Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of Toluene Biodegradation Activity in Groundwater from a Shallow Bedrock Aquifer Underlying a Phytoremediation System

ASSESSMENT OF TOLUENE BIODEGRADATION ACTIVITY IN GROUNDWATER FROM A SHALLOW BEDROCK AQUIFER UNDERLYING A PHYTOREMEDIATION SYSTEM Andrea J. Roebuck Advisor: University of Guelph, 2018 Kari E. Dunfield Researchers have been striving to understand and model environmental groundwater remediation to facilitate case-specific decision-making and optimize remediation. This has proven difficult due to the highly site-specific nature of the processes affecting contamination fate and transport in natural environments. This study aims to contribute to the science for decision-making processes and improve our understanding of the role of microbes in groundwater remediation. To achieve this, depth-discrete samples were obtained over three seasons from a toluenecontaminated, shallow, fractured bedrock aquifer underlying a phytoremediation system in Southwestern Ontario. Quantitative PCR was used to quantify abundance and potential activity of aerobic and anaerobic toluene degrading communities in groundwater. Active aerobic and anaerobic toluene degraders were present across the Site in all sampling events. Abundance and activity shifts were associated with both season and redox conditions, but not statistically by toluene concentration.
Comparing the Performance of Rolled Steel and 3D-Printed 316L Stainless Steel

Three-dimensional printing is a non-conventional additive manufacturing process. It is different from the conventional subtractive manufacturing process. It offers exceptional rapid prototyping capabilities and results that conventional subtractive manufacturing methods cannot attain, especially in applications involving curved or intricately shaped components. Despite its advantages, metal 3D printing will face porosity, warpage, and surface roughness issues. These issues will affect the future practical application of the parts indirectly, for example, by affecting the structural strength and the parts’ assembly capability. Therefore, this study compares the qualities of the warpage, weight, and surface roughness after milling and grinding processes for the same material (316L stainless steel) between rolled steel and 3D-printed steel. The experimental results show that 3D-printed parts are approximately 13% to 14% lighter than rolled steel. The surface roughness performance of 3D-printed steel is better than that of rolled steel for the same material after milling or grinding processing. The hardness of the 3D-printed steel is better than that of the rolled steel. This research verifies that 3D additive manufacturing can use surface processing to optimize surface performance and achieve the functions of lightness and hardness.
Identification of Salt-Sensitive and Salt-Tolerant Genes through Weighted Gene Co-Expression Networks across Multiple Datasets: A Centralization and Differential Correlation Analysis

Salt stress is a significant challenge that severely hampers rice growth, resulting in decreased yield and productivity. Over the years, researchers have identified biomarkers associated with salt stress to enhance rice tolerance. However, the understanding of the mechanism underlying salt tolerance in rice remains incomplete due to the involvement of multiple genes. Given the vast amount of genomics and transcriptomics data available today, it is crucial to integrate diverse datasets to identify key genes that play essential roles during salt stress in rice. In this study, we propose an integration of multiple datasets to identify potential key transcription factors. This involves utilizing network analysis based on weighted co-expression networks, focusing on gene-centric measurement and differential co-expression relationships among genes. Consequently, our analysis reveals 86 genes located in markers from previous meta-QTL analysis. Moreover, six transcription factors, namely LOC_Os03g45410 (OsTBP2), LOC_Os07g42400 (OsGATA23), LOC_Os01g13030 (OsIAA3), LOC_Os05g34050 (OsbZIP39), LOC_Os09g29930 (OsBIM1), and LOC_Os10g10990 (transcription initiation factor IIF), exhibited significantly altered co-expression relationships between salt-sensitive and salt-tolerant rice networks. These identified genes hold potential as crucial references for further investigation into the functions of salt stress response in rice plants and could be utilized in the development of salt-resistant rice cultivars. Overall, our findings shed light on the complex genetic regulation underlying salt tolerance in rice and contribute to the broader understanding of rice’s response to salt stress.
On Mixed Wind-Sea/Swell Conditions in the Open Ocean

A number of studies have aimed to find those factors affecting the drag coefficient at the ocean surface. The direction of swell relative to the local wind has been proposed as a contributing factor. Different approaches have been used, but the results have been inconclusive. Here observed and modelled 2D wave spectra are compared. The data is obtained by the microwave MIROS-radar and the WAM-model (cycle-4) at different locations in the North Sea and Norwegian Sea. Based on the fact that the WAM source functions are not accounting for swell effects, a difference between the observed and simulated wind-sea growth is expected in situations where wind is opposing swell and wind is blowing in the same direction as swell if this effect should be considered significant. In this study no clear evidence is found that swell have a significant impact on integrated wave parameters, but may affect the shape of the wave spectrum. However, this type of analysis is highly sensitive to the accuracy of the modeled wind forcing, demanding both a high spatial resolution and a small integration time step, and preferably stationary wind conditions.
Pollution Characteristics and Health Risks of Polycyclic Aromatic Compounds (PACs) in Soils of a Coking Plant

Coke production is an important source of environmental polycyclic aromatic compounds (PACs), including parent polycyclic aromatic hydrocarbons (PAHs) and their derivatives. The focus near coking plants has primarily been on parent-PAH contamination, with less attention given to highly toxic derivatives. In this study, soil samples were collected from both within and outside of a coking plant. The concentrations of parent-PAHs and their derivatives, including methylated-PAHs, oxygenated-PAHs, and nitrated-PAHs, were examined. Spatial interpolation was employed to determine their spatial distribution patterns. Methods for identifying potential sources and conducting incremental lifetime cancer risk analysis were used. This could achieve a comprehensive understanding of the status of PAC pollution and the associated health risks caused by coke production. The concentrations of total PACs inside the plant ranged from 7.4 to 115.8 mg/kg, higher than those outside (in the range of 0.2 to 65.7 mg/kg). The spatial distribution of parent-PAH concentration and their derivatives consistently decreased with increasing distance from the plant. A significant positive correlation (p < 0.05) among parent-PAHs and their derivatives was observed, indicating relatively consistent sources. Based on diagnostic ratios, the potential emission sources of soil PACs could be attributed to coal combustion and vehicle emissions, while principal component analysis–multiple linear regression further indicated that primary emissions and secondary formation jointly influenced the PAC content, accounting for 60.4% and 39.6%, respectively. The exposure risk of soil PACs was dominated by 16 priority control PAHs; the non-priority PAHs’ contribution to the exposure risk was only 6.4%.
Contrasting Multi-Modal Similarity Framework for Video Scene Segmentation

This paper proposes a video scene segmentation framework referred to as a Contrasting Multi-Modal Similarity (CMS). Video is composed of multiple scenes which are short stories or semantic units of video, with each scene consisting of multiple shots. The task of video scene segmentation aims to semantically segment long videos, such as movies, into the sequence of scenes by identifying the boundaries of each scene transition. Current video scene segmentation frameworks have primarily relied on comparing only the visual cues of adjacent shots to identify scene boundaries. These frameworks have focused on two major approaches: 1) comparing only the visual cues of adjacent frames to distinguish between scenes and 2) performing clustering based on visual cues for distinction among scenes. However, within videos, there exist numerous scenes that are difficult to distinguish using visual information alone, as they often appear similar or ambiguous. Taking inspiration from the aforementioned issues, we propose a framework referred to as CMS that leverages not only visual cues (i.e., shots) but also textual cues (i.e., captions) to semantically distinguish scenes. The new framework, CMS, leverages visual cues and text cues as follows: 1) Generate captions corresponding to each shot using a zero-shot captioning model (Caption Generation). 2) Construct similarity score matrices for each modality to measure semantic similarities (Similarity Score Calculation). 3) Based on the above matrix, select similar shots and dissimilar shots for contrastive training (Similarity Score-based Sampling). Our experiments show that the CMS framework advances the performance to exceed the previous state-of-the-art methods with a relatively simple approach without complex model architectures.
Enhanced Knowledge Distillation for Advanced Recognition of Chinese Herbal Medicine

The identification and classification of traditional Chinese herbal medicines demand significant time and expertise. We propose the dual-teacher supervised decay (DTSD) approach, an enhancement for Chinese herbal medicine recognition utilizing a refined knowledge distillation model. The DTSD method refines output soft labels, adapts attenuation parameters, and employs a dynamic combination loss in the teacher model. Implemented on the lightweight MobileNet_v3 network, the methodology is deployed successfully in a mobile application. Experimental results reveal that incorporating the exponential warmup learning rate reduction strategy during training optimizes the knowledge distillation model, achieving an average classification accuracy of 98.60% for 10 types of Chinese herbal medicine images. The model boasts an average detection time of 0.0172 s per image, with a compressed size of 10 MB. Comparative experiments demonstrate the superior performance of our refined model over DenseNet121, ResNet50_vd, Xception65, and EfficientNetB1. This refined model not only introduces an approach to Chinese herbal medicine image recognition but also provides a practical solution for lightweight models in mobile applications.
Properties of Optical and Laser-Related Materials: A Handbook

Laser Materials and Their Hosts. Nonliner Optical Crystals. Main Optical Materials. Alkali and Alkaline Earth Halides. Oxides, Sulfides, Selenides and Tellurides. Semiconductors and Other Crystalline Materials. Glasses and Polymers. Liquids. Gases. Appendix. References. Index.
Inhibition of corticosterone synthesis impairs cued water maze consolidation, but it does not affect the expression of BDNF, CK2 and SGK1 genes in dorsal striatum

Corticosterone (CORT) release during learning experiences is associated with strong memories and activity of the glucocorticoid receptor. It has been shown that lesions of the dorsal striatum (DS) of rats trained in the cued version of the Morris water maze impair memory, and that local injection of CORT improves its performance, suggesting that DS activity is involved in procedural memory which may be modulated by CORT. We trained rats in cued Morris water maze and analyzed the effect of CORT synthesis inhibition on performance, CORT levels, expression of plasticity-involved genes, such as the brain derived neurotrophic factor (BDNF), casein kinase 2 (CK2), and the serum/glucocorticoid regulated kinase 1 (SGK1), as well as the presence of phosphorylated nuclear glucocorticoid receptor in serine 232 (pGR-S232) in the DS. The inhibition of CORT synthesis by metyrapone reduced CORT levels in plasma, prevented its increment in DS and impaired the performance of cued water maze. Additionally, there was an increase of CK2 and SGK1 mRNAs expression in trained subjects, which was unrelated to CORT levels. Finally, we did not observe changes in nuclear pGR-S232 in any condition. Our findings agree with evidence demonstrating that decreasing CORT levels hinders acquisition and consolidation of the spatial version of the Morris water maze; these novel findings broaden our knowledge about the involvement of the DS in the mechanisms underlying procedural memory.
Coping Strategies for Work-Family Conflict among Working Housewives in Cipatujah Village, Tasikmalaya Regency, Indonesia

This research addresses the escalating phenomenon of working mothers in Indonesia, particularly in Cipatujah Village, Tasikmalaya Regency. With nearly 30 percent of married women engaged in employment, the study focuses on the work-family conflict experienced by these working housewives and aims to uncover their coping strategies. The literature review emphasizes the scarcity of research on coping efforts from the perspective of working women, particularly in developing country contexts like Indonesia. Using a qualitative approach, the study explores the experiences of six working homemakers managing dual roles through observation, interviews, and document analysis. The findings reveal diverse types of work-family conflict, including time-based, strain-based, and behavior-based conflicts. The coping strategies employed by these housewives vary, encompassing problem-focused coping, emotion-focused coping, and a combination of both. This research contributes to the existing literature by providing nuanced insights into the challenges faced by working housewives in a specific rural context. The variations in coping strategies underscore the importance of recognizing individual differences and the complexity of work and family contexts. The study advocates for tailored support systems and policies, considering cultural values and grassroots-level experiences. In conclusion, this research contributes to a comprehensive understanding of coping mechanisms for work-family conflict among working mothers in Indonesia, offering valuable implications for policymakers and future research endeavors.
PSO-Aided Inverse Design of Silicon Modulator

Optimizing doping profiles has always been a key approach to enhance the performance of silicon modulators. Nevertheless, the pursuit of innovative profiles has encountered barriers in recent times. To tackle this issue, the idea of inverse design, widely adopted in passive photonic devices, can be employed in silicon active devices. As a result, we incorporate the inverse design method with the particle swarm optimization (PSO) algorithm and achieve a G-shaped doping profile for the modulator, exhibiting superior <inline-formula><tex-math notation="LaTeX">$V_{\pi } L$</tex-math></inline-formula> of 0.68 V<inline-formula><tex-math notation="LaTeX">$\cdot$</tex-math></inline-formula>cm and low loss of 9.3 dB/cm. The small-signal frequency response suggests a reliable operation range under reverse biases of 1<inline-formula><tex-math notation="LaTeX">$\sim$</tex-math></inline-formula>3 V with the bandwidth over 26 GHz. The silicon modulator with a G-shaped design demonstrates remarkable efficiency in modulation and very low loss, suggesting its great potential for application in microwave front-end systems. The use of inverse design shows great potential in enhancing active silicon photonic devices, allowing for faster, higher-capacity, and more reliable data communication systems.
Forensic value of orthodontic records for human identification: a systematic review

Extensive dental records are produced for orthodontic planning and treatment. Photographs, radiographs, and descriptive data used to register patient progress have benefited the fields of civil litigation and human identification. This study aimed to perform a systematic literature review guided by the following question: What type of orthodontic antemortem (AM) data have been used more often to confirm human dental identifications? The research protocol followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) and the Joanna Briggs Institute (JBI) manual. Registration was made in Open Science Framework. Ten databases were searched (LILACS, BBO, Cumed, Embase, MedLine [PubMed], SciELO, Scopus, Web of Science, Easy Dans, and BDTD). The eligible studies were only descriptive observational and should address the topic of human identification using orthodontic AM data. The risk of bias was assessed with the JBI tool. The initial search found 2,216 studies, of which 16 were eligible. Clinical photographs and panoramic radiographs were the most common orthodontic AM data. Most human identification cases relied on morphological (e.g., rotation and crown shape) and therapeutic (e.g., orthodontic appliances and restorations) identifiers. Orthodontic records can support human identification with relevant dental evidence, especially when providing images (radiographic or not). Forensic dentists should understand proper image analysis to interpret and detect morphological and therapeutic identifiers of forensic value.
Looking Back to Move Forward: Bibliometric and Visual Analysis of Knowledge Transfer in University-Industry Collaboration

Knowledge transfer in university-industry collaboration (KTUIC) has been a hot issue of concern in recent years. Based on 874 articles published in the core collection of Web of Science, this paper conducts an in-depth bibliometric and visual analysis in terms of literature distribution, cooperation network, co-citation, knowledge base, and research hotspots analysis. The results show that the number of annual publications has shown an approximate exponential growth in the past decades. The UK is the most critical node in cross-border cooperation. Alessandro Muscio, with 11 publications, and Henry Etzkowitz, with 793 citations, are the most prolific and cited authors respectively. Research Policy has the highest frequency of citations. The knowledge base of KTUIC includes UIC and knowledge transfer, basic theories of U-I relationships, university TTOs, Bayh-Dole Act and university patenting, and individuals in university technology transfer. Research hotspots mainly focus on the related issues of third mission and entrepreneurial universities. Additionally, we also propose the future research agenda of KTUIC from the perspective of five knowledge bases. These findings contribute to a deeper understanding of the development status and core issues in KTUIC, and offer valuable guidance for future research directions.
Understanding Chemical and Physical Processes of Biogenic Volatile Organic Compounds in The Atmospheric Boundary Layer

Biogenic volatile organic compounds (BVOC) are oxidized quickly in the atmosphere to form oxygenated VOC (OVOC) and play crucial roles in the formation of ozone and secondary organic aerosols. We use the National Center for Atmospheric Research’s Large-Eddy Simulation (LES) model and DISCOVER-AQ 2011 flight data to understand the role of boundary layer turbulence on the atmospheric chemistry of key BVOC species and their oxidation products. We simulate three distinct convective environments during the campaign, representing fair weather conditions (Case 1: 1 July), a convective event dominated by southwesterly flow (Case 2: 11 July) and a polluted event with high temperature and convection (Case 3: 29 July). Isoprene segregation is greatest in the lower boundary layer under warm and convective conditions, reaching up to a 10% reduction in the isoprene-OH reaction rate. Under warm and convective conditions, the BVOC lifetimes lengthen due to increased isoprene emission, elevated initial chemical concentrations and OH competition. Although turbulence-driven segregation has less influence on the OVOC species, convection mixes more OVOC into the upper atmospheric boundary layer (ABL) and increases the total OH reactivity. Production and loss rates of ozone above 2 km in all the three cases indicate in situ ozone
The Interaction Between Body Mass Index Genetic Risk Score and Dietary Intake on Weight Status: A Systematic Review

Background The escalating global obesity epidemic and the emergence of personalized medicine strategies point to the pressing need to investigate the interplay between genetic risk scores (GRSs), dietary intake, and their combined impact on weight status. This systematic review synthesizes evidence from diverse studies to elucidate how dietary patterns and individual foods interact with genetic predisposition to obesity. Methods Literature searches were conducted in the PubMed, Embase, Science Direct, and Scopus databases until August 2023, following PRISMA guidelines. Out of 575 articles, 15 articles examining the interaction between genetic risk score for body mass index and dietary intake on weight outcomes met the inclusion criteria. All included studies were cross-sectional in design and were assessed for quality using the Newcastle‒Ottawa Scale. Results Unhealthy dietary intake exacerbated the genetic predisposition to obesity, evident in studies assessing Western diet, sulfur microbial diet, and individual macronutrients, including saturated fatty acids, sugar-sweetened beverages and fried foods. Conversely, adhering to healthier dietary intake mitigated the genetic predisposition to obesity, as observed in studies involving Alternative Healthy Eating Index, Alternative Mediterranean Diet, Dietary Approach to Stop Hypertension scores, healthy plant-based diets, and specific foods such as fruits, vegetables, and n-3 polyunsaturated fatty acids. Conclusion This is the first systematic review to explore the interaction between genetics and dietary intake in shaping obesity outcomes. The findings have implications for tailored interventions; however, more controlled clinical trials with robust designs are needed to be able to recommend personalized nutrition based on nutrition for obesity prevention and management.
Exploring the Link between Social Support and Patient-Reported Outcomes in Chronic Obstructive Pulmonary Disease Patients: A Cross-Sectional Study in Primary Care

We aimed to explore the link between social support and various patient-reported outcome measures (PROMs) in primary care patients with COPD. This was a cross-sectional study with 168 patients with COPD from six primary care centers in Crete, Greece. We collected data on sociodemographic characteristics, medical history, disease-specific quality of life, the COPD Assessment Test (CAT), fatigue, the Fatigue Severity Scale (FSS), phycological parameters, Patient Health Questionnaire-9, General Anxiety Disorder-7, sleep complaints, the Pittsburg Sleep Quality Index, the Athens Insomnia scale (AIS), and the Epworth Sleepiness Scale. Social support was measured using the Multidimensional Scale of Perceived Social Support (MSPSS). Out of 168 patients with COPD, 114 (68.9%) exhibited low levels of social support. Low social support (MSPSS total ≤ 5) was positively associated with COPD symptoms (CAT score ≥ 10) (OR = 3.97, 95%CI:1.86–8.44; p < 0.01), fatigue (FSS ≥ 36) (OR = 2.74, 95%CI:1.31–5.74; p = 0.01), and insomnia symptoms (AIS ≥ 6) (OR = 5.17 95%CI:2.23–12.01; p < 0.01), while the association with depressive symptoms (PHQ-9 ≥ 10) was marginally significant (OR = 3.1, 95%CI:0.93–10.36; p = 0.07). Our results suggest that lower levels of social support are positively associated with PROMs in patients with COPD. Therefore, our findings show an additional way to improve the overall health of patients with COPD in primary care by putting social support at the epicenter of actions.