Elucidating and forecasting the organochlorine pesticides in suspended particulate matter by a two-stage decomposition based interpretable deep learning approach.

Accurately predicting the concentration of organochlorine pesticides (OCPs) presents a challenge due to their complex sources and environmental behaviors. In this study, we introduced a novel and advanced model that combined the power of three distinct techniques: Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Variational Mode Decomposition (VMD), and a deep learning network of Long Short-Term Memory (LSTM). The objective is to characterize the variation in OCPs concentrations with high precision. Results show that the hybrid two-stage decomposition coupled models achieved an average symmetric mean absolute percentage error (SMAPE) of 23.24 % in the empirical analysis of typical surface water. It exhibited higher predictive power than the given individual benchmark models, which yielded an average SMAPE of 40.88 %, and single decomposition coupled models with an average SMAPE of 29.80 %. The proposed CEEMDAN-VMD-LSTM model, with an average SMAPE of 13.55 %, consistently outperformed the other models, yielding an average SMAPE of 33.53 %. A comparative analysis with shallow neural network methods demonstrated the advantages of the LSTM algorithm when coupled with secondary decomposition techniques for processing time series datasets. Furthermore, the interpretable analysis derived by the SHAP approach revealed that precipitation followed by the total phosphorus had strong effects on the predicted concentration of OCPs in the given water. The data presented herein shows the effectiveness of decomposition technique-based deep learning algorithms in capturing the dynamic characteristics of pollutants in surface water.

Fully integrated sensor array for additives, permittivity, and pH monitoring for fishery.

Additive abuse in fishery, such as tricaine methanesulfonate (MS222), ciprofloxacin (CPFX), and malachite green (MG), threatens public human health and interferes with the ecological equilibrium of water resources. However, the majority of the present detection methods suffer from high costs, complex operations, and poor portability. Therefore, real-time and rapid detection of the above additive by mobile devices is becoming increasingly important. Here we report the fabrication and performance of an entirely electrochemical system with USB-stick size for simultaneous detection of MS222, CPFX, and MG, as well as pH and permittivity. The limits of detections are 0.17, 0.67, and 0.28 µg/mL, while the resolution ratios are 10 %, 10 %, and 5 % for MS222, MG, and CPFX, respectively. For both pH and permittivity, they have linear regressions measured by brightness and capacitance of the sample respectively, at the range of 1.5-9 (pH) and 10-20 (permittivity). The interference experiments, using target analytes (40 µg/mL) and 15 interfering analytes (80 µg/mL), demonstrated the anti-interference performance of the sensor patches. The field studies on carps, catfishes, and chubs indicated that the developed integrated portable system could be used for real sample analysis with high performance.

Estimating Additive Interaction in Two-Stage Individual Participant Data Meta-Analysis.

Individual participant data (IPD) meta-analysis provides important opportunities to study interaction and effect modification for which individual studies often lack power. While previous meta-analyses have commonly focused on multiplicative interaction, additive interaction holds greater relevance for public health and may in certain contexts better reflect biological interaction. Methodological literature on interaction in IPD meta-analysis does not cover additive interaction for models including binary or time-to-event outcomes. We aimed to describe how the Relative Excess Risk due to Interaction (RERI) and other measures of additive interaction or effect modification can be validly estimated within two-stage IPD meta-analysis. First, we explain why direct pooling of study-level RERI estimates may lead to invalid results. Next, we propose a three-step procedure to estimate additive interaction: 1) estimate effects of both exposures and their product term on the outcome within each individual study; 2) pool study-specific estimates using multivariate meta-analysis; 3) estimate an overall RERI and 95% confidence interval based on the pooled effect estimates. We illustrate this procedure by investigating interaction between depression and smoking and risk of smoking-related cancers using data from the PSYchosocial factors and Cancer (PSY-CA) consortium. We discuss implications of this procedure, including the application in meta-analysis based on published data.

Multifunctional Interface Layer Constructed by Trace Zwitterions for Highly Reversible Zinc Anodes.

The inhomogeneous plating/stripping of Zn anode, attributed to dendrite growth and parasitic reactions at the electrode/electrolyte interface, severely restricts its cycling life-span. Here, trace zwitterions (trifluoroacetate pyridine, TFAPD) are introduced into the aqueous electrolyte to construct a multifunctional interface that enhances the reversibility of Zn anode. The TFA- anions with strong specific adsorption adhere onto the Zn surface to reconstruct the inner Helmholtz plane (IHP), preventing the hydrogen evolution and corrosion side reactions caused by free H2O. The Py+ cations accumulate on the outer Helmholtz plane (OHP) of Zn anode with the force of electric field during Zn2+ plating, forming a shielding layer to uniformize the deposition of Zn2+. Besides, the adsorbed TFA- and Py+ promote the desolvation process of Zn2+ resulting in fast reaction kinetics. Thus, the Zn||Zn cells present an outstanding cycling performance of more than 10000 hours. And even at 85% utilization rate of Zn, it can stably cycle for over 200 hours at 10 mA cm-2 and 10 mAh cm-2. The Zn||I2 full cell exhibits a capacity retention of over 95% even after 30000 cycles. Remarkably, the Zn||I2 pouch cells (95 mAh) deliver a high-capacity retention of 99% after 750 cycles.

High-Resolution Structuring of Silica-Based Nanocomposites for the Fabrication of Transparent Multicomponent Glasses with Adjustable Properties.

Silicate-based multicomponent glasses are of high interest for technical applications due to their tailored properties, such as an adaptable refractive index or coefficient of thermal expansion. However, the production of complex structured parts is associated with high effort, since glass components are usually shaped from high-temperature melts with subsequent mechanical or chemical postprocessing. Here for the first time the fabrication of binary and ternary multicomponent glasses using doped nanocomposites based on silica nanoparticles and photocurable metal oxide precursors as part of the binder matrix is presented. The doped nanocomposites are structured in high resolution using UV-casting and additive manufacturing techniques, such as stereolithography and two-photon lithography. Subsequently, the composites are thermally converted into transparent glass. By incorporating titanium oxide, germanium oxide, or zirconium dioxide into the silicate glass network, multicomponent glasses are fabricated with an adjustable refractive index nD between 1.4584-1.4832 and an Abbe number V of 53.85-61.13. It is further demonstrated that by incorporating 7 wt% titanium oxide, glasses with ultralow thermal expansion can be fabricated with so far unseen complexity. These novel materials enable for the first time high-precision lithographic structuring of multicomponent silica glasses with applications from optics and photonics, semiconductors as well as sensors.

Dual-Functional Interfacial Layer Enabled by Gating-Shielding Effects for Ultra-Stable Zn Anode.

Large-scale application of low-cost, high-safety and environment-compatible aqueous Zn metal batteries (ZMBs) is hindered by Zn dendrite failure and side reactions. Herein, highly reversible ZMBs are obtained by addition of trace D-pantothenate calcium additives to engineer a dual-functional interfacial layer, which is enabled by a bioinspired gating effect for excluding competitive free water near Zn surface due to the trapping and immobilization of water by hydroxyl groups, and guiding target Zn2+ transport across interface through carboxyl groups of pantothenate anions, as well as a dynamic electrostatic shielding effect around Zn protuberances from Ca2+ cations to ensure uniform Zn2+ deposition. In consequence, interfacial side reactions are perfectly inhibited owing to reduced water molecules reaching Zn surface, and the uniform and compact deposition of Zn2+ is achieved due to promoted Zn2+ transport and deposition kinetics. The ultra-stable symmetric cells with beyond 9000 h at 0.5 mA cm-2 with 0.5 mAh cm-2 and over 5000 h at 5 mA cm-2 with 1 mAh cm-2, and an average Coulombic efficiency of 99.8% at 1 mA cm-2 with 1 mAh cm-2, are amazingly realized. The regulated-electrolyte demonstrates high compatibility with verified cathodes for stable full cells. This work opens a brand-new pathway to regulate Zn/electrolyte interface to promise reversible ZMBs.

Joint and interactive associations of body mass index and genetic factors with cardiovascular disease: a prospective study in UK Biobank.

BACKGROUND: Both body mass index (BMI) and genetic factors independently contribute to cardiovascular disease (CVD). However, it is unclear whether genetic risk modifies the association between BMI and the risk of incident CVD. This study aimed to investigate whether BMI categories and genetic risk jointly and interactively contribute to incident CVD events, including hypertension (HTN), atrial fibrillation (AF), coronary heart disease (CHD), stroke, and heart failure (HF). METHODS: A total of 496,851 participants from the UK Biobank with one or more new-onset CVD events were included in the analyses. BMI was categorized as normal weight (< 25.0 kg/m2), overweight (25.0-29.9 kg/m2), and obesity (≥ 30.0 kg/m2). Genetic risk for each outcome was defined as low (lowest tertile), intermediate (second tertile), and high (highest tertile) using polygenic risk score. The joint associations of BMI categories and genetic risk with incident CVD were investigated using Cox proportional hazard models. Additionally, additive interactions were evaluated. RESULTS: Among the 496,851 participants, 270,726 (54.5%) were female, with a mean (SD) age was 56.5 (8.1) years. Over a median follow-up (IQR) of 12.4 (11.5-13.1) years, 102,131 (22.9%) participants developed HTN, 26,301 (5.4%) developed AF, 32,222 (6.9%) developed CHD, 10,684 (2.2%) developed stroke, and 13,304 (2.7%) developed HF. Compared with the normal weight with low genetic risk, the obesity with high genetic risk had the highest risk of CVD: HTN (HR: 3.96; 95%CI: 3.84-4.09), AF (HR: 3.60; 95%CI: 3.38-3.83), CHD (HR: 2.76; 95%CI: 2.61-2.91), stroke (HR: 1.44; 95%CI: 1.31-1.57), and HF (HR: 2.47; 95%CI: 2.27-2.69). There were significant additive interactions between BMI categories and genetic risk for HTN, AF, and CHD, with relative excess risk of 0.53 (95%CI: 0.43-0.62), 0.67 (95%CI: 0.51-0.83), and 0.37 (95%CI: 0.25-0.49), respectively. CONCLUSIONS: BMI and genetic factors jointly and interactively contribute to incident CVD, especially among participants with high genetic risk. These findings have public health implications for identifying populations more likely to have cardiovascular benefit from weight loss interventions.

Assessing abundance-suitability models to prioritize conservation areas for the dwarf caimans in South America.

Species-environment relationships have been extensively explored through species distribution models (SDM) and species abundance models (SAM), which have become key components to understand the spatial ecology and population dynamics directed at biodiversity conservation. Nonetheless, within the internal structure of species' ranges, habitat suitability and species abundance do not always show similar patterns, and using information derived from either SDM or SAM could be incomplete and mislead conservation efforts. We gauged support for the abundance-suitability relationship and used the combined information to prioritize the conservation of South American dwarf caimans (Paleosuchus palpebrosus and P. trigonatus). We used 7 environmental predictor sets (surface water, human impact, topography, precipitation, temperature, dynamic habitat indices, soil temperature), 2 regressions methods (Generalized Linear Models-GLM, Generalized Additive Models-GAM), and 4 parametric distributions (Binomial, Poisson, Negative binomial, Gamma) to develop distribution and abundance models. We used the best predictive models to define four categories (low, medium, high, very high) to plan species conservation. The best distribution and abundance models for both Paleosuchus species included a combination of all predictor sets, except for the best abundance model for P. trigonatus which incorporated only temperature, precipitation, surface water, human impact, and topography. We found non-consistent and low explanatory power of environmental suitability to predict abundance which aligns with previous studies relating SDM-SAM. We extracted the most relevant information from each optimal SDM and SAM and created a consensus model (2,790,583 km2) that we categorized as low (39.6%), medium (42.7%), high (14.9%), and very high (2.8%) conservation priorities. We identified 279,338 km2 where conservation must be critically prioritized and only 29% of these areas are under protection. We concluded that optimal models from correlative methods can be used to provide a systematic prioritization scheme to promote conservation and as surrogates to generate insights for quantifying ecological patterns.

Applications of 3D-printed teeth in dental education: A narrative review.

Background: The contemporary era of education prompts the need for innovation that facilitates the comprehensible and immersive learning of students. Three-dimensional (3D) printing or additive manufacturing in the form of 3D-printed teeth provides an attractive alternative to extracted teeth and standard dental models, as they provide educational equality and realistic simulation of natural teeth. Aim: This review article summarises the literature that has proven the role and effectiveness of 3D-printed teeth in dental education. Method: This review article follows the Scale for the Assessment of Narrative Review Articles (SANRA) guidelines. Two electronic research databases, PubMed and Google Scholar, were used to search for relevant studies. Studies discussing the applications of 3D-printed teeth in dental education were included. Results: The positive and highly valuable role of 3D-printed teeth in dental education has been validated because of their feasible nature. Improvements in dental students' confidence, clinical skills, and learning experiences have also been proven. Conclusion: 3D-printed teeth can serve as a convenient and accessible alternative to extracted and standard dental models for dental education.

Fabrication, sustainability, and key performance indicators of bioelectronics via fiber building blocks.

Bioelectronics provide efficient information exchange between living systems and man-made devices, acting as a vital bridge in merging the domains of biology and technology. Using functional fibers as building blocks, bioelectronics could be hierarchically assembled with vast design possibilities across different scales, enhancing their application-specific biointegration, ergonomics, and sustainability. In this work, the authors review recent developments in bioelectronic fiber elements by reflecting on their fabrication approaches and key performance indicators, including the life cycle sustainability, environmental electromechanical performance, and functional adaptabilities. By delving into the challenges associated with physical deployment and exploring innovative design strategies for adaptability, we propose avenues for future development of bioelectronics via fiber building blocks, boosting the potential of "Fiber of Things" for market-ready bioelectronic products with minimized environmental impact.

Laser ultrasonic detection for defects of LAM components based on variable time window intensity mapping with adaptive 2σ thresholds.

Metallurgical defects in metal laser additive manufacturing (LAM) are inevitable due to complex non-equilibrium thermodynamics. A laser ultrasonic system was designed for detecting surface/near-surface defects in the layer-by-layer LAM process. An approach was proposed for ultrasonic imaging of defects based on variable time window intensity mapping with adaptive 2σ threshold denoising. The Gaussian mixture model hypothesis and expectation-maximization algorithm can automatically differentiate between components dominated by defects and background noises, thereby providing an adaptive threshold that accommodates detection environments and surface roughness levels. Results show that the ultrasonic wave reflection at defect boundaries diminishes far-field ultrasonic intensity upon pulsed laser irradiation on surface defects, enabling defect size and location characterization. This method is applicable to LAM samples with a significant surface roughness of up to 37.5 µm. It can detect superficial and near-surface defects down to 0.5 mm in diameter and depth, making it significant for online defect detection in additive manufacturing.

Serum albumin, genetic susceptibility, and risk of venous thromboembolism.

Background: Previous research on the association between serum albumin (ALB) and venous thromboembolism (VTE) has produced inconclusive results. The polygenic risk score is constructed from a set of independent risk variants associated with a disorder, enabling the identification of a larger fraction of the population at comparable or greater disease risk. It is still unknown whether ALB and genetic factors jointly contribute to the incidence of VTE. Objectives: The present study aimed to explore ALB, genetic susceptibility, and the risk of VTE. Methods: The present investigation was an analysis of prospectively collected data from UK Biobank, a population-based, longitudinal cohort. Cox proportional models were used to calculate hazard ratios and 95% CIs for VTE. The Kaplan-Meier curve was utilized to visualize the cumulative risk of VTE according to different serum ALB levels, and the restricted cubic spline model was leveraged to explore the exposure-response relationship among ALB levels and VTE risk. Results: During median follow-up of 13.5 years, 11,502 cases with VTE were diagnosed among 417,113 participants in the UK Biobank. The lower ALB levels were associated with a higher risk for VTE. Individuals with both a high genetic risk and lowest ALB level had the highest risk of VTE (hazard ratio, 3.89; 95% CI, 3.41-4.43), compared with those with low genetic risk and highest ALB level. The positive joint effects of low ALB and polygenic risk score increased the risk of VTE in individuals with high genetic risk. This study excluded non-European patients and primarily focused on the European population, which may limit the generalizability of the findings. Conclusion: Low serum ALB levels were linked to an increased risk of VTE, which was in accordance with a linear dose-response relationship. There was a positive additive effect of ALB and genetic susceptibility on the risk of VTE. ALB could serve as a biomarker for predicting the risk of VTE.

Characterisation of 3D-printed acetabular hip implants.

Three-dimensional printing is a rapidly growing manufacturing method for orthopaedic implants and it is currently thriving in several other engineering industries. It enables the variation of implant design and the construction of complex structures which can be exploited in orthopaedics and other medical sectors. In this review, we develop the vocabulary to characterise 3D printing in orthopaedics from terms defined by industries employing 3D printing, and by fully examining a 3D-printed off-the-shelf acetabular cup (Fig. 1). This is a commonly used 3D-printed implant in orthopaedics, and it exhibits a range of prominent features brought about by 3D printing. The key features and defects of the porous and dense regions of the implant are clarified and discussed in depth to determine reliable definitions and a common understanding of characteristics of 3D printing between engineers and medical experts in orthopaedics. Despite the extensive list of terminology derived here, it is clear significant gaps exist in the knowledge of this field. Therefore, it is necessary for continued investigations of unused implants, but perhaps more significantly, examining those in vivo and retrieved to understand their long-term impact on patients and the effects of certain features (e.g. surface-adhered particles). Analyses of this kind will establish an understanding of 3D printing in orthopaedics and additionally it will help to update the regulatory approach to this new technology.

Trace alcohol ether electrolytes with dual-site hydrogen bonds and modulated solvation structures for ultralong-life zinc-ion batteries.

Aqueous zinc-ion batteries (AZIBs) are highly regarded for their affordability, stability, safety, and eco-friendliness. Nevertheless, their practical application is hindered by severe side reactions and the formation of zinc (Zn) dendrites on the Zn metal anode surface. In this study, we employ tetrahydrofuran alcohol (THFA), an efficient and cost-effective alcohol ether electrolyte, to mitigate these issues and achieve ultralong-life AZIBs. Theoretical calculations and experimental findings demonstrate that THFA acts as both a hydrogen bonding donor and acceptor, effectively anchoring H2O molecules through dual-site hydrogen bonding. This mechanism restricts the activity of free water molecules. Moreover, the two oxygen (O) atoms in THFA serve as dual solvation sites, enhancing the desolvation kinetics of [Zn(H2O)6]2+ and improving the deposition dynamics of Zn2+ ions. As a result, even trace amounts of THFA significantly suppress adverse reactions and the formation of Zn dendrites, enabling highly reversible Zn metal anodes for ultralong-life AZIBs. Specifically, a Zn-based symmetric cell containing 2 % THFA achieves an ultralong cycle life of 8,800 h at 0.5 mA cm-2/0.5 mAh cm-2, while a Zn//VO2 full cell containing 2 % THFA maintains a remarkable 80.03 % capacity retention rate at 5 A g-1 over 2,000 cycles. This study presents a practical strategy to develop dendrite-free, cost-effective, and highly efficient aqueous energy storage systems by leveraging alcohol ether compounds with dual-site hydrogen bonding capabilities.

Triadic Halobenzene Processing Additive Combined Advantages of Both Solvent and Solid Types for Efficient and Stable Organic Solar Cells.

Solvent additives with a high boiling point (BP) and low vapor pressure (VP) have formed a key handle for improving the performance of organic solar cells (OSCs). However, it is not always clear whether they remain in the active-layer film after deposition, which can negatively affect the reproducibility and stability of OSCs. In this study, an easily removable solvent additive (4-chloro-2-fluoroiodobenzene (CFIB)) with a low BP and high VP is introduced, behaving like volatile solid additives that can be completely removed during the device fabrication process. In-depth studies of CFIB addition into the D18-Cl donor and N3 acceptor validate its dominant non-covalent intermolecular interactions with N3 through effective electrostatic interactions. Such phenomena improve charge dynamics and kinetics by optimizing the morphology, leading to enhanced performance of D18-Cl:N3-based devices with a power conversion efficiency of 18.54%. The CFIB-treated device exhibits exceptional thermal stability (T80 lifetime = 120 h) at 85 °C compared with the CFIB-free device, because of its morphological robustness by evolving no residual CFIB in the film. The CFIB features a combination of advantages of solvent (easy application) and solid (high volatility) additives, demonstrating its great potential use in the commercial mass production of OSCs.

Promoting Preferential Zn (002) Deposition with a Low-Concentration Electrolyte Additive for Highly Reversible Zn-Ion Batteries.

Aqueous zinc-ion batteries have promising potential as energy storage devices due to their low cost and environmental friendliness. However, their development has been hindered by zinc dendrite formation and parasitic side reactions. Herein, we introduce a low-concentration sodium benzoate (NaBZ) electrolyte additive to stabilize the electrode-electrolyte interface and promote deposition on the Zn (002) crystal plane. From experimental characterization and computational analyses, NaBZ was found to adsorb on the Zn surface and inhibit side reactions while guiding homogeneous Zn deposition on the (002) plane. Consequently, Zn|Zn symmetric cells with the NaBZ additive cycled stably for over 1000 h at a current density of 0.5 mA cm-2 and an areal capacity of 0.5 mAh cm-2, while Zn|Cu cells showed excellent reversibility with a Coulombic efficiency of 99.05%. Moreover, Zn|Na0.33V2O5 full cells achieve a high specific capacity of 124 mAh g-1 while cycling for 600 h at 2 A g-1. These findings present a low-cost electrolyte modification strategy for reversible zinc-ion batteries.

Can cadmium-contaminated rice be used to produce food additive sodium erythorbate?

Cadmium (Cd) in rice is a significant concern for its quality and safety. Currently, there is a crucial need to develop cost-effective and efficient ways to remove Cd or re-utilize Cd-contaminated rice. The food additive sodium erythorbate is produced via 2-ketogluconic acid (2KGA) fermentation by Pseudomonas plecoglossicida and lactonization using starch-rich raw materials, such as rice. We aimed to determine whether cadmium-contaminated rice can be used to produce sodium erythorbate. To achieve this aim, the migration of cadmium during the production of sodium erythorbate from Cd-contaminated rice was studied. Five rice varieties with different Cd contents from 0.10 to 0.68 mg/kg were used as raw materials. The results indicated the presence of Cd in rice and CaCO3 did not have a notable impact on the fermentation performance of 2KGA. The acidification of 2KGA fermentation broth, the addition of K4Fe(CN)6·3H2O and ZnSO4, and 2KGA purification using cation exchange effectively removed >98% of the Cd in the fermentation broth, but the 2KGA yield remained high at approximately 94%. The sodium erythorbate synthesized from Cd-contaminated rice was of high quality and free from Cd, meeting the requirements of the Chinese National Standard, GB 1886.28-2016. The study provided a safe and effective strategy for comprehensively utilizing Cd-contaminated rice to produce high value-added food additive.

Eddy Current Sensor Probe Design for Subsurface Defect Detection in Additive Manufacturing.

Pore and crack formation in parts produced by additive manufacturing (AM) processes, such as laser powder bed fusion, is one of the issues associated with AM technology. Surface and subsurface cracks and pores are induced during the printing process, undermining the printed part durability. In-situ detection of defects will enable the real-time or intermittent control of the process, resulting in higher product quality. In this paper, a new eddy current-based probe design is proposed to detect these defects in parts with various defects that mimic pores and cracks in additively manufactured parts. Electromagnetic finite element analyses were carried out to optimize the probe geometry, followed by fabricating a prototype. Artificial defects were seeded in stainless steel plates to assess the feasibility of detecting various flaws with different widths and lengths. The smallest defect detected had a 0.17 mm radius for blind holes and a 0.43 mm notch with a 5 mm length. All the defects were 0.5 mm from the surface, and the probe was placed on the back surface of the defects. The surface roughness of the tested samples was less than 2 µm. The results show promise for detecting defects, indicating a potential application in AM.

Smart Spare Parts (SSP) in the Context of Industry 4.0: A Systematic Review.

The implementation of Industry 4.0 has integrated manufacturing, electronics, and engineering materials, leading to the creation of smart parts (SPs) that provide information on production system conditions. However, SP development faces challenges due to limitations in manufacturing processes and integrating electronic components. This systematic review synthesizes scientific articles on SP fabrication using additive manufacturing (AM), identifying the advantages and disadvantages of AM techniques in SP production and distinguishing between SPs and smart spare parts (SSPs). The methodology involves establishing a reference framework, formulating SP-related questions, and applying inclusion criteria and keywords, initially resulting in 1603 articles. After applying exclusion criteria, 70 articles remained. The results show that while SP development is advancing, widespread application of AM-manufactured SP is recent. SPs can anticipate production system failures, minimize design artifacts, and reduce manufacturing costs. Furthermore, the review highlights that SSPs, a subcategory of SPs, primarily differs by replacing conventional critical parts in the industry, offering enhanced functionality and reliability in industrial applications. The study concludes that continued research and development in this field is essential for further advancements and broader adoption of these technologies.

An evaluation of the effectiveness of four chemical additives on the fermentation characteristics, in vitro digestibility and aerobic stability of total mixed ration silage based on soy sauce residue.

The study aimed to compare the impact of four chemical additives on fermentation characteristics, aerobic stability and in vitro digestibility of total mixed ration (TMR) silage based on soy sauce residue. The TMR (35% soy sauce residue + 45% Napier grass + 20% concentrate) was placed into silos (10 L). The experiment followed the completely random design, treated with different chemical additives: (1) distilled water (control); (2) 0.1% potassium sorbate (SP); (3) 0.1% sodium benzoate (SS); (4) 0.5% calcium propionate (SC); (5) 0.5% sodium diacetate (SD). Total of 100 silos (5 treatments × 4 aerobic exposure days × 5 replicates) were ensiled for 60 days. After exposure to the air, the samples were analyzed for the dynamic change of fermentation parameters at 4, 9 and 15 days, and the data was analyzed as repeated measures. The content of butyric acid and ammonia nitrogen was maintained at a low level. The highest (p < 0.05) lactic acid (LA) content and the lowest (p < 0.05) pH value were measured in SP. At the first 4 days of aerobic exposure, TMR silages treated with four chemical additives were more stable relative to the control, as indicated by the low pH value and yeast counts. Furthermore, the highest (p < 0.05) LA content and the lowest (p < 0.05) pH value indicated that SP performed superior aerobic stability compared with other chemical additives. The SP shows higher (p < 0.05) 72 h cumulative gas production (GP72) and in vitro neutral detergent fiber digestibility (IVNDFD) relative to the control. In conclusion, the SP performed superior in improving fermentation characteristics, aerobic stability and in vitro digestibility of TMR silages based on soy sauce residue.