Miracle-dz/UniFAR-FTUs huggingface dataset:
Scaling Challenges in High Power Photonic Crystal Surface-Emitting Lasers

Since the initial proposal in 1999 by Noda et al., photonic crystal surface emitting lasers (PCSELs) have shown to achieve large area, coherent lasing with a narrow, single mode beam. Owing to their unique orthogonal electrical/optical cavity scheme, PCSELs have emerged as one of the most promising platforms for high power diode lasers. In this paper, we report the performance trade-offs and challenges in power scaling, modal competition, and charge injection control. To address these challenges, we investigate the electrical and optical performances of PCSELs under high-power operation. Heterostructure designs with electron block layers were incorporated for efficient and balanced electrical charge injection. Symmetry breaking strategy was introduced in the photonic crystal design to engineer the in-plane momentum dependent quality factor (Q(k)) for mode discrimination and single mode operation. The impact of electrode designs was also investigated to achieve large area uniform charge injection. Simulation results of these designs indicate promising solutions and improved performances for large-area high-power and single-mode PCSEL operations.
Associations of Computed Tomography Image-Assessed Adiposity and Skeletal Muscles with Triple-Negative Breast Cancer

Simple Summary Despite BMI’s wide use as a measure of body size and its clinical and epidemiological utility, it measures weight and height without differentiating between adipose tissue and skeletal muscle. To overcome these limitations, we analyzed the third lumbar (L3) computed tomography (CT) images of 350 breast cancer patients to measure the areas of adipose tissue and five-level skeletal muscle components and assessed their relationships with triple-negative breast cancer (TNBC), an aggressive subtype leading to higher mortality. We found that higher areas of adipose tissues were associated with an increased likelihood of TNBC subtype, especially in premenopausal women. Since the risk factors associated with adiposity and skeletal muscles are modifiable, such as healthy diets, resistance training, and adequate protein intake, it is expected that a better understanding of this body composition component will lead to novel prevention and management strategies for TNBC. Abstract Obesity measured by anthropometrics is associated with increased risk of triple-negative breast cancer (TNBC). It is unclear to what extent specific adipose tissue components, aside from muscle, are associated with TNBC. This retrospective study included 350 breast cancer patients who received treatment between October 2011 and April 2020 with archived abdominal or pelvic computed tomography (CT) images. We measured the areas of adipose tissue and five-density levels of skeletal muscle on patients’ third lumbar vertebra (L3) image. Logistic regression was performed to examine the associations of specific adiposity and skeletal muscles components and a four-category body composition phenotype with the TNBC subtype. Results showed that higher vs. lower areas (3rd vs. 1st tertiles) of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) were associated with increased odds of TNBC vs. non-TNBC after adjusting for age, race, stage, tumor grade, tumor size, and skeletal muscle areas (adjusted odds ratio [AOR], 11.25 [95% CI = 3.46–36.52]) and (AOR, 10.34 [95% CI = 2.90–36.90]) respectively. Higher areas of low density muscle was also associated with increased odds of TNBC (AOR, 3.15 [95% CI = 1.05–10.98]). Compared to normal body composition (low adipose tissue/high muscle), high adiposity/high muscle was associated with higher odds of TNBC (AOR, 5.54 [95% CI = 2.12–14.7]). These associations were mainly in premenopausal women and among patients with the CT performed after breast cancer surgery. Specific adipose tissue and low-density muscle can be associated with the TNBC subtype in breast cancer patients. The direction of association warrants confirmation by prospective studies.
Precision-Cut Tumor Slices (PCTS) as an Ex Vivo Model in Immunotherapy Research

Precision-cut tumor slices (PCTS) have recently emerged as important ex vivo human tumor models, offering the opportunity to study individual patient responses to targeted immunotherapies, including CAR-T cell therapies. In this review, an outline of different human tumor models available in laboratory settings is provided, with a focus on the unique characteristics of PCTS. Standard PCTS generation and maintenance procedures are outlined, followed by an in-depth overview of PCTS utilization in preclinical research aiming to better understand the unique functional characteristics of cytotoxic T cells within human tumors. Furthermore, recent studies using PCTS as an ex vivo model for predicting patient responses to immunotherapies and other targeted therapies against solid tumors are thoroughly presented. Finally, the advantages and limitations of the PCTS models are discussed. PCTS are expected to gain momentum and be fully utilized as a significant tool towards better patient stratification and personalized medicine.
Effect of Using Raw and Treated Quinoa Seeds (Chenopodium Quinoa) in the Diets on Oxidation Indicators of Broiler Carcass

The experiment aimed to study the use of different proportions of raw and treated Chenopodium quinoa seeds by soaking in the diet to identify the effect on the oxidation indicators of the meat stored for 2, 4, and 6 weeks. In the experiment, 336 sexed broilers (Ross308) were used at the age of one day, with an average initial weight of 39 g/chick. The chicks were fed on a starter diet (1-14 days) and the finisher diet including the initial grower diet (15-28 days) and second grower diet (29-42 days). Chicks were randomly distributed to seven treatments (8 males + 8 females/replicate), while the raw quinoa seeds were added at 0, 0.5, 1, and 1.5% for treatments T1, T2, T3, and T4, and the treated by soaked in water for 48 hours for treatments T5, T6 and T7 % feed, respectively. The results showed a significant decrease (P<0.05) in the values of Thiobarbituric Acid (TBA), Peroxide Value (PV), and Free Fatty Acids (FFA) for the meat of all treatments using raw and treated quinoa seeds compared to the control treatment and for all storage periods of 2, 4 and 6 weeks. The current study results showed that all concentrations of raw and treated quinoa seeds contributed to reducing the exposure of meat to rancidity and preserving it from oxidation during different storage periods. Besides, enhancing the possibility of storing it for long periods.
Personalized Online Learning, Test Fairness, and Educational Measurement: Considering Differential Content Exposure Prior to a High Stakes End of Course Exam

ABSTRACT According to the Standards for Educational and Psychological Testing (2014), one aspect of test fairness concerns examinees having comparable opportunities to learn prior to taking tests. Meanwhile, many researchers are developing platforms enhanced by artificial intelligence (AI) that can personalize curriculum to individual student needs. This leads to a larger overarching question: When personalized learning leads to students having differential exposure to curriculum throughout the K-12 school year, how might this affect test fairness with respect to summative, end-of-year high-stakes tests? As a first step, we traced the differences in content exposure associated with personalized learning and more traditional learning paths. To better understand the implications of differences in content coverage, we conducted a simulation study to evaluate the degree to which curriculum exposure varied across students in a particular AI-enhanced learning platform for Algebra instruction with high-school students. Results indicate that AI-enhanced personalized learning may pose threats to test fairness as opportunity-to-learn on K-12 summative high-stakes tests. We discuss the implications given different perspectives of the role of testing in education
Sm-CeO2/Zeolite Bifunctional Catalyst for Direct and Highly Selective Conversion of Bioethanol to Propylene

A series of Sm-CeO2/Beta composites with various Beta contents were prepared by an incipient impregnation method, followed by calcination at 650 °C. They were characterized by XRD, N2 adsorption, SEM, NH3-TPD, CO2-TPD and 27Al MAS NMR. The Sm-CeO2/Beta bifunctional catalysts exhibit eminent catalytic performances in the selective conversion of ethanol to propylene. In particular, the Sm-CeO2/10%Beta catalyst with 10% Beta zeolite gives the highest C3H6 yield of 59.3%. A good match between Sm-CeO2 and Beta accounts for its optimal result.
Words are monuments: Patterns in US national park place names perpetuate settler colonial mythologies including white supremacy

1. Ecologists, outdoor professionals and the public work and play in lands with complex histories. Part of decolonizing our professional and recreational prac - tices is to expose settler colonial biases and recognize the histories of colonized lands and the peoples who have stewarded these lands for millennia prior to colonization. 2. To provide a
Does attending an English private school benefit mental health and life satisfaction? From adolescence to adulthood

ABSTRACT Previous research has shown that there is a small but significant cumulative private school advantage in terms of educational attainment in Britain. However, research on how school type influences non-educational outcomes is more scarcer. This paper aims to identify the extent to which school type influences satisfaction with life and mental health from adolescence to early adulthood. Using Next Steps, a longitudinal study of young people in England born in 1989/90, the authors use multiple variable regression analyses to address the research questions. They find that for this cohort there is no evidence of a difference for mental health and life satisfaction by school type for either men or women in adolescence or early adulthood.
Development of an automated gait analysis tool

Development of an Automated Gait Analysis Tool Elham Dolatabadi Doctor of Philosophy Institute of Biomaterials and Biomedical Engineering University of Toronto 2016 Gait analysis involves the measurement of quantities that characterize human locomotion. This type of analysis helps clinicians detect gait disorder and therefore implement necessary therapeutic interventions. However, clinicians have been faced with numerous difficulties such as high dimensionality and nonlinear time dependencies among measured gait parameters. Moreover, the existing analysis of gait is compounded by long recording times in gait laboratories and delayed diagnosis of disorder. An effective analysis of gait could be facilitated if technology enabled frequent assessment in the home or in any clinic, i.e., without the need to visit a specialized gait clinic. The major goal of this thesis is therefore to investigate the use of easyto-use sensing devices for home use, as well as novel algorithms capable of processing sensed data, e.g., machine learning methods to automatically analyze gait data. This thesis consists of four different studies toward addressing our major goal. In the first study, we examined the applicability of the Microsoft Kinect sensor as an affordable, portable and easy to use sensing technology for long-term monitoring of mobility after an orthopaedic surgical procedure. This study provided reasonable outcomes that confirmed using a single Kinect sensor for a gait and movement analysis. In the second study, we investigated the validity and reliability of the Kinect sensor for spatiotemporal gait analysis in clinical settings. The results presented in this study indicated that the Kinect sensor along with its tracking algorithm and our custom made algorithms provide excellent validity when compared to gait measures obtained from a pressure mat. In the third study, we explored the use of an unsupervised machine learning technique to separate individuals with gait disorder into homogenous groups based on selected spatiotemporal gait measures. Unsupervised learning methods for gait analysis have been shown to be very successful in (1) grouping the gait patterns with similar characteristics, and (2) generating a composite measure indicative of overall gait performance and sensitive to improvement or de-
Mediating Effect of Digital Marketing Capability on Marketing Effectiveness of Community Enterprises in Nakhon Pathom Province, Thailand

Most community enterprises in Thailand are not successful because of limited marketing channels and technology. The purpose of this paper is to examine the effect of platform capability and web capability on marketing effectiveness with a consideration of the mediating effect of digital marketing capability to community enterprises in Nakhon Pathom Province, Thailand. The study uses a multi-stage sampling method surveying 400 community enterprise members in Nakhon Pathom Province. The model applies and combines the concepts of dynamic capability. Data analysis uses structural equation modelling and the LISREL program for path analysis and testing the congruence of the causal relationship model. The causal model of factors influencing marketing effectiveness significantly fits the empirical data. The fit statistics are c2= 349.046, df = 245, p-value = 0.158, c2/df = 1.425, RMSEA = 0.024, NFI = 0.996, NNFI = 0.998, CFI = 0.996, RMR = 0.024, SRMR = 0.024, GFI = 0.933 and AGFI = 0.910. The results show that digital marketing is a full mediating effect of platform and web capabilities on marketing effectiveness of community enterprises. Community enterprises need to implement more online marketing channels for better performances. Moreover, the study serves as a guideline for developing community enterprises and the capability level of grassroots, which are a significant base of local economic development of Thailand. Importantly, grassroots development has been a national agenda of the Thai government. Keywords: Community enterprise, mediating effect, dynamic capability, marketing effectiveness, digital marketing.
A novel CAPTCHA solver framework using deep skipping Convolutional Neural Networks

A Completely Automated Public Turing Test to tell Computers and Humans Apart (CAPTCHA) is used in web systems to secure authentication purposes; it may break using Optical Character Recognition (OCR) type methods. CAPTCHA breakers make web systems highly insecure. However, several techniques to break CAPTCHA suggest CAPTCHA designers about their designed CAPTCHA’s need improvement to prevent computer vision-based malicious attacks. This research primarily used deep learning methods to break state-of-the-art CAPTCHA codes; however, the validation scheme and conventional Convolutional Neural Network (CNN) design still need more confident validation and multi-aspect covering feature schemes. Several public datasets are available of text-based CAPTCHa, including Kaggle and other dataset repositories where self-generation of CAPTCHA datasets are available. The previous studies are dataset-specific only and cannot perform well on other CAPTCHA’s. Therefore, the proposed study uses two publicly available datasets of 4- and 5-character text-based CAPTCHA images to propose a CAPTCHA solver. Furthermore, the proposed study used a skip-connection-based CNN model to solve a CAPTCHA. The proposed research employed 5-folds on data that delivers 10 different CNN models on two datasets with promising results compared to the other studies.
The effect of social media on social capital and life-satisfaction in the case of college sports

ABSTRACT The growing use of social media has resonated with scholars to examine the role of social media in society. Given that sports are an integral part of American society, it is imperative to ask how the use of social media for sports is associated with individuals’ lives. In an attempt to answer this question, the current study employs the concept of social identification and social capital as a theoretical framework. Using survey data collected in the domain of college sports, the path analysis demonstrates the interlinked relationships between the use of social media, social capital, identification, and life satisfaction. Particularly, it is noteworthy that the use of social media is positively related to the production of social capital and life satisfaction both directly and indirectly through identification. Theoretical and practical implications are discussed.
The Relationship between Pregnancy Intention, Pregnancy Outcomes, Postpartum Depression, and Maternal Role Adaptation

Introduction: Unplanned pregnancy and its complications are a global problem that affects women, families, and the community. Objective: This study aimed to assess the relationship between pregnancy intention, pregnancy outcomes, postpartum depression, and maternal role adaptation in pregnant women referred to healthcare centers of Robat Karim City, Iran. Materials and Methods: This cohort study was conducted on 240 pregnant women referred to the healthcare centers of Robat Karim in 2019. They were selected by the convenience sampling method. After completing the London questionnaire in the 26th week of gestation, the participants were equally divided into planned and unplanned pregnancy groups. Edinburgh postnatal depression scale and parenting sense of competency scale were completed 10 days and 30 days after delivery. The obtained data were presented by descriptive statistics and analyzed by the Chi-square and t test for comparison between two groups and structural equation model for assessing the relationship between variables. Results: The mean ± SD values of age, marital duration time, and gravidity number of participants were 30±7.1, 1.5±0.02, and 5, respectively. The results revealed a significant difference between the two groups concerning the mean score of postpartum depression and maternal competency, 10 and 30 days after delivery (P=0.001). The results of path analysis showed that pregnancy intention had a negative and significant effect on postpartum depression (B = -0.58, t value=-2.5), but a positive and significant impact on maternal competency (B = 0.39, t value=-2). According to the determined amount of variance, the variable of intention to pregnancy predicts 33% of postpartum depression (R2=0.33). Also, two variables of pregnancy intention and postpartum depression predict 55% of maternal competency (R2=0.55). Conclusion: Pregnancy intention had a significant effect on maternal depression and competency. It is recommended that pregnancy intention be screened during pregnancy, and also appropriate training and social support be provided for mothers with unplanned pregnancies.
SEISMIC RETROFIT OF EXISTING BUILDINGS THROUGH THE DISSIPATIVE COLUMNS

A new replaceable hysteretic damper to better control seismic building damage, consisting of two or more adjacent steel vertical elements (columns) connected to each other with continuous mild/low strength steel shear links, is investigated in this study. New Dam-pers, called Dissipative Columns (DC), are continuously linked with X-shaped steel plates and provide additional stiffness and damping to a lateral system. The Dissipative Column has been conceived as a device installed within a frame or as an external damper to provide ma-cro-dissipation. In fact, considering different configurations, a parametric analysis is devel-oped, through non-linear pushover and cyclic analyses carried out in ABAQUS, in order both to evaluate the effect of the main geometrical and structural parameters and provide the de-sign capacity curves of this new damper. Moreover, non linear dynamic analyses of an exist-ing building without and with the Dissipative Columns have been performed in SAP2000 in order to evaluate the supplemental damping provided by the new damper. The DC can be considered a new damping device, easy to install in new as well as existing buildings in order to protect them from seismic damage.
Casing Coupling for Extreme Temperature Setting

The next leap in utilization of geothermal energy for electricity production might comprise of drilling deep wells down to the roots of geothermal reservoirs. Near these roots fluid at very high temperature and even at supercritical conditions can be accessed. Extraction of such fluid from natural reservoirs can if some obstacles can be conquered revolve geothermal utilization and electricity production. To allow deep geothermal wells to become a viable option a comprehensive research has to be carried out to eliminate all uncertainty regarding the resource. Furthermore the technical challenges which developers face on all stages from drilling and extraction to production have to be solved. One of the most essential parts of a geothermal well is the casing, string of pipes which ensure the structural integrity of a well and seal the well from unwanted fluids from the geothermal reservoir. Successful casing design and installation increases the longevity of a well, while design or installation faults can render a well inoperable or be the cause of high maintenance cost. It has been identified that deep geothermal wells will test a casing string performance further than conventional wells and if deep geothermal wells are to be a feasible option the casing design has to be resilient and reliable. This thesis reviews two threaded casing connection options proposed for extreme temperature settings and aims to answer which if any of examined options are best suited for deep wells of the future using finite element analysis. Assumptions made for the research are to some extent based on the Iceland Deep Drilling Project (IDDP). The results indicate that conventional threaded options can’t be recommended for examined conditions and premium connections with metal to metal sealing surface have no advantages over conventional connections under inspected loads. The results do not highlight any advantages of upgrading the casing to a higher grade material according to API 5CT standard.
Feelings of Loneliness due to COVID‑19 Pandemic’s Home Confinement/ Quarantine and its Relationship with Anxiety Traits and Empathy

Introduction: We aimed to understand how loneliness and empathy relate to home confinement/quarantine and to explore the relation between loneliness, anxiety traits and empathy. Methods: This is an observational cross‑sectional cohort study including 364 participants. We delivered an online questionnaire composed by UCLA Loneliness scale (assessing loneliness), STAI‑Y (assessing trait anxiety), and IRI (assessing empathy). For the statistical analysis we performed descriptive and inferential statistics. When not‑otherwise specified, two‑tailed p<0.05 was considered significant. Results: The mean for IRI was 60.46 (SD: 10.88), for UCLA Loneliness scale was 32.70 (SD: 8.11) and for STAI‑Y was 42.01 (SD: 12.29). We found no statistically significant correlation between empathy and loneliness (p>0.05). Nonetheless, loneliness and anxiety traits were positively correlated (p<0.05), and psychiatric comorbidity was associated with higher levels of loneliness and anxiety traits (p<0.05). Conclusion: Our results suggest social cohesion, solidarity and continuous online contact may have played a significant role on preservation of empathy and feelings of loneliness. The fact that loneliness may be felt in a positive way (such tightening household relationships) can explain the non‑correlationbetween the last and empathy. Ultimately, the positive correlation between anxiety traits and loneliness underlines the vulnerability of previously anxious subjects, enhancing the importance of promoting mental health during the pandemic.