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The objective of this study is to comprehend how changes in laser speed affect the behaviour and features of neck formation in SS316L during powder bed fusion. This study examines the impact of various laser speeds on the neck formation in the commonly used SS316L. Uniweld Laser 3000 was used for laser joining. A constant laser power of 15 W and laser scan speed of 25–150 mm/s were implemented, and powder joining within a single track was observed. Results show that neck size decreases with increasing laser scanning speed and no particle joining occurs at 150 mm/s scan speed, as it is considered too fast for sufficient heat absorption and melting. As laser speed decreases to 125 mm/s, neck starts to form because the particles absorb more heat, which facilitates melting and bonding. Surface diffusion occurs early at this stage because it requires only a small amount of energy to break atomic bonds on the surfaces of particles compared to those in the internal part. This process involves atoms moving along the surfaces of the particles, facilitating the initial stages of sintering by reducing surface energy and causing neck formation between particles. At 125 mm/s, the particle shape remains spherical, and the average neck size is 49 μm. At 100 μm, the powder average neck size is 62 μm. Moreover, the powder completely merges at 50 mm/s and 25 mm/s. The neck formed between particles considerably improves the product's mechanical strength by strengthening bonds between particles. Material density increases with neck quality, and stable neck growth can reduce the porosity of the final parts. Ensuring thermal stability in the laser powder bed fusion allows consistent heat to particles, ensuring even temperature in materials and ultimately facilitating stable neck growth. Thermal stability enables atoms in particles to migrate efficiently and prevents defects, such as bubbling, which increases porosity in printed parts. Therefore, a slow scanning speed allows particles to absorb more heat for melting, increasing the neck size of particles. This knowledge is useful for optimizing laser processing parameters in various industrial applications.

The research has focused on evaluating the mechanical strength of long unidirectional kenaf-PLA composite and the degradation effect after accelerated weathering exposure. The composite was fabricated using a green traditional method of hot-pressing method with different compositions of non-chemically treated kenaf fiber to PLA with the ratio of 30:70, 40:60, 50:50, and 60:40. The finding of this work demonstrated fiber weight-matrix ratio of 50:50 gain a remarkable optimum strength with 224 % and 239 % enhancement for tensile and flexural strength respectively. The applied enhanced Rule of Mixture (E-ROM) model used in this study was reliable in predicting the experimental results whereby the composites reached an optimum value. Despite the successful enhancement of fiber–matrix compatibility and composite strength, the presence of fiber misalignment, structural imperfections, and voids observed in scanning electron microscopy (SEM) images still has some detrimental effects on its degradability. Nevertheless, a noteworthy strength reduction of PLA (80 %) as compared to the PLA-kenaf composite demonstrated better resistivity of weathering for the composite after 508 h. Hence, this study suggests deeper insights into the viability of eco-friendly combed methods as fiber treatments for kenaf as PLA reinforcement. It is proven that even without any chemical treatment, the composite demonstrated a remarkable mechanical resilience suitable for indoor non-structural applications.

In this paper, an effective algorithm for optimizing the subarray of conformal arrays is proposed. The method first divides the conformal array into several first-level subarrays. It uses the X algorithm to solve the feasible solution of first-level subarray tiling and employs the particle swarm algorithm to optimize the conformal array subarray tiling scheme with the maximum entropy of the planar mapping as the fitness function. Subsequently, convex optimization is applied to optimize the subarray amplitude phase. Data results verify that the method can effectively find the optimal conformal array tiling scheme.

The global financial landscape has undergone unprecedented transformations in recent decades, characterized by increased complexity, volatility, and interconnectivity. In this dynamic environment, the ability to anticipate stock market trends has become a paramount concern for investors, financial analysts, and policymakers alike. This research aims to distil insights and contribute to advanced predictive models for the dynamic global financial landscape. The exploration encompasses diverse approaches, including artificial neural networks, convolutional neural networks, LSTM, and traditional machine learning algorithms. Emphasis is placed on data pre-processing, numerical analyses, and the efficacy of LSTM models. The significance of this research lies in its synthesis of existing knowledge, offering a holistic view of methodologies and outcomes in Share Market Prediction. The model signifies a foundation for further innovation in predictive modeling, addressing real-time data challenges and dynamic market conditions. This work advances the understanding and forecasting of stock market trends.

Copper-based shape memory alloys (SMAs) have recently been introduced as a viable alternative to Ni–Ti SMAs. This is attributed to the fact that Cu-based SMAs are cheaper than Ni–Ti SMAs and exhibit satisfactory shape memory properties. Of these materials, Cu–Al–Ni SMAs have been widely used as they possess high thermal resistance and good mechanical properties. The concentration of Al and Ni is the most important factor determining the martensite type and transformation temperatures of these SMAs. Furthermore, thermal treatment, including quenching and aging, significantly affects the microstructural evolution and martensitic transformation (MT) temperatures of Cu–Al–Ni SMAs. Modifying the formed martensite phases and MT temperatures is possible by controlling the quenching rate and ageing temperature. Damping ability is one of the distinct advantages of these Cu-based SMAs, which has been modified and improved by many researchers. Plastic deformation is an effective method of evolving the microstructure of Cu–Al–Ni SMAs and improving their mechanical properties. Therefore, this present study examines the effect of alloy composition and thermal treatment on the MT temperatures and the microstructural evolution of Cu–Al–Ni SMAs. It also discusses the solutions to control the damping behavior of Cu-based SMAs, as well as the role of plastic deformation in improving the different properties Cu–Al–Ni SMAs. Lastly, additive manufacturing (AM) is proposed as a modern method of producing porous Cu–Al–Ni SMAs since it grants the possibility of controlling the porosities more efficiently.

Security professionals and law enforcement, who presently have to manually go through hours of film to find minor incidents, are becoming more interested in automated crime and violence detection. Developments in computer vision and machine learning are enabling automated systems to quickly scan and mark relevant incidents, reducing the workload of human investigators. Most existing datasets tend to focus on too specific situations (e.g., vehicle violence). Typically, these datasets consist of a limited number of video clips gathered from various sources, such as YouTube. Furthermore, the lack of distinct action-based groups or precise diversity in these datasets may limit their broader usefulness. To overcome the constraints of existing datasets, we have developed a balanced dataset that includes 3020 video clips. This dataset is evenly divided between 1510 non-violent clips and 1510 violent clips, capturing a diverse range of real-world situations. The duration of the clips ranged from 3 to 12 seconds, and they were recorded by non-professional actors. The aim of this comprehensive and balanced approach is to offer an extended resource for the training and evaluation of automated video analysis systems.

Within the family Fabaceae, the genus Glycine is composed of two subgenera annuals (2n=40) and perennials. This life strategy transition may have differentially affected the evolution of various gene families. Its cultivated species G. max has high level of susceptibility to major pathogens including viruses, bacteria and fungi. Understanding nucleotide-binding domain leucine-rich repeat (NLR) genes evolution in soybean is of paramount importance due to their central role in plant immunity and their potential in improving disease resistance in soybean cultivars. In this study, we investigated the significance of this annual-perennial transition on the macroevolution of NLR genes in the genus Glycine. Our results reveal a remarkable distinction between annual species such as Glycine max and Glycine soja, which exhibit an expanded NLRome compared to perennial species (G. cyrtoloba, G. stenophita, G. dolichocarpa, G. falcata, G. syndetika, G. latifolia and G. tomentella). Our evolutionary timescale analysis pinpoints recent accelerated gene duplication events for this expansion, which occurred between 0.1 and 0.5 million years ago, driven predominantly by lineage-specific and terminal duplications. In contrast, perennials initially experienced significant contraction during the diploidisation phase following the Glycine-specific whole-genome duplication event (~10 million years ago). Despite the reduction in the NLRome, perennial lineages exhibit a unique and highly diversified repertoire of NLR genes with limited interspecies synteny. The investigation of gene gain and loss ratios revealed that this diversification resulted from the birth of novel genes following individual speciation events. Among perennials, G. latifolia, a well-known resistance resource, has the highest ratio of these novel genes in the tertiary gene pool. Our study suggests evolutionary mechanisms, including recombination and transposition, as potential drivers for the emergence of these novel genes. This study also provides evidence for the unbalanced expansion of the NLRome in the Dt subgenome compared with the At subgenome in the young allopolyploid G. dolichocarpa. To the best of our knowledge, this is the first study to investigate the effect of annuality and perenniality life transition on the evolution of NLR genes in the genus Glycine to identify its genomics resources for improving the resistance of soybean crop with global importance on the economy and food security.

Global wheat production faces a severe threat from drought stress, necessitating innovative strategies for enhanced crop resilience. This study examined the synergistic impact of biochar and potassium co-application on the growth, physiological attributes, and antioxidant defense system of wheat under water deficit conditions at crown root initiation (CRI), anthesis, and grain development stage. Drought-induced reactive oxygen species (ROS) accumulation, particularly pronounced at the CRI stage, adversely affected all growth stages. At CRI, co-application of biochar and foliar potassium delivered significant improvements in growth parameters, including increased plant height (15.4%), spike length (50%), grain yield (43.0%), photosynthetic performance (chlorophyll content 125.8%), and relative water content (11.2%), compared to untreated drought-exposed counterparts. The combined application of biochar and potassium effectively reduced hydrogen peroxide production, electrolyte leakage, proline accumulation, and malondialdehyde generation, while increasing relative water content and glutathione levels under both well-irrigated and drought stress conditions. Furthermore, the combined biochar and potassium treatment was effective in mitigating oxidative stress and enhancing physiological resilience in wheat, particularly during the anthesis stage of drought stress. Specifically, the combined treatment ameliorated the effects of drought by reducing ROS levels through enhanced antioxidant enzyme activities and elevating osmoprotectants levels. The synergistic modulation of tissue osmotic balance and relative water content holds promise for mitigating drought-induced stress, offering an innovative and practical strategy for resilient wheat production in water-limited environments.

Heterojunction nanocomposites (ZnO:NiO:CuO) were synthesized via a hydrothermal method and annealed at three different temperatures (400 °C, 600 °C, and 800 °C). The structural, optical, and electrical properties were examined by employing XRD, SEM, UV–Vis, FTIR, and LCR meter techniques to investigate the effects of annealing. Increasing the annealing temperature resulted in the nanocomposites (NCPs) exhibiting enhanced crystallinity, purity, optical properties, and improved electrical and dielectric behavior. The calculated crystalline sizes (Debye-Scherrer method) of the NCPs were determined to be 21, 26 and 34 nm for annealing temperature 400 °C, 600 °C, and 800 °C, respectively. The calculated bandgaps of synthesized samples were found in the range of 2.92-2.55 eV. This temperature-dependent annealing process notably influenced particle size, morphology, band-gap characteristics, and photocatalytic efficiency. EDX analysis affirmed the sample purity, with elemental peaks of Zn, Cu, Ni, and O. These NCPs demonstrated exceptional photocatalytic activity against various dyes solutions (Methyl orange (MO), Methylene Blue (MB), and mixed solution of dyes) under sunlight and also showed good antibacterial properties assessed by the disc diffusion method. Notably, the nanocomposite annealed at 400 °C exhibited a particularly high degradation efficiency by degrading 96% MB and 91% MO in just 90 min under sunlight.

Introduction Caring is learned through faculty role-modeling and clinical interactions, enhancing nursing students’ caring character. Relationship between caring, motivation, teacher experience, and learning environment remains uncertain. Objective The present study aimed to explore the relationship between their caring characters, motivation, lecturer experience, and learning environment among undergraduate nursing students in Indonesia. Methods A cross-sectional study was conducted between December 2022 and February 2023, recruiting 550 undergraduate nursing students from 10 universities in West Java province, Indonesia. The study included instruments such as students’ perceptions of learning, academic motivation scale, service quality assessment of instructional laboratories, and caring character learning instrument. The Bootstrap analysis was used to analyze the mediating effect of study variable. Results The study involved participants aged 20–25 years. The mean scores for caring characters, lecturer experience, motivation, and learning environment were 2.18 ± 0.97, 3.46 ± 1.20, 4.32 ± 1.53, and 5.96 ± 2.08, respectively. The results showed significant direct effects of lecturer experience on caring character, mediating effects of learning environment, motivation, and chain mediating effects of learning environment and motivation. The direct effect accounted for 44.34% of the total effect, while the indirect effect was 35.21%. Conclusions The study found that learning environment and motivation mediate the relationship between lecturer experience and caring characters among undergraduate nursing students in West Java, Indonesia. Emphasizing best practices and creating a student-friendly environment is crucial for fostering guidance and support.

The fabrication of bi-material micro-components via two-component micro-powder injection moulding (2C-µPIM) from 3 mol% yttria-stabilised zirconia (3YSZ) and micro/nano bimodal stainless steel 316L (SS 316L) powders has received insufficient attention. Apart from this, retaining the bonding between ceramic and metal at different processing stages of 2C-µPIM is challenging. This study investigated the solvent and thermal debinding mechanisms of green bi-material micro-parts of 3YSZ and bimodal SS 316L without collapsing the ceramic/metal joining. In this research, feedstocks were prepared by integrating the powders individually with palm stearin and low-density polyethylene binders. The results demonstrated that during the solvent debinding process, the palm stearin removal rate in the bi-materials composed of 3YSZ and bimodally configured SS 316L feedstocks intensified with an increase in temperature. The establishment of interconnected pores in the solvent-debound components facilitated the thermal debinding process, which removed 99% of the binder system. Following sintering, the debound bi-materials exhibited a relative density of 95.3%. According to a study of the microstructures using field emission scanning electron microscopy, an adequate bond between 3YSZ and bimodal SS 316L was established in the micro-part after sintering. The bi-material sintered at 1350 °C had the highest hardness of 1017.4 HV along the joining region.

Mount Semeru is an active volcano and the highest on the island of Java with an altitude of 3726 meters above sea level (masl). The last major activity of Mount Semeru which occurred on 04 December 2021, there was an eruption or Hot Cloud Fall (GAP). According to the Centre for Volcanology and Geological Hazard Mitigation (PVMBG, 2021), the GAP in this incident was directed towards the southeast of Mount Semeru, namely Curah Kobokan with a glide distance of up to 11 km. The area affected by GAP is a small part of Malang Regency and Lumajang Regency. The purpose of this study is to analyze the quality of groundwater resources in the Rejali watershed after the eruption of Mount Semeru in 2021. This type of research is quantitative research. All data obtained is processed using the Pollution Index (IP) method listed in the Decree of the Minister of Environment Number: 115 of 2003 concerning Guidelines for Determining Water Quality Status. The groundwater quality parameters used are pH, BOD, DO, TDS, Fe, Mn, TSS, and COD. The results of this study are, the pollution index value in segments 1-3 is moderately polluted, and in segments 4-5 is lightly polluted.

In Laser Powder Bed Fusion (LPBF), residual stress in as-built 3D parts may require post-processing treatments to prevent the formation of cracks and voids, where heat treatment is commonly applied to overcome such issues. The selection of heat treatment parameters is critical in achieving suitable microstructure and mechanical properties in the final 3D-printed parts. For the past decade, less review on the effect of heat treatment parameters on the microstructure and mechanical performance of Ti6Al4V parts additively manufactured by LPBF has been reported. In this paper, the effect of heat treatment parameters such as heating temperature, heating rate, cooling rate, and holding time on the microstructure and mechanical properties of Ti6Al4V, namely microhardness and tensile strength, are discussed. In addition, the effectiveness of heat treatment in resolving LPBF issues for Ti6Al4V parts is also addressed. It has been reported that the common microstructure in as-built parts is acicular α′-martensite which, after heat treatment, transforms into an α+β bimodal structure. Microstructure development is reported to be significantly dependent on heating temperature as compared to holding time and cooling rate. Meanwhile, the effect of the heating rate has received little attention in previous reports. In general, heat treatment improves ductility (εb = 9–15%) but reduces strength (UTS = 1184 MPa–946 MPa) for LPBF parts. Additionally, heat treatment is found to be effective in improving porosity and residual stress in LPBF materials. Future work will involve focusing on optimising heat treatment.

The study focuses on the chemistry of groundwater and if it is suitable for drinking and for use in agriculture using water quality indices, GIS mapping, and multivariate analyses in Sharsa Upazila, Jashore district, Bangladesh. In this study, the concentration of NH4+, K+, Ca2+, EC, Turbidity overstep BDWS drinking standards in 69 %, 14 %, 100 %, 40 % (WHO), 73 % of samples respectively. The value of Water Quality Indices (WQI) results inferred that the maximum specimen was held good quality for drinking uses, and the values distributed central eastern part to the south-eastern part were good quality water in the selected studied area. The study area's PH, EC, SAR, Na (%), TH, and NO3− values were mapped using GIS tools to show their spatial distribution. The cluster and correlation matrix analyses are used to validate for Principle Component Analysis (PCA). The five PCA results exhibited that the presence of EC, turbidity, K+, SO42− and NO3− was significant and was caused by both geogenic (rock weathering and cation exchange) and anthropogenic (agrochemicals, animal feedback) factor. According to the hydro-geochemical data, the maximum number of samples is of the Ca–Mg–HCO3–Cl type and is dominated by rocks. The irrigation water indices like MH, KR, SAR, and %Na indicate show high-quality groundwater for irrigation purposes. Most of the samples were satisfactory and compiled with WHO and Bangladeshi criteria for standard drinking water guideline values.

Hazardous organic dyes, present in the effluents of industries, are continuously polluting the environment. Photodegradation of these dyes on catalyst surface under sunlight irradiation is economic, safe and suitable strategy to protect environment. Hence, the synthesis and applications of Zn1-xNixO (x = 0.00, 0.02, 0.04, 0.06) NPs are reported here. Effect of pH and dopant concentration was studied to modify the electrical, magnetic, antibacterial and photocatalytic properties of Ni doped ZnO NPs. The samples were characterized by Scanning electron microscopy (SEM), Powder X-ray diffraction (XRD), UV–Visible spectroscopy (UV–Vis.), Energy-dispersive X-ray spectroscopy (EDS) and Fourier-transform infrared spectroscopy (FTIR) to determine the morphology, crystallite structure, optical properties, elemental composition and functional group detection, respectively. LCR meter and VSM were used to evaluate the dielectric properties and magnetic properties of Ni doped ZnO NPs, respectively. XRD pattern confirmed the presence of hexagonal wurtzite geometry of ZnO NPs. The structural and morphological analysis showed the increase in crystallinity with little effect on shape of doped NPs by increasing the dopant concentration and slight increase of pH. It was observed that the Ni doped ZnO NPs possess good photocatalytic potential by 94% degradation of 20 ppm solution of methyl orange dye (MO) in just 80 min under sunlight. Moreover, the enhancement in antibacterial potential was also observed with increase in dopant concentration and decrease in crystallite size of doped ZnO NPs. Smaller size NPs were found more effective against gram negative bacterial strains.