What happens when recognized and diverse conditioning factors of linguistic variation are omitted from analysis and/or are not analyzed under a single analytical procedure? This paper explores the consequences of such a choice on data interpretation and, consequently, (socio)linguistic theorization. Utilizing Twitter-style English in the Philippines (EngPH) as a case study, I employ the Twitter Corpus of Philippine Englishes (TCOPE) primarily to investigate and elucidate variations in three morphosyntactic variables that have been previously examined using a piecemeal approach. I propose a holistic quantitative approach that incorporates documented linguistic, social, diachronic, and stylistic factors in a unified analysis. The paper illustrates the impacts of adopting this holistic approach through two statistical procedures: Bayesian regression modeling and Boruta feature selection with random forest modeling. In contrast to earlier research findings, my overall results reveal biases in non-unified quantitative analyses, where the confidence in the effects of certain factors diminishes in light of others during analysis. The adoption of a unified analysis or modeling also enhances the resolution at which variations have been examined in EngPH. For instance, it highlights that presumed ‘universals’, such as the hierarchy of linguistic > stylistic > diachronic > social factors in explaining variation in some domains, is contingent on the specific variable under examination. Overall, I argue that unified analyses reduce data distortion and introduce more nuanced interpretations and insights that are critical for establishing a well-grounded empirical theory of EngPH variation and language variation as a whole. Full article

During the COVID-19 pandemic, a considerable proportion of patients developed a severe condition that included respiratory failure, shock, or multiple organ dysfunction. Acute Kidney Injury (AKI) has been recognized as a possible cause of severe COVID-19 development. Given this, this study investigates the occurrence and consequences of AKI in Mexican patients to contribute to better knowledge and management of this problem. Methods: Using a retrospective observational cohort methodology, we investigated 313 cases from a cohort of 1019 patients diagnosed with COVID-19 at the IMSS Zacatecas General Hospital of Zone No. 1 in 2020. The prevalence of AKI was determined using the AKIN criteria based on serum creatinine levels and a detailed review of demographic characteristics, medical history, comorbidities, and clinical development. Results: The data showed a 25.30% prevalence of AKI among patients infected with severe COVID-19. Remarkably, these patients with AKI exhibited an advanced age (>65 years), arterial hypertension, a higher number of white blood cells during admission and the hospital stay, and elevated levels of C-reactive protein, serum creatinine, and blood urea nitrogen (BUN). Clinically, patients with AKI had signs of prostration, pneumonia, and the requirement for ventilatory assistance when compared to those without AKI. Finally, those diagnosed with AKI and COVID-19 had a 74% death rate. Relative risk analyses indicated that age (>65 years), arterial hypertension, high creatinine levels, endotracheal intubation, and pneumonia are associated with the development of AKI. On the other hand, among the protective factors against AKI, high hemoglobin levels and the consumption of statins during COVID-19 were found. Conclusions: The findings of this study underscore the significance of promptly identifying and effectively managing AKI to potentially alleviate the negative consequences of this complication within the Mexican population during COVID-19. Full article

Aero-engines can be exposed to One Engine Inoperative (OEI) conditions during service, and the resulting overheating effect may significantly impact their structural integrity and flight safety. This paper focuses on the influence of overheating on the microstructural evolution and tensile properties of the GH4720Li alloy, a nickel-based polycrystalline superalloy commonly used in turbine disks. Based on the typical OEI operating conditions of a real aero-engine, a series of non-isothermal high-temperature tensile tests involving an OEI stage of 800 °C were conducted. The effects of OEI-induced overheating on the microstructure and tensile properties of the GH4720Li alloy were investigated. The results showed that, after OEI treatment, the primary γ′ phase in this alloy was partially dissolved. The GH4720Li superalloy also exhibited numerous microcracks at the grain boundaries, resulting in complex effects on its tensile properties. The alloy’s yield strength and ultimate tensile strength were slightly decreased, whereas its ductility decreased considerably. The OEI-induced embrittlement phenomenon was mainly caused by the non-uniform distribution of the tertiary γ′ phase within grains. The formation of microcracks nucleated at the interfaces between the primary γ′ precipitates and γ matrix phase was another key factor. Full article

The present study emphasizes the importance of documenting ethnomedicinal plants and herbal practices of the local rural communities of Tehsil Hajira (Pakistan). The aim was to document, explore and quantify the traditional ethnomedicinal knowledge. Ethnobotanical data were collected using semi-structured questionnaires and analyzed using various quantitative indices. The results showed that 144 medicinal plant species from 70 families and 128 genera play an important role in herbal preparations. The most common type of preparation was powder (19.0%), followed by paste (16.7%), aqueous extract (15.7%), decoction (14.7%) and juice (11.0%). Fragaria nubicola (0.94) and Viola canescens (0.93) had the highest relative frequency of mention (RFC), while Berberis lycium (1.22) and Fragaria nubicola (1.18) had the highest use value (UV). Geranium wallichianum (85.5), Ligustrum lucidum (83) and Indigofera heterantha (71.5) were the most important species in the study area with the highest relative importance (RI) value. The diseases treated were categorized into 17 classes, with diseases of the digestive system and liver having the highest Informant Consensus Factor (ICF) value, followed by diseases of the oropharynx and musculoskeletal system. Important plants mentioned for the treatment of various diseases of the gastrointestinal tract are Zanthoxylum alatum, Berberis lycium, Mentha longifolia, Punica granatum, Rubus ellipticus and Viola canescens. New applications of rarely documented plants from this area are: Oxalis corniculata paste of the whole plant to treat vitiligo, Carthamus tinctorius flowers to treat chicken pox, Dioscorea deltoidea tuber powder to treat productive cough, Inula cappa root decoction to treat miscarriage, Habenaria digitata tuber juice for the treatment of fever, Viola canescens leaves and flowers for the treatment of sore throat and Achillea millefolium root and leaf juice for the treatment of pneumonia. These plants may contain interesting biochemical compounds and should be subjected to further pharmacological studies to develop new drugs. Traditional medicinal knowledge in the area under study is mainly limited to the elderly, traditional healers and midwives. Therefore, resource conservation strategies and future pharmacological studies are strongly recommended. Full article

Much research has been conducted to determine how hair regeneration is regulated, as this could provide therapeutic, cosmetic, and even psychological interventions for hair loss. The current study focused on the hair growth effect and effective utilization of fatty oil obtained from Bryde’s whales through a high-throughput DNA microarray approach in conjunction with immunohistochemical observations. The research also examined the mechanisms and factors involved in hair growth. In an experiment using female C57BL/6J mice, the vehicle control group (VC: propylene glycol: ethanol: water), the positive control group (MXD: 3% minoxidil), and the experimental group (WO: 20% whale oil) were topically applied to the dorsal skin of the mouse. The results showed that 3% MXD and 20% WO were more effective than VC in promoting hair growth, especially 20% WO. Furthermore, in hematoxylin and eosin-stained dorsal skin tissue, an increase in the number of hair follicles and subcutaneous tissue thickness was observed with 20% WO. Whole-genome transcriptome analysis also confirmed increases for 20% WO in filaggrin (Flg), a gene related to skin barrier function; fibroblast growth factor 21 (Fgf21), which is involved in hair follicle development; and cysteine-rich secretory protein 1 (Crisp1), a candidate gene for alopecia areata. Furthermore, the results of KEGG pathway analysis indicated that 20% WO may have lower stress and inflammatory responses than 3% MXD. Therefore, WO is expected to be a safe hair growth agent. Full article

Microfluidic technology provides a solution to the challenge of continuous CaCO₃ particle synthesis. In this study, we utilized a 3D-printed microfluidic chip to synthesize CaCO₃ micro- and nanoparticles in vaterite form. Our primary focus was on investigating a continuous one-phase synthesis method tailored for the crystallization of these particles. By employing a combination of confocal and scanning electron microscopy, along with Raman spectroscopy, we were able to thoroughly evaluate the synthesis efficiency. This evaluation included aspects such as particle size distribution, morphology, and polymorph composition. The results unveiled the existence of two distinct synthesis regimes within the 3D-printed microfluidic chips, which featured a channel cross-section of 2 mm². In the first regime, which was characterized by chaotic advection, particles with an average diameter of around 2 $\mathsf{\mu }$m were produced, thereby displaying a broad size distribution. Conversely, the second regime, marked by diffusion mixing, led to the synthesis of submicron particles (approximately 800–900 nm in diameter) and even nanosized particles (70–80 nm). This research significantly contributes valuable insights to both the understanding and optimization of microfluidic synthesis processes, particularly in achieving the controlled production of submicron and nanoscale particles. Full article

The search for unexplored plant resources that would provide a good basis for the development of novel probiotic functional foods is rapidly increasing. In this context, the strawberry tree fruit (Arbutus unedo L.) is particularly interesting, as it is rich in numerous antioxidant bioactive compounds that have been shown to be beneficial to health, but have not yet found industrial applications. In this work, the probiotic characterization of lactic acid bacteria strain Lactiplantibacillus plantarum DB2, isolated from strawberries (Fragaria ananassa × Duch.), was performed. The tested strain proved to be safe to use, displaying no antibiotic resistance or hemolytic activity. Due to its proven probiotic potential during simulated gastrointestinal transit, its antimicrobial activity, and its coaggregation with pathogens, it was selected for fermentation of an aqueous Arbutus unedo L. extract, which was subsequently microencapsulated and freeze-dried to extend its shelf life and preserve its functional properties. The antioxidant activity of the ferment obtained was maintained (80%), while after microencapsulation and freeze-drying, about 50% and 20% of the antioxidant activity was retained, respectively. In conclusion, this study demonstrates for the first time the application of probiotics isolated from strawberries in the fermentation of strawberry tree extract and monitors the antioxidant activity during post-fermentation formulation, paving the way for a potential industrial application of this underutilized plant. Full article

The study explores how different dimensions of perfectionism influence psychological well-being (PWB) in emerging adults. Literature has deepened the relationships between maladaptive perfectionism (e.g., excessive self-criticism, perceived discrepancy from the standards) and low PWB. Less is known about whether and how adaptive perfectionism (e.g., pursuing personal standards) relates to PWB. Secondly, the study has investigated whether self-compassion (i.e., self-benevolence, seeing personal imperfections as a common condition) may mediate the relationships between adaptive/maladaptive perfectionism and PWB. Participants (N = 217, 18–35 y. o.) completed self-report questionnaires measuring: adaptive/maladaptive perfectionism (Almost Perfect Scale-Revised, APS-R: high standards and order/discrepancy, respectively), PWB, and self-compassion (SCS). Adaptive perfectionism was associated with PWB, particularly a higher presence of purpose in life, environmental mastery, self-acceptance, and personal growth. Conversely, discrepancy resulted in the most robust predictor of low PWB (β = −0.68), followed by high standards with a positive direction (β = 0.23; Rc² = 0.514, p < 0.001). A strong negative association emerged between discrepancy and SCS (r = −0.67, p < 0.001). A mediation analysis shows that self-compassion has an indirect effect, reducing the strength of the relationship between discrepancy and low PWB. Results suggest focusing on self-compassion as a buffer factor that reduces the negative impact of maladaptive perfectionism on psychological well-being. Implications for education and health psychology are discussed. Full article

This study aimed to compare the impact of CAD/CAM closed systems and open systems on the marginal gap of monolithic zirconia-reinforced lithium silicate (ZLS) ceramic crowns, as both systems are used in everyday dentistry, both chair-side and laboratory. For the closed system, 20 plastic teeth were scanned by a Primescan intra-oral scanner (IOS), and for the open system, the same number of plastic teeth were scanned by Trios 4 IOS. For the closed system, CEREC software was used, and for the open system, EXOCAD software was used. All 40 ZLS crowns were grinded by the same four-axis machine and cemented with Temp-bond, followed by self-adhesive resin cement. For each type of cement, an evaluation of the marginal gap was conducted by scanning electron microscopy (SEM). Before comparisons between the groups, a Kolmogorov–Smirnov test was performed on the study variables showing a normal distribution (p > 0.05). Independent T tests (α = 0.05) and paired-sample T tests (α = 0.05) were used. The independent T test found no significant mean marginal gap differences in the zirconia-reinforced lithium silicate crowns bonded with Temp-bond and scanned by Primescan (28.09 μm ± 3.06) compared to Trios 4 (28.94 μm ± 3.30) (p = 0.401), and there was no significant mean marginal gap differences in zirconia-reinforced lithium silicate crowns bonded with self-adhesive resin cement (Gcem ONE) and scanned by Primescan (46.70 μm ± 3.80) compared to Trios 4 (47.79 μm ± 2.59) (p = 0.295). Paired-sample T tests showed significantly higher mean marginal gaps with Gcem ONE compared to Temp-bond for the total mean marginal gap when scanning with Primescan (p = 0.0005) or Trios 4 (p = 0.0005). In everyday dentistry, both closed systems (Primescan with Cerec) and open systems (Trios 4 with Exocad) can be used to achieve an acceptable (<120 µm) marginal gap for ZLS CELTRA^® DUO single crowns. There is a significant difference between cementation with Temp-bond and Gcem ONE self-adhesive resin cement (p < 0.05). Full article

Energy management is important for both consumers and utility providers. Utility providers are concerned with identifying and reducing energy wastage and thefts. Consumers are interested in reducing their energy consumption and bills. In Pakistan, residential and industrial estates account for nearly 31,000 MW of the maximum total demand, while the transmission and distribution capacity has stalled at about 22,000 MW. This 9000 MW gap in demand and supply, as reported in 2022, has led to frequent load shedding. Although the country now has an excess generation capacity of about 45,000 MW, the aging transmission and distribution network cannot deliver the requisite power at all times. Hence, electricity-related problems are likely to continue for the next few years in the country and the same is true for other low- and middle-income countries (LMICs). Several energy monitoring systems (EnMS) have been proposed, but they face limitations in terms of cost, ease of application, lack of universal installation capability, customization, and data security. The research below focused on the development of an economical, secure, and customizable real-time EnMS. The proposed EnMS comprises low-cost hardware for gathering energy data with universal compatibility, a secured communication module for real-time data transmission, and a dashboard application for visualization of real-time energy consumption in a user-preferred manner, making the information easily accessible and actionable. The experimental results and analysis revealed that approximately 40% cost savings in EnMS development could be achieved compared to other commercially available EnMSs. The performance of the EnMS hardware was evaluated and validated through rigorous on-site experiments. The front-end of the EnMS was assessed through surveys and was found to be interactive and user-friendly for the target clients. The developed EnMS architecture was found to be an economical end-product and an appropriate approach for small and medium clients such as residential, institutional, commercial, and industrial consumers, all on one platform. Full article

This study investigates the utilisation of organometallic network frameworks composed of fourth-period transition metals and tetrahydroxyquinone (THQ) in electrocatalytic CO₂ reduction. Density functional theory (DFT) calculations were employed in analysing binding energies, as well as the stabilities of metal atoms within the THQ frameworks, for transition metal TM-THQs ranging from Y to Cd. The findings demonstrate how metal atoms could be effectively dispersed and held within the THQ frameworks due to sufficiently high binding energies. Most TM-THQ frameworks exhibited favourable selectivity towards CO₂ reduction, except for Tc and Ru, which experienced competition from hydrogen evolution reaction (HER) and required solution environments with pH values greater than 5.716 and 8.819, respectively, to exhibit CO₂RR selectivity. Notably, the primary product of Y, Ag, and Cd was HCOOH; Mo produced HCHO; Pd yielded CO; and Zr, Nb, Tc, Ru, and Rh predominantly generated CH₄. Among the studied frameworks, Zr-THQ displayed values of 1.212 V and 1.043 V, corresponding to the highest limiting potential and overpotential, respectively, while other metal–organic frameworks displayed relatively low ranges of overpotentials from 0.179 V to 0.949 V. Consequently, it is predicted that the TM-THQ framework constructed using a fourth-period transition metal and tetrahydroxyquinone exhibits robust electrocatalytic reduction of CO₂ catalytic activity. Full article

This paper investigates the problem of exponential $H_{\infty }$ output control for switching fuzzy systems, considering both impulse and non-impulse scenarios. Unlike previous research, where the average dwell time (ADT: ${\tau }_a$) and the upper bound of inter-event intervals (IEIs: T) satisfy the condition ${\tau }_a\ge \frac{ln\mu +(\alpha +\beta )T}{\alpha }=\frac{ln\mu +\beta T}{\alpha }+T$, implying that frequent switching is difficult to achieve, this paper demonstrates that by adopting the mode-dependent event-triggered mechanism (ETM) and a switching law, frequent switching is indeed achieved. Moreover, the question of deriving the normal $L_2$ norm constraint is solved through the ADT method, although only a weighted $L_2$ norm constraint was obtained previously. Additionally, by constructing a controller-mode-dependent Lyapunov function and adopting logarithmic quantizers, the sufficient criteria of exponential $H_{\infty }$ output control problem are presented. The validity of established results is demonstrated by a given numerical simulation. Full article

Industry 5.0 is an emerging value-driven manufacturing model in which human–machine interface-oriented intelligent manufacturing is one of the core concepts. Based on the theoretical human–cyber–physical system (HCPS), a reference framework for human–machine collaborative additive manufacturing for Industry 5.0 is proposed. This framework establishes a three-level product–economy–ecology model and explains the basic concept of human–machine collaborative additive manufacturing by considering the intrinsic characteristics and functional evolution of additive manufacturing technology. Key enabling technologies for product development process design are discussed, including the Internet of Things (IoT), artificial intelligence (AI), digital twin (DT) technology, extended reality, and intelligent materials. Additionally, the typical applications of human–machine collaborative additive manufacturing in the product, economic, and ecological layers are discussed, including personalized product design, interactive manufacturing, human–machine interaction (HMI) technology for the process chain, collaborative design, distributed manufacturing, and energy conservation and emission reductions. By developing the theory of the HCPS, for the first time its core concepts, key technologies, and typical scenarios are systematically elaborated to promote the transformation of additive manufacturing towards the Industry 5.0 paradigm of human–machine collaboration and to better meet the personalized needs of users. Full article

Ships are important targets for modern naval warfare detection and reconnaissance. The accurate detection of ships contributes to the maintenance of maritime rights and interests and the realisation of naval strategy. Synthetic Aperture Radar (SAR) image detection tasks play a vital role in ship detection, which has consistently been a research hotspot in the field of SAR processing. Although significant progress has been achieved in SAR ship detection techniques using deep learning methods, some challenges still persist. Natural images and SAR images significantly diverge in imaging mechanisms and scattering characteristics. In complex background environments, ships exhibit multiscale variations and dense arrangements, and numerous small-sized ships may be present, culminating in false or missed detections. To address these issues, we propose a novel SAR ship detection network, namely, a Wavelet-Driven Feature-Enhanced Attention–You Only Look Once X (WDFA-YOLOX) network. Firstly, we propose a Wavelet Cascade Residual (WCR) module based on the traditional image processing technique wavelet transform, which is embedded within an improved Spatial Pyramid Pooling (SPP) module, culminating in the formation of the effective wavelet transform-based SPP module (WSPP). The WSPP compensates for the loss of fine-grained feature information during pooling, enhancing the capability of the network to detect ships amidst complex background interference. Secondly, a Global and Local Feature Attention Enhancement (GLFAE) module is proposed, leveraging a parallel structure that combines convolutional modules with transformer modules to reduce the effect of irrelevant information and effectively strengthens valid features associated with small-sized ships, resulting in a reduction in false negatives in small-sized ship detection. Finally, a novel loss function, the Chebyshev distance-generalised IoU loss function, is proposed to significantly enhance both the precision of the detection box and the network convergence speed. To support our approach, we performed thorough experiments on the SSDD and HRSID, achieving an average precision (AP) of 99.11% and 96.20%, respectively, in ship detection. The experimental results demonstrate that WDFA-YOLOX has significant advantages in terms of detection accuracy, generalisation capability, and detection speed and can effectively realise more accurate detection in SAR images, consistently exhibiting superior performance and application value in SAR ship detection. Full article

Information on the state of the environment is important to achieve the objectives of the European Green Deal, including the EU’s Biodiversity Strategy for 2030. The existing regulatory provisions for genetically modified organisms (GMOs) foresee an obligatory post-market environmental monitoring (PMEM) of potential adverse effects upon release into the environment. So far, GMO monitoring activities have focused on genetically modified crops. With the advent of new genomic techniques (NGT), novel GMO applications are being developed and may be released into a range of different, non-agricultural environments with potential implications for ecosystems and biodiversity. This challenges the current monitoring concepts and requires adaptation of existing monitoring programs to meet monitoring requirements. While the incorporation of existing biodiversity monitoring programs into GMO monitoring at the national level is important, additional monitoring activities will also be required. Using case examples, we highlight that monitoring requirements for novel GMO applications differ from those of GM crop plants previously authorized for commercial use in the European Union. Full article

Piecewise fractional-order differential operators have received more attention in recent years because they can be used to describe various evolutionary dynamical problems to investigate crossover behaviors. In this manuscript, we use the aforementioned operators to investigate a mathematical model of COVID-19. By utilizing fractional calculus, our approach aims to capture the crossover dynamics of disease spread, considering heterogeneity and transitions between epidemic phases. This research seeks to develop a framework using specialized mathematical techniques, such as the Caputo fractional derivative, with the potential to investigate the crossover dynamical behaviors of the considered epidemic model. The anticipated contribution lies in bridging fractional calculus and epidemiology, offering insights for both theoretical advancements and practical public health interventions. In order to improve our understanding of epidemic dynamics and support, we used MATLAB to simulate numerical results for a visual representation of our findings. For this interpretation, we used various fractional-order values. In addition, we also compare our simulated results with some reported results for infected and death classes to demonstrate the efficiency of our numerical method. Full article

Forest fires often pose serious hazards, and the timely monitoring and extinguishing of residual forest fires using unmanned aerial vehicles (UAVs) can prevent re-ignition and mitigate the damage caused. Due to the urgency of forest fires, drones need to respond quickly during firefighting operations, while traditional drone formation deployment requires a significant amount of time. This paper proposes a pure azimuth passive positioning strategy for circular UAV formations and utilizes the Deep Q-Network (DQN) algorithm to effectively adjust the formation within a short timeframe. Initially, a passive positioning model for UAVs based on the relationships between the sides and angles of a triangle is established, with the closest point to the ideal position being selected as the position for the UAV to be located. Subsequently, a multi-target optimization model is developed, considering 10 UAVs as an example, with the objective of minimizing the number of adjustments while minimizing the deviation between the ideal and adjusted UAV positions. The DQN algorithm is employed to solve and design experiments for validation, demonstrating that the deviation between the UAV positions and the ideal positions, as well as the number of adjustments, are within acceptable ranges. In comparison to genetic algorithms, it saves approximately 120 s. Full article

Vulvovaginal candidiasis (VVC) is a common condition that can lead to significant discomfort, affecting approximately 70–75% of women at least once in their lives. During pregnancy, the prevalence of VVC is estimated to be around 20%, peaking at about 30% in the third trimester, with a number of specific risk factors predisposing to yeast infection being identified and needing elucidation. This review aims to provide updated knowledge on candidiasis during pregnancy, addressing risk factors and maternal and neonatal outcomes, as well as discussing optimal therapeutic strategies to safeguard mothers and newborns. The bibliographic search involved two biomedical databases, PubMed and Embase, without imposing time limits. Among all Candida spp., Candida albicans remains the most frequent causative species. The hyperestrogenic environment of the vaginal mucosa and reduced immune defenses, physiological effects of pregnancy, create conditions favorable for Candida spp. vaginal colonization and hence VVC. Recent evidence shows an association between VVC and adverse obstetric outcomes, including premature membrane rupture (PROM), chorioamnionitis, preterm birth, and puerperal infections. Prompt and effective management of this condition is therefore crucial to prevent adverse obstetric outcomes, maternal–fetal transmission, and neonatal disease. Additional studies are required to confirm the benefits of systemic treatment for maternal candida infection or colonization in preventing premature birth or neonatal systemic candidiasis. Full article

This article presents an assessment of sustainable mobility initiatives developed in Montevideo, Uruguay, in the period from 2020 to 2023. The significance of sustainable mobility is underscored due to its far-reaching implications for the environment, energy efficiency, and the overall quality of life of citizens. This study focuses on crucial aspects of four initiatives deployed in Montevideo in 2020–2023: electric mobility solutions using scooters, the development of infrastructure and services for urban cycling, the development of electric public transportation, and private electric transportation. Important results are obtained and commented on for each of the studied initiatives, regarding efficiency, environmental impact, accessibility, the quality of the service, and other relevant indicators. Based on the analysis, valuable knowledge is acquired to guide the future development of efficient and sustainable transportation modes in Montevideo, Uruguay. Full article

Is additive manufacturing (AM) a sustainable process? Can the process be optimised to produce sustainable AM parts and production techniques? Additive manufacturing offers the production of parts made of different types of materials in addition to the complex geometry that is difficult or impossible to produce by using the traditional subtractive methods. This study is focused on the optimisation of laser powder bed fusion (L-PBF), one of the most common technologies used in additive manufacturing and 3D printing. This research was carried out by modulating the build layer thickness of the deposited metal powder and the input volumetric energy density. The aim of the proposed strategy is to save the build time by maximizing the applied layer thickness of nitinol powder while retrieving the different AM part properties. The saving in the process time has a direct effect on the total cost of the produced part as a result of several components like electric energy, inert gas consumption, and labour. Nickel-rich nitinol (52.39 Ni at.%) was selected for investigation in this study due to its extremely high superplastic and shape memory properties in addition to the wide application in various industries like aerospace, biomedical, and automotive. The results obtained show that significant energy and material consumption can be found by producing near full dens AM parts with limited or no alteration in chemical and mechanical properties. Full article

Deploying an airbag when a vehicle occupant is too close to it can cause injury. An adaptive Airbag Control Unit (ACU) would improve the effectiveness of the safety system, provided it is aware of the actual position of the occupants once the crash is going to occur. Occupants can be monitored with vision-based and radar-based sensing in the vehicle, but the research question is whether other reliable devices exist. In this research, a real seat is equipped with four sensors in the supports from the floor, as well as an Inertial Measurement Unit (IMU) and a microcontroller. The device is capable of identifying correct position or different Out of Position (OP) conditions and inform an adaptive ACU. The paper presents the seat layout in detail and its testing in extensive driving experiments with multiple participants. Depending on the position of the driver, the identification is correct 45–100% of the time. Monitoring the occupant position by a sensorized seat is feasible and can improve the reliability of the onboard safety system when integrated with other occupant monitoring devices. Full article

This study examined the impact of tea polyphenols (TPs) on the intestinal flora of loaches (Paramisgurnus dabryanus) under chronic ammonia nitrogen stress using high-throughput sequencing. Two groups of 600 loaches were studied over one month, and they were separated into a control group and tea polyphenol group. Alpha and beta diversity analyses showed diverse bacterial communities, with significant differences in the abundance and uniformity observed initially but not between sampling time points. Cluster analyses revealed distinct differences in microbial communities between groups. A predictive function analysis indicated enrichment in pathways related to amino acid and nucleotide biosynthesis. These findings offer initial insights into how tea polyphenols may affect intestinal microbial communities in loaches under ammonia nitrogen stress. Full article