Miracle-dz/UniFAR-FTUs huggingface dataset:
Durability of Ultem 9085 in Marine Environments: A Consideration in Fused Filament Fabrication of Structural Components

The long-term durability of polymer components produced by additive manufacturing (AM) in marine conditions is poorly understood. Here, fused filament fabrication (FFF) of Ultem 9085 was conducted and accelerated aging was performed. Two printing orientations (−45/45° and 0/90°) and two sample types (ASTM D638 Type 1 and Type 4) were produced and subjected to accelerated aging in either seawater or air. Results from tensile tests showed that the elastic modulus, yield strength and ultimate tensile strength increased after seawater aging, whereas the elongation to failure decreased. Results of thermogravimetric analysis (TGA) and derivative–TGA curves indicated that hydrolysis occurred after seawater exposure to the polycarbonate (PC) component and changes in structure or hydrogen bonds formed in the polyetherimide (PEI) component. Differential scanning calorimetry showed that physical aging occurred after short exposure periods and low temperature. Longer exposures and higher temperatures resulted in increasing plasticization by water and scission of the PC molecules. Results from Raman suggest that hydrolysis of the PC occurred, with a reduction in free volume produced by physical aging or hydrogen bonding with water molecules. These results highlight that Ultem 9085 is susceptible to degradation in marine environments, and there are two primary mechanisms, including physical and chemical aging. Their specific contribution is highly sensitive to the aging temperature and require careful selection in accelerated aging evaluations.
Salinity Induced Haematological Inflection in Indian White Shrimp, Fenneropenaeus indicus (H. Milne-Edwards, 1837)

The haematological profile of Indian white prawn (Fenneropenaeus indicus (H. Milne-Edwards, 1837), Penaeidae) at different salinities, i.e. 0, 5, 10, 15, 20, 25, 30 and 35 ppt was studied after acclimating the animals for 7 days in each saline condition. The haematological parameters, i.e. total haemolymph protein (THP), plasma protein (PP), serum protein (SP), haemocyte protein (HP), phenoloxidase, intracellular anion (NBT reduction), alkaline phosphatase (ALP), acid phosphatase (ACP) and total free amino acids (TFAA) were analysed and the data were statistically evaluated. These haematological parametes except ACP were at elevated level at 5 and 10 ppt indicating the animal’s hyper immune response to the stressful ambient conditions. ACP was significantly low at 5 and 10 ppt.
Fe3O4/PMMA with Well-Arranged Structures Synthesized through Magnetic Field-Assisted Atom Transfer Radical Polymerization

Particle- or fiber-reinforced polymer composites with controlled orientations are attracting interest and applications producing innovative materials, biological constructs, and energy devices. To gain the controlled orientations, filed-assisted synthesis is widely selected for its easy operation and control. In this paper, we designed magnetic field-assisted equipment and synthesized a magnetic polymer composite Fe3O4/PMMA with a well-arranged layers structure by combining the magnetic field with atom transfer radical polymerization (ATRP). During the polymerization of polymer composites, the magnetic nanoparticles were surrounded by monomers. With the growth of polymer chains, the magnetic particles pushed polymer chains to move according to a specific direction and form a well-arranged structure under the magnetic fields. The existence of a well-arranged layered structure of the composites gives potential guidance for controlling the micro-structure by adding an extra field during the polymerization process. The experimental results provided a possible design to influence the macroscale properties through control of the micro-structure of polymer composites.
Leveraging Multi-Annotator Label Uncertainties as Privileged Information for Acute Respiratory Distress Syndrome Detection in Chest X-ray Images

Acute Respiratory Distress Syndrome (ARDS) is a life-threatening lung injury for which early diagnosis and evidence-based treatment can improve patient outcomes. Chest X-rays (CXRs) play a crucial role in the identification of ARDS; however, their interpretation can be difficult due to non-specific radiological features, uncertainty in disease staging, and inter-rater variability among clinical experts, thus leading to prominent label noise issues. To address these challenges, this study proposes a novel approach that leverages label uncertainty from multiple annotators to enhance ARDS detection in CXR images. Label uncertainty information is encoded and supplied to the model as privileged information, a form of information exclusively available during the training stage and not during inference. By incorporating the Transfer and Marginalized (TRAM) network and effective knowledge transfer mechanisms, the detection model achieved a mean testing AUROC of 0.850, an AUPRC of 0.868, and an F1 score of 0.797. After removing equivocal testing cases, the model attained an AUROC of 0.973, an AUPRC of 0.971, and an F1 score of 0.921. As a new approach to addressing label noise in medical image analysis, the proposed model has shown superiority compared to the original TRAM, Confusion Estimation, and mean-aggregated label training. The overall findings highlight the effectiveness of the proposed methods in addressing label noise in CXRs for ARDS detection, with potential for use in other medical imaging domains that encounter similar challenges.
Solvothermal synthesis of SnO2 nanoparticles for perovskite solar cells application

Perovskite solar cells show great potential application prospects in the field of solar cells due to their promising properties. However, most perovskite solar cells that exhibit excellent photovoltaic performance typically require a carrier transport layer that necessitates a high-temperature annealing process. This greatly restricts the scalability and compatibility of perovskite solar cells in flexible electronics. In this paper, SnO2 nanoparticles with high crystallinity, good dispersibility and uniform particle size distribution are first prepared using a solvothermal method and dispersed in n-butanol solution. SnO2 electron transport layers are then prepared by a low-temperature spin coating method, and the photovoltaic characteristics of perovskite solar cells prepared with different SnO2 nanoparticles/n-butanol concentrations are studied. Results indicate that the rigid perovskite solar cell achieves the highest power conversion efficiency of 15.61% when the concentration of SnO2 nanoparticles/n-butanol is 15 mg mL−1. Finally, our strategy is successfully applying on flexible perovskite solar cells with a highest PCE of 14.75%. Our paper offers a new possibility for large-scale preparation and application of perovskite solar cells in flexible electronics in the future.
Using the Evidence-Based Adequacy Model across Educational Contexts: Calibrating for Technical, Policy, and Leadership Influences.

This article reports on a rigorous approach developed for calibrating the Evidence-Based Adequacy Model to suit the Ontario K–12 public education context, and the actual calibrations made. The four-step calibration methodology draws from expert consultations and a review of the academic literature. Specific attention is given to the technical revisions and, importantly, the significant influence of policy (values) and leaders’ decision-making on the calibration process. It also presents emerging implications for leaders and researchers who are considering calibrating the EBAM for use in their educational context. Calibrating the instrument was a necessary step before use in a jurisdiction outside of the United States, where the model was developed, and our team has been the first to outline a methodology and bring Canadian evidence to the discussion.
Effect of fermentation conditions on antioxidative, antimicrobial and techno-functional properties of Camellia sinensis leaves

Introduction and Aim: Fermented food is an excellent source of nutrition as it contains promising bioactive compounds. Black tea is a fermented product and the most commonly used beverage. In the present study, the effects of various fermentation conditions and drying techniques on the proximate nutritional analysis, phytochemicals, tannin, antioxidative, and antimicrobial activity of Camellia sinensis leaves were examined. Materials and Methods: The FTIR analysis was performed to detect the presence of different functional groups. Using standard methods, total phenol, flavonoid, and tannin content were determined. The antioxidant activity was determined by using DPPH, ABTS, and FRAPS assays. Results: The results showed a decrease in protein content and an increase in ash, moisture, and crude fiber content, indicating that the samples’ nutritional profiles were improved after fermentation processing. The FTIR results showed the presence of hydroxy, carboxyl, amine, alkane, alkene, and alkyne bonding. The antioxidant activity of fermented samples was more than that of unfermented ones. Fermented samples had strong antimicrobial activity against Escherichia coli. An increase in TPC and TFC contributed to the rise in the antioxidant activity of the fermented sample. An increase in TSS suggested improvement in flavour and sweetness. Antimicrobial activity against Escherichia coli, demonstrated their potential as a natural antimicrobial agent. Conclusion: The enhanced antimicrobial activity of fermented tea leaves highlights the importance of the fermentation process in producing tea with improved microbial control and possible health benefits.
Mechanism of V-Shaped Pits on Promoting Hole Injection in the InGaN MQWs: First-Principles Investigation

In the InGaN multiple quantum wells (MQWs), V-shaped pits play a crucial role in carrier transport, which directly affects emitting efficiency. First-principles calculations are applied to investigate the formation of the V-shaped pits, and the results indicate that they are inclined to form in the N-rich environment. Meanwhile, we calculate the interfacial electronic properties of the sidewalls of the V-shaped pits with varying indium (In) and magnesium (Mg) compositions. The calculated valence band offset (VBO) of the In0.3Ga0. 7N/Ga0.94Mg0. 06N (0001) is 0.498 eV, while that of the In0.07Ga0. 93N/Ga0.94Mg0. 06N (101̅1) is 0.340 eV. The band alignment results show that the valence band edges in the Ga1–yMgyN layer are in higher energy than in the InxGa1–xN layer. These are in good agreement with the values reported in the previous numerical simulation. Moreover, the calculation of the projected density of states (PDOS) of interfaces discloses that the strong hybridization between the N 2p orbital and the Mg 2p orbital exerts a vital influence on the upward shifts of the valence band edges in the superlattices (SLs). All these results reveal that holes are easier to inject into the quantum wells (QWs) via the sidewall of V-shaped pits rather than the c-plane QWs, providing a theoretical basis for the growth of InGaN MQWs samples containing V-shaped pits.
EFFECT OF STAINLESS STEEL 304 TIG WELDING AMPERE ON STRESS CORROSION CRACKING PHENOMENON

This article discusses the experimental results of stress corrosion cracking grade 304 stainless steel after GTAW welding under environmental corrosion simulation. The corrosion phenomenon that occurs is Stress Corrosion Cracking (SCC). The experimental method is a specimen welded using a current of 55, 60, and 65 Ampere respectively with a gas flow rate of 5 L/min argon shielding gas. The constant tensile loads of 2000 N and 4000 N in the state of the test object immersed for 2 x 24 hours in a solution of HCl + Aquades. Different Ampere and shielding gas flow rate parameters affected the cracks phenomenon. Vickers Hardness and Microstructure were used to evaluate the weld area. The lowest ampere of the weld results in maximum rough cracks from the surface and it's visible on the surface. The increased hardness of the 55 Ampere current specimen indicates a change in structure or phase after welding. The highest ampere produces fine cracks on all surfaces.
Root Cause Analysis for Cloud-Native Applications

Root cause analysis (RCA) is a critical component in maintaining the reliability and performance of modern cloud applications. However, due to the inherent complexity of cloud environments, traditional RCA techniques become insufficient in supporting system administrators in daily incident response routines. This article presents an RCA solution specifically designed for cloud applications, capable of pinpointing failure root causes and recreating complete fault trajectories from the root cause to the effect. The novelty of our approach lies in approximating causal symptom dependencies by synergizing several symptom correlation methods that assess symptoms in terms of structural, semantic, and temporal aspects. The solution integrates statistical methods with system structure and behavior mining, offering a more comprehensive analysis than existing techniques. Based on these concepts, in this work, we provide definitions and construction algorithms for RCA model structures used in the inference, propose a symptom correlation framework encompassing essential elements of symptom data analysis, and provide a detailed description of the elaborated root cause identification process. Functional evaluation on a live microservice-based system demonstrates the effectiveness of our approach in identifying root causes of complex failures across multiple cloud layers.
Comparison Between Two Treatment options for screw retained Mandibular Dentures Regarding Implant Stability

This study aimed to compare between using four implants in the inter foraminal region and using four implants (two in the anterior region and two short implants in the posterior region) to retain mandibular dentures regarding implant stability. Fourteen completely edentulous patients were selected and divided into two groups (seven patients for each group). Group A, Each patient was rehabilitated with four implants in the inter-foraminal region retaining mandibular denture. Group B, Each patient was rehabilitated with four implants (two conventional were inserted in the inter foraminal region and two short implants were inserted on each side at the first molar regions) retaining mandibular denture. Immediate loading was done. Implant stability was evaluated using osstell at time of insertion, after two months, and after four months. Independent sample t-test was used to compare between two groups in non-related samples. Repeated measure was used to compare between follow-up periods within groups. Group A showed higher implant stability compared to group B. However, the t-test showed no statistically significant difference. Also, there was an increase in implant stability throughout the study period.
Deciphering the molecular classification of pediatric sepsis: integrating WGCNA and machine learning-based classification with immune signatures for the development of an advanced diagnostic model

Introduction: Pediatric sepsis (PS) is a life-threatening infection associated with high mortality rates, necessitating a deeper understanding of its underlying pathological mechanisms. Recently discovered programmed cell death induced by copper has been implicated in various medical conditions, but its potential involvement in PS remains largely unexplored. Methods: We first analyzed the expression patterns of cuproptosis-related genes (CRGs) and assessed the immune landscape of PS using the GSE66099 dataset. Subsequently, PS samples were isolated from the same dataset, and consensus clustering was performed based on differentially expressed CRGs. We applied weighted gene co-expression network analysis to identify hub genes associated with PS and cuproptosis. Results: We observed aberrant expression of 27 CRGs and a specific immune landscape in PS samples. Our findings revealed that patients in the GSE66099 dataset could be categorized into two cuproptosis clusters, each characterized by unique immune landscapes and varying functional classifications or enriched pathways. Among the machine learning approaches, Extreme Gradient Boosting demonstrated optimal performance as a diagnostic model for PS. Discussion: Our study provides valuable insights into the molecular mechanisms underlying PS, highlighting the involvement of cuproptosis-related genes and immune cell infiltration.
Federated Texture Classification: Implementing Colorectal Histology Image Analysis using Federated Learning

This research explores neural network models' performance and adaptability in the context of the colorectal histology dataset as it pertains to the categorization of textures. Inception, VGG19, and MobileNet, together with their federated variations, are among the models being examined. The study includes a detailed evaluation, parameter analysis, and training information. VGG19 stands out as a particularly noteworthy high performance, with remarkable accuracy, precision, and recall. Due to its lightweight design, MobileNet performs less well, but its potential is enhanced by the addition of federated learning. The accuracy and precision of federated versions of Inception, VGG19, MobileNet, and a Lightweight MobileNet model are competitive, with FL-Lightweight MobileNet achieving outstanding results. The work has important ramifications for the field of medical image analysis since it shows how federated learning may balance the need for data confidentiality and privacy with model performance. This study marks a turning point in the development of medical imaging by opening the door to in-depth investigation into the complex interactions across federated paradigms. Furthermore, these results provide a compelling story in the wider discussion of how cutting-edge technologies and the pressing needs of contemporary healthcare might work together.
A Systemic Approach to Managing Natural Disasters

Natural disasters may be defined as events that are triggered by natural phenomena or natural hazards (e.g., earthquakes, hurricanes, floods, windstorms, landslides, volcanic eruptions and wildfires). Throughout history, natural disasters have exerted a heavy toll of death and suffering and are increasing alarmingly worldwide. During the past two decades they have killed millions of people, and adversely affected the life of at least one billion people. For example, recent disasters, such as the quake that triggered a tsunami in the Indian Ocean (United Nations Development Programme [UNDP], 2005); earthquake in Pakistan (Kamp et al., 2008); the Wenchuan earthquake in China (Zhao et al., 2009) and more recently the L’Aquila earthquake in Italy (Owen & Bannerman, 2009). On the other hand, hurricanes have shown how vulnerable coastal communities could be to such events. For instance, Hurricane Katrina caused an estimated $35 to $60 billion in damage aBsTraCT
New Techniques and Applications of Bioprocess inspired Manufacturing and Synthesis

Manufacturing and designing bio-inspired materials has been successful in the past two decades due to the techniques, which focus on emulating well-defined geometries or specific functionalities of real biological materials. Additionally, in contrast to our human technologies, which often need severe circumstances, biological structure-forming techniques in natural frameworks may produce biomaterials effectively and correctly in ecologically benign conditions. Thus, bioprocess-inspired fabrication has been suggested as a new research area in recent years to explore natural structure-forming processes in order to develop unique approaches for manufacturing sophisticated materials with different morphologies and functionalities. In this paper, we focus on reviewing the principles, techniques, and applications of bioprocess-inspired manufacturing and synthesis. This paper also reviews the process of biomineralization, which is an application of bioprocess-inspired fabrication used by living organisms in establishing biominerals such as shells, bones, diatoms, and teeth. This survey has aim to critically discuss bio-process-inspired to cover the dearth of literature in this area of research.
P-wave seismic time-lapse analysis of horizontal well completions causing pressure compartmentalization

When horizontal wells are completed many changes can occur. During completions, pressure changes take place because of the fluid and proppant injected. One way of monitoring such changes is through the use of time-lapse seismic data. In Wattenberg Field, located near Greeley, Colorado, Anadarko Petroleum Corporation (APC) has teamed up with the Colorado School of Mines Reservoir Characterization Project (RCP) to acquire time-lapse seismic data over a section of land in which eleven horizontal wells were completed. The P-wave seismic is of considerable interest since the P-waves are sensitive to pressure changes in the reservoir. However, the first step is to determine if there are considerable pressure changes associated with the completions. The net pressures from the completion reports per stage were studied. The net pressure indicates the creation of hydraulic fractures and the propagation of those fractures. This thesis hypothesizes that where there is a positive net pressure, the pressure is building up near the wellbore and a negative net pressure indicates hydraulic fracture propagation. A pre-stack seismic inversion was done to determine the P-impedance changes in the time-lapse surveys. The percent difference in P-impedance volume was observed with the net pressure trend in corresponding reservoir intervals. This analysis showed that the negative changes in P-impedance correlate with the negative net pressure. This analysis implies that the formation is being hydraulically fractured and the fractures are propagating away from the wellbore, so the net pressure is decreasing resulting in the decrease in P-impedance. The results of this study allows for integration between the completion parameters and the time-lapse seismic analysis. This study then provides insight for the stimulated reservoir volume, since the seismic anomalies in combination with the completion pressures can identify areas that were fractured better than others. These areas correspond to negative net pressures during hydraulic fracturing stimulation.
Consistent delay in recent timing of passerine autumn migration

Climate change affects important biological processes, bird migration phenology being a particular well-documented one. While spring migration have been found to advance by numerous studies, autumn migration is less studied and show more variable change in timing. Few studies of autumn migration are based on data from after 2000, leaving the last two decades to be relatively less studied. Here, we investigate recent change in autumn migration phenology of European passerines. The most recent available bird ringing data from Denmark is used to analyse phenological change of median and late migration of 14 passerine migrants between 2003–2021. We find an overall delay of autumn migration, mainly driven by short-distance migrants. All short-distance migrants, one out of five medium-distance and three out of five long-distance migrants delay autumn migration. None of the included species advance autumn migration significantly. As climate change has continuously resulted in milder conditions in north-western Europe, we expect this to cause further effects on migration phenology also in recent decades. Our results provide novel insight into recent migration phenology trends, and the observed delay in long-distance migrants may illustrate a changed response to climate change.