In response to potential denial environments such as canyons, gullies, islands, and cities where users are located, traditional Telemetry, Tracking, and Command (TT&C) systems can still maintain core requirements such as availability, reliability, and sustainability in the face of complex electromagnetic environments and non-line-of-sight environments that may cause service degradation or even failure. This paper presents a single-station emergency solution that integrates communication and TT&C (IC&T) functions based on radar chaff cloud technology. Firstly, a suitable selection of frequency bands and modulation methods is provided for the emergency IC&T system to ensure compatibility with existing communication and TT&C systems while catering to the future needs of IC&T. Subsequently, theoretical analyses are conducted on the communication link transmission loss, data transmission, code tracking accuracy, and anti-multipath model of the emergency IC&T system based on the chosen frequency band and modulation mode. This paper proposes a dual-way asynchronous precision ranging and time synchronization (DWAPR&TS) system employing dual one-way ranging (DOWR) measurement, a dual-way asynchronous incoherent Doppler velocity measurement (DWAIDVM) system, and a single baseline angle measurement system. Next, we analyze the physical characteristics of the radar chaff and establish a dynamic model of spherical chaff cloud clusters based on free diffusion. Additionally, we provide the optimal strategy for deploying chaff cloud. Finally, the emergency IC&T application based on the radar chaff cloud relay is simulated, and the results show that for severe interference, taking drones as an example, under a measurement baseline of 100 km, the emergency IC&T solution proposed in this paper can achieve an accuracy range of approximately 100 m, a velocity accuracy of 0.1 m/s, and an angle accuracy of 0.1°. In comparison with existing TT&C system solutions, the proposed system possesses unique and potential advantages that the others do not have. It can serve as an emergency IC&T reference solution in denial environments, offering significant value for both civilian and military applications. Full article

Postconcussion syndrome (PCS) is one of the leading complications that may appear in patients after mild head trauma. Every day, thousands of people, regardless of age, gender, and race, are diagnosed in emergency departments due to head injuries. Traumatic Brain Injury (TBI) is a significant public health problem, impacting an estimated 1.5 million people in the United States and up to 69 million people worldwide each year, with 80% of these cases being mild. An analysis of the available research and a systematic review were conducted to search for a solution to predicting the occurrence of postconcussion syndrome. Particular biomarkers that can be examined upon admission to the emergency department after head injury were found as possible predictive factors of PCS development. Setting one unequivocal definition of PCS is still a challenge that causes inconsistent results. Neuron Specific Enolase (NSE), Glial Fibrillary Acidic Protein (GFAP), Ubiquitin C-terminal Hydrolase-L1 (UCH-L1), Serum Protein 100 B (s100B), and tau protein are found to be the best predictors of PCS development. The presence of all mentioned biomarkers is confirmed in severe TBI. All mentioned biomarkers are used as predictors of PCS. A combined examination of NSE, GFAP, UCH-1, S100B, and tau protein should be performed to detect mTBI and predict the development of PCS. Full article

This paper gives an overview over all currently available data sets for the European Long-term Ecosystem Research (eLTER) monitoring site Gesäuse-Johnsbachtal. The site is part of the LTSER platform Eisenwurzen in the Alps of the province of Styria, Austria. It contains both protected (National Park Gesäuse) and non-protected areas (Johnsbachtal). Although the main research focus of the eLTER monitoring site Gesäuse-Johnsbachtal is on inland surface running waters, forests and other wooded land, the eLTER whole system (WAILS) approach was followed in regard to the data selection, systematically screening all available data in regard to its suitability as eLTER’s Standard Observations (SOs). Thus, data from all system strata was included, incorporating Geosphere, Atmosphere, Hydrosphere, Biosphere and Sociosphere. In the WAILS approach these SOs are key data for a whole system approach towards long term ecosystem research. Altogether, 54 data sets have been collected for the eLTER monitoring site Gesäuse-Johnsbachtal and included in the Dynamical Ecological Information Management System – Site and Data Registry (DEIMS-SDR), which is the eLTER data platform. The presented work provides all these data sets through dedicated data repositories for FAIR use. This paper gives an overview on all compiled data sets and their main properties. Additionally, the available data are evaluated in a concluding gap analysis with regard to the needed observation data according to WAILS, followed by an outlook on how to fill these gaps. Full article

Underwater acoustic vector sensors (UAVSs) are increasingly utilized for remote passive sonar detection, but the accuracy of direction-of-arrival (DOA) estimation remains a challenging problem, particularly under low signal-to-noise ratio (SNR) conditions and complex background noise. In this paper, a comprehensive theoretical analysis is conducted on UAVS signal preprocessing subjected to gain-phase uncertainties for average acoustic intensity measurement (AAIM) and complex acoustic intensity measurement (CAIM)-based vector DOA estimation, aiming to explain the theoretical restrictions of intensity-based vector acoustic preprocessing approaches. On this basis, a generalized vector acoustic preprocessing optimization model is established in which the principle can be described as “maximizing the denoising performance under the constraints of an equivalent amplitude-gain response and phase-bias response”. A novel vector acoustic preprocessing method named linear matched stochastic resonance (LMSR) is proposed within the framework of matched stochastic resonance theory, which can naturally guarantee the linear gain-phase restrictions, as well achieving effective denoising performance. Numerical analyses demonstrate the superior vector DOA estimation performance of our proposed LMSR-AAIM and LMSR-CAIM methods in comparison to classical intensity-based AAIM and CAIM methods, especially under low-SNR conditions and non-Gaussian impulsive noise circumstances. Experimental verification conducted in the South China Sea further verifies its the effectiveness for practical application. This work can lay a solid foundation to break through the challenges of underwater remote vector acoustic DOA estimation under low-SNR conditions and complex ocean ambient noise and can provide important guidance for future research work. Full article

A gearbox compound fault intelligent diagnosis method based on the period group sparse model is proposed for the problem that the fault features are coupled with each other and the fault components are superimposed on each other and difficult to be separated in the gearbox compound fault signal. Firstly, a binary sequence is constructed to embed the fault pulse period as a priori knowledge into the group sparse model to decouple and separate the composite fault signal while maintaining the amplitude and sparsity of the extracted features. Secondly, the wavelet packet energy features of the decoupled signals are extracted to improve the data quality while enhancing the characterization ability of the dictionary in the classification model. Finally, the wavelet packet energy features are imported into the sparse dictionary classification model, and the fault diagnosis is completed by outputting the fault categories using the self-driven characteristics of the data. The results show that the fault identification accuracy using the proposed method is 97%. In addition, the experimental validation under different states and working conditions with different rotational speeds allows the superiority and effectiveness of the algorithm in this paper to be tested and has the feasibility of a practical application in engineering. Full article

This study presents a novel microfluidic mixer designed, fabricated, and characterized using additive manufacturing technology — stereolithography (SLA) — and harnessing capillarity principles achieved through microstructure patterning. Micromixers are integral components in optimizing mixing and reaction processes within microfluidic systems. The proposed microdevice employs a tank mixing method capable of blending two fluids. With a channel length of up to 6 mm, the process time is remarkably swift at 3 s, and the compact device measures 35 × 40 × 5 mm. The capillarity-driven working flow rates range from 1 $\mathrm{L}$/$\mathrm{s}$ to 37 $\mathrm{L}$/$\mathrm{s}$, facilitated by channel dimensions varying between 400 $\mathrm{m}$ and 850 $\mathrm{m}$. The total liquid volume within the device channels is 1652 $\mathrm{m}\mathrm{L}$ (6176 $\mathrm{L}$ including the supply tanks). The mix index, representing the homogeneity of the two fluids, is approximately 0.55 along the main channel. The manufacturing process, encompassing printing, isopropyl cleaning, and UV (ultraviolet) curing, is completed within 90 min. This microfluidic mixer showcases efficient mixing capabilities, rapid processing, and a compact design, marking it as a promising advancement in microfluidic technology. The new microfluidic mixer is a major step forward in microfluidic technology, providing a cost-effective and flexible solution for various uses. Its compatibility with SLA additive manufacturing allows for quick prototyping and design improvements, making it valuable for research and practical applications in chemistry, biology, and diagnostics. This study highlights the importance of combining advanced manufacturing techniques with basic fluid dynamics to create effective and easy-to-use microfluidic solutions. Full article

This study presents the predicted hydrodynamic characteristics of different rudder plane configurations on the stern of a full-scale submarine in deep water, which are obtained using the Reynolds-Averaged Navier–Stokes method in Ansys Fluent Solver. First, the results obtained for the X-rudder plane configuration are verified according to previous numerical and experimental results in order to assess the accuracy of the simulation procedure. The X-rudder plane, Y-rudder plane, and Cross-rudder plane configurations in deep water with deflection angles ranging from −21 degrees to +21 degrees are then simulated. Next, the hydrodynamic forces and moments of the Cross-plane, X-plane, and Y-plane rudder configurations obtained through simulation are analyzed using Taylor’s expansion to estimate the hydrodynamic coefficients. The obtained results demonstrate that the X-force of the X-plane rudder configuration is larger than the corresponding forces acting on the Cross-plane rudder and Y-plane rudder configurations. Meanwhile, the Y-force and Z-force of the X-plane rudder configuration are significantly greater than the corresponding forces of the left configurations. The same tendency can be seen in the moment of the X-plane rudder about the y- and z-axes. However, the roll moment induced by the Y-plane and Cross-plane rudder configurations is significantly larger than that under the X-plane rudder configuration. Full article

Yarrowia lipolytica is a robust yeast species that has gained significant attention as a biofactory for various biotechnological applications and undoubtedly can be referred to as a hidden treasure trove due to boasting a diverse array of enzymes with wide-ranging applications in multiple industries, including biofuel production, food processing, biotechnology, and pharmaceuticals. As the biotechnology field continues to expand, Y. lipolytica is poised to play a pivotal role in developing eco-friendly and economically viable bioprocesses. Its versatility and potential for large-scale production make it a promising candidate for sustainably addressing various societal and industrial needs. The current review article aimed to highlight the diverse enzymatic capabilities of Y. lipolytica and provide a detailed analysis of its relevance in biocatalysis, including the use of whole-cell catalysts and isolated enzymes. The review focused on wild-type yeast strains and their species-dependant properties and selected relevant examples of Y. lipolytica used as a host organism for overexpressing some enzymes. Furthermore, the application of Y. lipolytica’s potential in enantiomers resolution, lipids processing, and biodiesel synthesis, as well as the synthesis of polymers or esterification of different substrates for upgrading biologically active compounds, was discussed. Full article

The recent rapid growth in Internet of Things (IoT) technologies is enriching our daily lives but significant information security risks in IoT fields have become apparent. In fact, there have been large-scale botnet attacks that exploit undiscovered vulnerabilities, known as zero-day attacks. Several intrusion detection methods based on network traffic monitoring have been proposed to address this issue. These methods employ federated learning to share learned attack information among multiple IoT networks, aiming to improve collective detection capabilities against attacks including zero-day attacks. Although their ability to detect zero-day attacks with high precision has been confirmed, challenges such as autonomous labeling of attacks from traffic information and attack information sharing between different device types still remain. To resolve the issues, this paper proposes IDAC, a novel intrusion detection method with autonomous attack candidate labeling and federated learning-based attack candidate sharing. The labeling of attack candidates in IDAC is executed using information autonomously extracted from traffic information, and the labeling can also be applied to zero-day attacks. The federated learning-based attack candidate sharing enables candidate aggregation from multiple networks, and it executes attack determination based on the aggregated similar candidates. Performance evaluations demonstrated that IDS with IDAC within networks based on attack candidates is feasible and achieved comparable detection performance against multiple attacks including zero-day attacks compared to the existing methods while suppressing false positives in the extraction of attack candidates. In addition, the sharing of autonomously extracted attack candidates from multiple networks improves both detection performance and the required time for attack detection. Full article

The White Paper on Peak Carbon and Carbon Neutral Action 2022 states that China is to achieve peak carbon by 2030 and carbon neutrality by 2060. Based on the “3060 dual-carbon” goal, how to improve the efficiency of energy performance is an important prerequisite for building a low-carbon, energy-saving, green, and beautiful China. The office performance building studied in this paper is located in the urban area of Turpan, where the climate is characterized by an extremely hot summer environment and a cold winter environment. At the same time, the building is oriented east–west, with the main façade facing west, and the main façade consists of a large area of single-layer glass curtain wall, which is affected by western sunlight. As a result, there are serious problems with the building’s energy consumption, which in turn leads to excessive carbon emissions and high life cycle costs for the building. To address the above problems, this paper analyzes and optimizes the following four dimensions. First, the article creates a Convolutional Neural Network (CNN) prediction model with Total Energy Use in Buildings (TEUI), Global Warming Potential (GWP), and Life Cycle Costs (LCC) as the performance objectives. After optimization, the R² of the three are 0.9908, 0.9869, and 0.9969, respectively, thus solving the problem of low accuracy of traditional prediction models. Next, the NSGA-II algorithm is used to optimize the three performance objectives, which are reduced by 41.94%, 40.61%, and 31.29%, respectively. Then, in the program decision stage, this paper uses two empowered Topsis methods to optimize this building performance problem. Finally, the article analyzes the variables using two sensitivity analysis methods. Through the above research, this paper provides a framework of optimization ideas for office buildings in extremely hot and cold regions while focusing on the four major aspects of machine learning, multi-objective optimization, decision analysis, and sensitivity analysis systematically and completely. For the development of office buildings in the region, whether in the early program design or in the later stages, energy-saving measures to optimize the design have laid the foundation of important guidelines. Full article

Banana bunchy top virus (BBTV) was recently detected in Mozambique and appears to be limited to the provinces of Gaza, Maputo and Zambezia, but it has great potential to spread to other provinces. Despite its importance, nothing is known about the BBTV isolates that occur in Mozambique. In this study, the sequences of the S and R genes of forty isolates chosen as representatives of samples collected previously from eleven farms of the four administrative posts of the district of Chóckwè, province of Gaza, were sequenced and analyzed. The S-DNA nucleotide sequences of the analyzed isolates were highly conserved, with identity ranging from 97% to 100%. The same was observed for the R-DNA sequences, with most identities ranging between 98% and 100% among the isolates from Chókwè and above 90% when compared to the isolates from GenBank. The phylogenetic analysis showed that the Mozambican BBTV isolates belong to the Pacific–Indian Oceans (PIO) group, showing greater proximity to the isolate JQ820453 from Malawi than to the isolates from sub-Saharan countries, which were grouped in a distinct subclade. This is the first study conducted to determine the molecular characteristics of BBTV isolates present in Mozambique. Full article

The catalytic isomerization of glucose to fructose plays a pivotal role in the application of biomass as a feedstock for chemicals. Herein, we propose a facile solid-state-grinding strategy to construct ZrO₂/MgO mixed oxides, which offered an excellent fructose yield of over 34.55% and a high selectivity of 80.52% (80 °C, 2 h). The co-mingling of amphiphilic ZrO₂ with MgO improved the unfavorable moderate/strongly basic site distribution on MgO, which can prohibit the side reactions during the reaction and enhance the fructose selectivity. Based on the catalyst characterizations, MgO was deposited on the ZrO₂ surface by plugging the pores, and the addition of ZrO₂ lessened the quantity of strongly basic sites of MgO. Additionally, the presence of ZrO₂ largely enhanced the catalyst stability in comparison with pure MgO by recycling experiments. Full article

Stress is a natural yet potentially harmful aspect of human life, necessitating effective management, particularly during overwhelming experiences. This paper presents a scoping review of personalized stress detection models using wearable technology. Employing the PRISMA-ScR framework for rigorous methodological structuring, we systematically analyzed literature from key databases including Scopus, IEEE Xplore, and PubMed. Our focus was on biosignals, AI methodologies, datasets, wearable devices, and real-world implementation challenges. The review presents an overview of stress and its biological mechanisms, details the methodology for the literature search, and synthesizes the findings. It shows that biosignals, especially EDA and PPG, are frequently utilized for stress detection and demonstrate potential reliability in multimodal settings. Evidence for a trend towards deep learning models was found, although the limited comparison with traditional methods calls for further research. Concerns arise regarding the representativeness of datasets and practical challenges in deploying wearable technologies, which include issues related to data quality and privacy. Future research should aim to develop comprehensive datasets and explore AI techniques that are not only accurate but also computationally efficient and user-centric, thereby closing the gap between theoretical models and practical applications to improve the effectiveness of stress detection systems in real scenarios. Full article

A novel, in situ, low-cost and facile method has been developed to fabricate flexible NO₂ sensors capable of operating at ambient temperature, addressing the urgent need for monitoring this toxic gas. This technique involves the synthesis of highly porous structures, as well as the specific development of laser-induced graphene (LIG) and its heterostructures with SnO₂, all through laser scribing. The morphology, phases, and compositions of the sensors were analyzed using scanning electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy and Raman spectroscopy. The effects of SnO₂ addition on structural and sensor properties were investigated. Gas-sensing measurements were conducted at room temperature with NO₂ concentrations ranging from 50 to 10 ppm. LIG and LIG/SnO₂ sensors exhibited distinct trends in response to NO₂, and the gas-sensing mechanism was elucidated. Overall, this study demonstrates the feasibility of utilizing LIG and LIG/SnO₂ heterostructures in gas-sensing applications at ambient temperatures, underscoring their broad potential across diverse fields. Full article

Skin and soft tissue reconstruction has long been based on the reconstructive ladder. However, a skin substitute has become popular due to its predictable outcomes, without donor-site morbidity. The biodegradable temporizing matrix (BTM; NovoSorb, PolyNovo Ltd., Port Melbourne, Australia) is a synthetic skin substitute that has recently gained its clinical application. Compared with those of other dermal templates, the clinical efficacy and performance of the BTM are not well established, especially among the Asian population. This study aims to share our experience and strategy of using BTM in various wound conditions. The data of patients who underwent skin and soft tissue reconstruction with BTM at a single institution between January 2022 and December 2023 were reviewed. The patient demographics, wound characteristics, surgical details, secondary procedures, and complications were recorded and analyzed. Postoperative 6-month photographs were collected and independently evaluated by two plastic surgeons and two wound care center nurses using the Manchester Scar Scale (MSS). This study included 37 patients, consisting of 22 males and 15 females with a mean age of 51.8 years (range, 18–86 years old). The wound etiologies included trauma (67.6%), necrotizing soft tissue infection (16.2%), burns (10.8%), toe gangrene (2.7%), and scar excision (2.7%). The average wound area covered by BTM was 50.6 ± 47.6 cm². Among the patients, eight received concomitant flap surgery and BTM implantation, 20 (54.1%) underwent subsequent split-thickness skin grafts (STSG), and 17 had small wounds (mean: 21.6 cm²) healed by secondary intention. Infection was the most common complication, affecting six patients (n = 6 [16.2%]), five of whom were treated conservatively, and only one required debridement. Thirty-three patients (89.2%) had good BTM take, and only four had BTM failure, requiring further reconstruction. At the last follow-up, 35 out of the 37 patients (94.6%) achieved successful wound closure, and the total MSS score was 10.44 ± 2.94, indicating a satisfactory scar condition. The patients who underwent BTM grafting without STSG had better scar scores than those who received STSG (8.71 ± 2.60 vs. 11.18 ± 2.84, p = 0.039). In conclusion, the BTM is effective and feasible in treating various wounds, with relatively low complication rates, and it can thus be considered as an alternative for skin and soft tissue reconstruction. When combined with adipofasical flap reconstruction, it achieves a more comprehensive anatomical restoration. Full article

The application of Neurospora sp., a fungus that commonly thrives on complex agricultural and plant wastes, has proven successful in utilizing citrus peel waste as a source of naringin. A UV-Vis spectrophotometric method proved the biotransformation of naringin, with an absorption maximum (λ_max) observed at 310 nm for the biotransformed product, naringenin (NAR). Further verification of the conversion of naringin was provided through thin layer chromatography (TLC). The Neurospora crassa mediated biotransformation of naringin to NAR was utilized for the rapid (within 5 min) synthesis of silver (Ag) and gold (Au) nanoconjugates using sunlight to accelerate the reaction. The synthesized NAR-nano Ag and NAR-nano Au conjugates exhibited monodispersed spherical and spherical as well as polygonal shaped particles, respectively. Both of the nanoconjugates showed average particle sizes of less than 90 nm from TEM analysis. The NAR-Ag and NAR-Au nanoconjugates displayed potential enhancement of the antimicrobial activities, including antibacterial and nematicidal properties over either standalone NAR or Ag or Au NPs. This study reveals the potential of naringinase-producing Neurospora sp. for transforming naringin into NAR. Additionally, the resulting NAR-Ag and NAR-Au nanoconjugates showed promise as sustainable antibiotics and biochemical nematicides. Full article

Sediment erosion around submarine pipelines is a popular topic, widely investigated in both ocean and submarine-pipeline engineering. In this paper, the incompressible smoothed-particle hydrodynamics (ISPH) method is modified for simulation of local scouring process around the submarine pipeline under the action of unidirectional flow. The erosion model is based on the Clear Water Particle–Turbid Water Particle–Critical Shear Stress (CWP-TWP-CSS) concept, and a sand–water two-phase model is proposed to deal with the sediment-entrained flow. The results of the numerical simulation are compared with the experimental data to verify the accuracy and applicability of the numerical model. The scouring process around the pipeline is investigated under different conditions, i.e., pipeline diameters, gap ratios, and flow velocities. The ISPH model is further used to study the flow characteristics of the scour pits around the submarine pipeline and the influence of the vortices on the maximum scour depth, to provide a theoretical basis for the stability design of submarine pipelines. Full article

The dust originating from the extinct lake of the Aral Sea poses a considerable threat to the surrounding communities and ecosystems. The accurate location of these wind erosion areas is an essential prerequisite for controlling sand and dust activity. However, few relevant indicators reported in this current study can accurately describe and measure wind erosion intensity. A novel wind erosion intensity (WEI) of a pixel resolution unit was defined in this paper based on deformation due to the wind erosion in this pixel resolution unit. We also derived the relationship between WEI and soil InSAR temporal decorrelation (ITD). ITD is usually caused by the surface change over time, which is very suitable for describing wind erosion. However, within a pixel resolution unit, the ITD signal usually includes soil and vegetation contributions, and extant studies concerning this issue are considerably limited. Therefore, we proposed an ITD decomposition model (ITDDM) to decompose the ITD signal of a pixel resolution unit. The least-square method (LSM) based on singular value decomposition (SVD) is used to estimate the ITD of soil (SITD) within a pixel resolution unit. We verified the results qualitatively by the landscape photos, which can reflect the actual conditions of the soil. At last, the WEI of the Aral Sea from 23 June 2020, to 5 July 2020 was mapped. The results confirmed that (1) based on the ITDDM model, the SITD can be accurately estimated by the LSM; (2) the Aral Sea is experiencing severe wind erosion; and (3) the middle, northeast, and southeast bare areas of the South Aral Sea are where salt dust storms may occur. Full article

Background: Peritoneal carcinomatosis is one of deadliest metastatic patterns of gastric cancer, being associated with a median overall survival (OS) of 4 months. Up to now, palliative systemic chemotherapy (pSC) has been the only recommended treatment. The aim of this study is to evaluate a potential survival benefit after CRS + HIPEC compared to pSC. Methods: A systematic review was conducted according to the PRISMA guidelines in March 2024. Manuscripts reporting patients with peritoneal carcinomatosis from gastric cancer treated with CRS + HIPEC were included. A meta-analysis was performed, comparing the survival results between the CRS + HIPEC and pSC groups, and the primary outcome was the comparison in terms of OS. We performed random-effects meta-analysis of odds ratios (ORs). We assessed heterogeneity using the Q2 statistic. Results: Out of the 24 papers included, 1369 patients underwent CRS + HIPEC, with a median OS range of 9.8–28.2 months; and 103 patients underwent pSC, with a median OS range of 4.9–8 months. CRS + HIPEC was associated with significantly increased survival compared to palliative systemic chemotherapy (−1.8954 (95% CI: −2.5761 to −1.2146; p < 0.001). Conclusions: CRS + HIPEC could provide survival advantages in gastric cancer peritoneal metastasis compared to pSC. Full article

E-liquids contain combinations of chemicals, with many enhancing the sensory attractiveness of the product. Studies are needed to understand and characterize e-liquid ingredients, particularly flavorings, to inform future research and regulations of these products. We identified common flavor ingredients in a convenience sample of commercial e-liquids using gas chromatography–mass spectrometry. E-liquid flavors were categorized by flavor descriptors provided on the product packaging. A Flavor Ingredient Wheel was developed to link e-liquid flavor ingredients with flavor categories. An analysis of 109 samples identified 48 flavor ingredients. Consistency between the labeled flavor and ingredients used to produce such flavor was found. Our novel Flavor Ingredient Wheel organizes e-liquids by flavor and ingredients, enabling efficient analysis of the link between ingredients and their flavor profiles and allowing for quick assessment of an e-liquid ingredient’s flavor profile. Investigating ingredient profiles and identifying and classifying commonly used chemicals in e-liquids may assist with future studies and improve the ability to regulate these products. Full article

Chromium slag is a solid waste of chromium salt production, which contains highly toxic Cr(VI) and significant amounts of valuable metals, such as Fe and Cr. Recycling chromium slag as a raw sintering material in sintering–ironmaking processes can simultaneously reduce toxic Cr(VI) and recover valuable metals. A micro-sintering experiment, compressive strength test, microhardness test, and first-principles calculation are performed to investigate the influence of Cr₂O₃ on the sintering microstructure and mechanical properties of the silico-ferrite of calcium and aluminum (SFCA) in order to understand the basis of the sintering process with chromium slag addition. The results show that the microstructure of SFCA changes from blocky to interwoven, with further increasing Cr₂O₃ content from 0 wt% to 3 wt%, and transforms to blocky with Cr₂O₃ content increasing to 5 wt%. Cr₂O₃ reacts with Fe₂O₃ to form (Fe_1−xCr_x)₂O₃ (0 ≤ x ≤ 1), which participates in forming SFCA. With the increase in Cr doping concentrations, the hardness of SFCA first decreases and then increases, and the toughness increases. When Cr₂O₃ content increases from 0 wt% to 3 wt%, the SFCA microhardness decreases and the compressive strength of the sintered sample increases. Further increasing Cr₂O₃ contents to 5 wt%, the SFCA microhardness increases, and the compressive strength of sintered sample decreases. Full article

In recent years, tubular nanostructures have been related to immense advances in various fields of science and technology. Considerable research efforts have been centred on the theoretical prediction and manufacturing of non-carbon nanotubes (NTs), which meet modern requirements for the development of novel devices and systems. In this context, diatomic inorganic nanotubes formed by atoms of elements from the 13th group of the periodic table (B, Al, Ga, In, Tl) and nitrogen (N) have received much research attention. In this study, the elastic properties of single-walled boron nitride, aluminium nitride, gallium nitride, indium nitride, and thallium nitride nanotubes were assessed numerically using the nanoscale continuum modelling approach (also called molecular structural mechanics). The elastic properties (rigidities, surface Young’s and shear moduli, and Poisson’s ratio) of nitride nanotubes are discussed with respect to the bond length of the corresponding diatomic hexagonal lattice. The results obtained contribute to a better understanding of the mechanical response of nitride compound-based nanotubes, covering a broad range, from the well-studied boron nitride NTs to the hypothetical thallium nitride NTs. Full article