffolds. Then the effects of process parameters and annealing heat treatments on the compressive strength and modulus of the porous samples have been investigated. The examined parameters include extrusion width, layer height, infill pattern, and infill percentage. To create porous structures with interconnected porosities, the infill pattern is rotated by eighteen degrees in each layer, forming new porous structures that can be utilized as bone scaffolds in tissue engineering. After evaluating the compressive mechanical properties of the samples and examining the effects of printing parameters on them, similar samples were subjected to heat treatment, and their compressive mechanical properties were also investigated. The results indicate that the maximum compressive strength and modulus occur in the sample with an extrusion width of 0.6 mm, a layer height of 0.25 mm, a wiggle infill pattern, and a maximum infill percentage. The un-heat-treated sample’s compressive strength and modulus values are 84.51 MPa and 2.28 GPa, respectively. In contrast, these values are 105.44 MPa and 2.29 GPa for the heat-treated sample.
Design and control of redundant-actuated Six-DOF micropositioning stage with magnetic gravity compensation
Authors: Tang Xu , Xu Yifan , Liu Xingyu
Published: January 2025

The performance of ultra-precision positioning stages is particularly critical in the field of ultra-precision manufacturing. This paper presents the design of an eight-actuator redundant six-degree-of-freedom micropositioning stage with magnetic suspension gravity compensation (6-DOF RDMS). All drives are electromagnetic direct-drive systems based on voice coil motors (VCMs). The vertical motors incorporate a Halbach array and a magnetic suspension gravity compensation structure. A mathematical model and a finite element model are established for the designed positioning stage. The models are utilized for magnetic field and magnetic force analysis, thermal analysis, and analysis of the dynamic force-induced deformation of stator to ensure operational stability. A decoupling control system for the six-degree-of-freedom micropositioning stage is developed, mapping the six degrees of freedom to the control loops of the eight actuators to achieve high-precision positioning. Finally, a prototype was constructed, validating the effectiveness and feasibility of the structural design and the decoupling control system.
Convolutional neural network-based wire-cut image recognition and defect detection research
Authors: Li Xiaopeng , Wang Yuangang , Wang Zhen
Published: January 2025

This paper presents an advanced defect detection system for wire Electrical Discharge Machining (EDM), utilizing Convolutional Neural Networks (CNNs) to automatically identify, classify, and localize defects such as cracks, notches, and burrs. Wire EDM is a precision manufacturing process critical for cutting conductive materials, where defect detection plays a vital role in ensuring product quality. The proposed method incorporates a modified ResNet-50 architecture, optimized specifically for defect detection in wire EDM. The architecture leverages deep residual learning to enhance feature extraction, allowing the system to detect minute defects effectively. A dataset of 10,000 RGB images (224 × 224 pixels) was used for training, with the model achieving an impressive 95.3% accuracy, 94.2% recall, 95.8% precision, and 94.7% F1 score on the test set. The system demonstrated excellent performance in detecting cracks, though it showed slightly lower performance on deformation-related defects. A comprehensive comparison with traditional defect detection methods and other deep learning models underscores the superiority of the proposed approach in terms of both accuracy and robustness. The results indicate that this CNN-based system offers a reliable and efficient solution for quality control in wire EDM processes. Future research will focus on further optimizing the network for real-time defect detection and extending the approach to incorporate multi-modal data, such as sensor and acoustic signals, to improve overall detection performance.
Into the latent space of capacitive sensors: interpolation and synthetic data generation using variational autoencoders
Authors: Honrubia Miguel Monteagudo , Herraiz-Martínez Francisco Javier , Domingo Javier Matanza
Published: January 2025

For many sensing applications, collecting a large experimental dataset could be a time-consuming and expensive task that can also hinder the implementation of Machine Learning models for analyzing sensor data. Therefore, this paper proposes the generation of synthetic signals through a Variational Autoencoder (VAE) to enlarge a spectra dataset acquired with a capacitive sensor based on a Dielectric Resonator. Trained with signals of several water/glycerine concentrations, this generative model learns the dataset characteristics and builds a representative latent space. Consequently, exploring this latent space is a critical task to control the generation of synthetic signals and interpolating concentrations unmeasured by the sensor. For this reason, this paper proposes a search method based on Bayesian Optimization that automatically explores the latent space. The results show excellent signal reconstruction quality, proving that the VAE architecture can successfully generate realistic synthetic signals from capacitive sensors. In addition, the proposed search method obtains a reasonable interpolation capability by finding latent encodings that generate signals related to the target glycerin concentrations. Moreover, this approach could be extended to other sensing technologies.