Miracle-dz/UniFAR-FTUs huggingface dataset:
A Search for Transit Effects in Spectra of 51 Pegasi and HD 209458

We have used high‐resolution optical spectra to search for obvious absorption or emission lines from the planets orbiting HD 209458 and 51 Pegasi. For each star, two spectra were obtained during inferior conjunction, enabling the detection of absorption lines from the planetary atmosphere. Spectra were also examined at a full range of orbital phases. The search involved subtracting spectra during transit from reference spectra taken out of transit. We found no significant variations in the spectra of HD 209458 and 51 Peg at any orbital phase, with typical detection thresholds of several percent. Velocity measurements of HD 209458 taken 40 minutes after midtransit fall ∼20 m s−1 below the Keplerian fit, presumably due to the planet removing flux from the receding hemisphere of the rotating stellar surface. This is consistent with the planet orbiting in the same direction as the star spins, in agreement with recent work by D. Queloz and coworkers.
Effects of feeding CLOSTAT (Bacillus subtilis PB6) on the clinical health, performance, and carcass characteristics of feedlot steers1

Abstract The objectives of this experiment were to evaluate the effects of feeding Bacillus subtilis PB6 on clinical health, performance, and carcass characteristics of feedlot steers. Bos indicus crossbred steer calves (n = 397; 342 kg initial body weight [BW]) were randomly assigned to pens by initial BW; pens (n = 24) were randomly assigned to one of two of the following experimental treatments: 1) no supplemental dietary direct-fed microbial, control (CON; n = 12 pens) or 2) 13 g/steer daily B. subtilis PB6 (CLO; CLOSTAT, Kemin Industries, Des Moines, IA; n = 12 pens). Steers were housed in 12.2 × 30.5 m soil-surfaced pens; pen served as the experimental unit. The percentage of cattle treated once or twice for bovine respiratory disease (BRD) did not differ among treatments (P ≥ 0.27); BRD mortality also did not differ between CON and CLO (P = 0.34). During the receiving period, final BW (P = 0.97), average daily gain (ADG; P = 0.91), dry matter intake (DMI; P = 0.77), and gain:feed (P = 0.79) were not different among treatments. There was a tendency (P = 0.09) for CLO-supplemented steers to be 14% more efficient from days 0 to 14 of the receiving period. Final BW, overall finishing phase ADG, and DMI did not differ by treatment (P ≥ 0.14); ADG was 0.14 kg greater for CLO than CON (P = 0.03) from days 29 to 56 of the finishing period. Gain: feed tended (P = 0.07) to be 7% greater (0.144 vs. 0.141) for CLO than CON throughout the duration of the finishing period, and 6.7% greater (P = 0.08; 0.152 for CLO vs. 0.150 for CON) for the entirety of the experiment. Carcass traits did not differ among treatments (P ≥ 0.31). The results of this experiment suggest that supplementing 13 g/steer daily B. subtilis PB6 may improve feed efficiency in feedlot cattle.
Assembly & Sequence

Assembly & Sequence was a ARC 500 Selected Topics seminar taught during the Spring of 2019 at the Syracuse University School of Architecture. This course is a hybrid integrating architectural design, process, theory, and representation. The course was an experiment in the methodology of disintegrated design. We embraced the idea of a building as a collection of autonomous parts and examined their integration as a whole. The course was structured around a series of exercises progressing in scale. The course consisted of three primary design exercises, each building upon the last culminating in a team architectural project. After each exercise students were required to ‘pass’ there work on to other students and were not allowed to use what they produced from the previous exercise. The course was initiated by an interest in early Dada and Surrealist ideas. Dadaism was born and created in response to the atrocities of World War I. The Dadaists believed the war was a result of the celebrated and unchecked embrace of progress and rationalism. In response, their art was to be antirational, embraced chance and happenstance. In other words, there work needed no reason or understanding. Rationale and reason has become a dominant approach to architectural design education, where students are asked to produce proofs, arguments and construct complex rationalizations of their work. This course aimed to follow the Dadaist approach by creating a pedagogy that would release students from all logical and critical defense of their work.
Potential moderators and mediators of intervention effects in a sport-based mental health literacy and resilience program for adolescent men

Abstract Engaging young men in mental health promotion initiatives is important given the negative attitudes toward mental health and increased suicide rates, reported by young men. Ahead of the Game (AOTG) is a sport-based, psychoeducational initiative which uses sports as a mental health and resilience promotional medium. This study sought contribute to the literature on the effectiveness of the AOTG program by exploring for whom, and through what mechanisms, the intervention works. A secondary analysis of the AOTG randomized controlled trial was conducted, which comprised a sample of 350 adolescent male sport-playing participants (M = 14.53 years, SD = 1.19 years) and control group of 466 sport participants (M = 14.66 years, SD = 1.39), various mental health related measures were taken at baseline and at approximately 8 weeks follow-up. Moderation analyses were conducted to examine age, socioeconomic status, and baseline measures of mental health as potential moderators of program effects. Mediation analyses were run to explore whether changes in psychological distress and wellbeing were mediated by changes in AOTG’s various primary mental health related outcomes. Results indicated age did not moderate any effects of AOTG. Meanwhile, socioeconomic status and baseline help seeking, implicit beliefs, and psychological distress all showed signs of moderating main effects of AOTG. Mediation analyses revealed that changes in resilience and implicit beliefs partially mediated changes in psychological distress. Further, increased resilience had an indirect effect of on athletes’ wellbeing. The implications and future directions, in light of these findings, are explored. Lay summary: Ahead of the Game was shown to be effective regardless of age and particularly beneficial for those in low socioeconomic, displaying low levels of help seeking, and those with higher psychological distress. Increasing resilience was also shown to be an important pathway for increasing wellbeing and reducing distress. IMPLICATIONS FOR PRACTICE Increasing resilience is an important pathway through which mental health promotion and prevention programs may promote well-being and reduce distress Mental health knowledge prior to the delivery of mental health literacy does not appear to effect program effectiveness Athletes aged from 12 to 18 years of age may benefit similarly from the same mental health promotion and prevention programs
Privacy Concerns Matter, Knowledge Does Not: Investigating Effects of Online Behavioral Advertising among Chinese and Dutch Adults

Abstract The present study aims to address (1) the extent to which privacy concerns and online behavioral advertising (OBA) knowledge as consumer characteristics create boundary conditions for the persuasiveness of OBA and (2) if their roles in OBA effects differ for Dutch and Chinese individuals. Results from an online experiment (N = 241) show that OBA is less effective for individuals with high privacy concerns than for individuals with low privacy concerns, while level of OBA knowledge does not influence the positive effects of OBA compared to non-OBA. OBA is also more effective for Dutch consumers than for Chinese consumers, which could be attributed to the finding that Chinese consumers have higher privacy concerns than Dutch consumers.
Diversity of Antimicrobial Peptides in Silkworm

Antimicrobial resistance is a phenomenon that the present-day world is witnessing that poses a serious threat to global health. The decline in the development of novel therapeutics over the last couple of decades has exacerbated the situation further. In this scenario, the pursuit of new alternative therapeutics to commonly used antibiotics has gained predominance amongst researchers across the world. Antimicrobial peptides (AMPs) from natural sources have drawn significant interest in the recent years as promising pharmacological substitutes over the conventional antibiotics. The most notable advantage of AMPs is that microorganisms cannot develop resistance to them. Insects represent one of the potential sources of AMPs, which are synthesized as part of an innate immune defence against invading pathogens. AMPs from different insects have been extensively studied, and silkworm is one of them. Diverse classes of AMPs (including attacins, cecropins, defensins, enbocins, gloverins, lebocins and moricins) were identified from silkworm that exhibit antimicrobial property against bacteria, fungi and viruses, indicating their potential therapeutic benefits. This review briefs about the immune responses of silkworm to invading pathogens, the isolation of AMPs from silkworms, AMPs reported in silkworms and their activity against various microorganisms.
Partnering with First Nations in Northern British Columbia Canada to Reduce Inequity in Access to Genomic Research

Indigenous-led, culturally safe health research and infrastructure are essential to address existing inequities and disparities for Indigenous Peoples globally. Biobanking, genomic research, and self-governance could reduce the existing divide and increase Indigenous participation in health research. While genomic research advances medicine, barriers persist for Indigenous patients to benefit. In northern BC, Canada, the Northern Biobank Initiative (NBI), with guidance from a Northern First Nations Biobank Advisory Committee (NFNBAC), has engaged in consultations with First Nations on biobanking and genomic research. Key informant interviews and focus groups conducted with First Nations leaders, Elders, Knowledge Keepers, and community members established culturally safe ways of biobanking and exploring genomic research. Strong support for a Northern British Columbia First Nations Biobank (NBCFNB) that will promote choice, inclusion, and access to health research opportunities emerged. The acceptance and enthusiasm for the development of this NBCFNB and its governance table highlight the shift towards Indigenous ownership and support of health research and its benefits. With engagement and partnership, community awareness, multigenerational involvement, and support from diverse and experienced healthcare leaders, the NBCFNB will establish this culturally safe, locally driven, and critically important research priority that may serve as an example for diverse Indigenous groups when designing their unique biobanking or genomic research opportunities.
Time Scales of Clouds and Cloud-Controlling Variables in Subtropical Stratocumulus from a Lagrangian Perspective

AbstractThe Lagrangian evolution of cloud cover and cloud-controlling variables is well approximated using red noise processes with different autocorrelation time scales for each variable. Trajectories within the subtropical marine boundary layer are generated using winds from ECMWF Re-Analysis data for low cloud decks in four eastern subtropical ocean basins. Cloud cover, liquid water path, and boundary layer depth are sampled at 12-h intervals using A-Train satellites, and droplet concentration is sampled every 24 h. Lower-tropospheric stability and vertical velocity are sampled concurrently using reanalysis data. Samples are converted to seasonal and diurnal anomalies. Data are spatially averaged over a range of length scales. The e-folding decay times τ for autocorrelation are calculated for each variable based on lag times of 12, 24, 36, and 48 h. Using lag 24 h and an averaging radius of 100 km, τ ≈ 15–17 h for liquid water path and vertical velocity, τ ≈ 19 h for cloud cover, τ ≈ 24–25 h for bounda.
In Silico Identification and Analysis of Potentially Bioactive Antiviral Phytochemicals against SARS-CoV-2: A Molecular Docking and Dynamics Simulation Approach

SARS-CoV-2, a deadly coronavirus sparked COVID-19 pandemic around the globe. With an increased mutation rate, this infectious agent is highly transmissible inducing an escalated rate of infections and death everywhere. Hence, the discovery of a viable antiviral therapy option is urgent. Computational approaches have offered a revolutionary framework to identify novel antimicrobial treatment regimens and allow a quicker, cost-effective, and productive conversion into the health center by evaluating preliminary and safety investigations. The primary purpose of this research was to find plausible plant-derived antiviral small molecules to halt the viral entrance into individuals by clogging the adherence of Spike protein with human ACE2 receptor and to suppress their genome replication by obstructing the activity of Nsp3 (Nonstructural protein 3) and 3CLpro (main protease). An in-house library of 1163 phytochemicals were selected from the NPASS and PubChem databases for downstream analysis. Preliminary analysis with SwissADME and pkCSM revealed 149 finest small molecules from the large dataset. Virtual screening using the molecular docking scoring and the MM-GBSA data analysis revealed that three candidate ligands CHEMBL503 (Lovastatin), CHEMBL490355 (Sulfuretin), and CHEMBL4216332 (Grayanoside A) successfully formed docked complex within the active site of human ACE2 receptor, Nsp3, and 3CLpro, respectively. Dual method molecular dynamics (MD) simulation and post-MD MM-GBSA further confirmed efficient binding and stable interaction between the ligands and target proteins. Furthermore, biological activity spectra and molecular target analysis revealed that all three preselected phytochemicals were biologically active and safe for human use. Throughout the adopted methodology, all three therapeutic candidates significantly outperformed the control drugs (Molnupiravir and Paxlovid). Finally, our research implies that these SARS-CoV-2 protein antagonists might be viable therapeutic options. At the same time, enough wet lab evaluations would be needed to ensure the therapeutic potency of the recommended drug candidates for SARS-CoV-2.
Ondelettes Quaternioniques pour la Classification de Textures

This paper proposes a new texture classiﬁer based on the Quaternionic Wavelet Transform (QWT). This recent transform separates the informations contained in the image better than a classical wavelet transform (DWT), and provides a multiscale image analysis which coefﬁcients are 2D analytic, with one near-shift invariant magnitude and a phase, that is made of three angles. The interpretation and use of the QWT coefﬁcients, especially the phase, are discussed, and we present a texture classiﬁer using both the QWT magnitude and the QWT phase of images. Our classiﬁer performs a better recognition rate than a standard wavelet based classiﬁer.
Development of a Metabolic Syndrome Classification and Prediction Model for Koreans Using Deep Learning Technology: The Korea National Health and Nutrition Examination Survey (KNHANES) (2013–2018)

The prevalence of metabolic syndrome (MetS) and its cost are increasing due to lifestyle changes and aging. This study aimed to develop a deep neural network model for prediction and classification of MetS according to nutrient intake and other MetS-related factors. This study included 17,848 individuals aged 40–69 years from the Korea National Health and Nutrition Examination Survey (2013–2018). We set MetS (3–5 risk factors present) as the dependent variable and 52 MetS-related factors and nutrient intake variables as independent variables in a regression analysis. The analysis compared and analyzed model accuracy, precision and recall by conventional logistic regression, machine learning-based logistic regression and deep learning. The accuracy of train data was 81.2089, and the accuracy of test data was 81.1485 in a MetS classification and prediction model developed in this study. These accuracies were higher than those obtained by conventional logistic regression or machine learning-based logistic regression. Precision, recall, and F1-score also showed the high accuracy in the deep learning model. Blood alanine aminotransferase (β = 12.2035) level showed the highest regression coefficient followed by blood aspartate aminotransferase (β = 11.771) level, waist circumference (β = 10.8555), body mass index (β = 10.3842), and blood glycated hemoglobin (β = 10.1802) level. Fats (cholesterol [β = −2.0545] and saturated fatty acid [β = −2.0483]) showed high regression coefficients among nutrient intakes. The deep learning model for classification and prediction on MetS showed a higher accuracy than conventional logistic regression or machine learning-based logistic regression.
Social Learning for Sequential Driving Dilemmas

Autonomous driving (AV) technology has elicited discussion on social dilemmas where trade-offs between individual preferences, social norms, and collective interests may impact road safety and efficiency. In this study, we aim to identify whether social dilemmas exist in AVs’ sequential decision making, which we call “sequential driving dilemmas” (SDDs). Identifying SDDs in traffic scenarios can help policymakers and AV manufacturers better understand under what circumstances SDDs arise and how to design rewards that incentivize AVs to avoid SDDs, ultimately benefiting society as a whole. To achieve this, we leverage a social learning framework, where AVs learn through interactions with random opponents, to analyze their policy learning when facing SDDs. We conduct numerical experiments on two fundamental traffic scenarios: an unsignalized intersection and a highway. We find that SDDs exist for AVs at intersections, but not on highways.
Period Decompositions for the Capacity Constrained Lot Size Problem with Setup Times

We study the Capacity Constrained Lot Size Problem with Setup Times (CLST). Based on two strong reformulations of the problem, we present a transformed reformulation and valid inequalities that speed up column generation and Lagrange relaxation. We demonstrate computationally how both ideas enhance the performance of our algorithm and show theoretically how they are related to dual space reduction techniques. We compare several solution methods, and propose a new efficient hybrid scheme that combines column generation and Lagrange relaxation in a novel way. Computational experiments show that the proposed solution method for finding lower bounds is competitive with other state-of-the-art approaches found in the literature. Finally, a branch-and-price based heuristic is designed and computational results are reported. The heuristic scheme compares favorably or outperforms similar approaches. Resume : Nous etudions un probleme de planification de production avec des contraintes de capacite et des temps de mise en route. En nous basant sur deux reformulations fortes du probleme, nous presentons une reformulation transformee et des inegalites valides qui accelerent la generation des colonnes et le processus de la relaxation Lagrangienne. Nous presentons des resultats qui indiquent que ces idees ameliorent la performance de nos algorithmes et nous demontrons d’une facon theorique comment ces idees sont liees aux techniques de reduction de l’espace dual. Nous comparons plusieurs methodes de resolution, et proposons une nouvelle approche hybride efficace. Les resultats indiquent que la methode pour trouver des bornes inferieures est competitive avec d’autres approches dans la litterature. Finalement, une nouvelle approche heuristique est proposee et nous rapportons des resultats favorables. Les Cahiers du GERAD G–2013–76 1
Research of fuzzy control for double inverted pendulum

The inverted pendulum is a multivariable,nonlinear,strong-complying control system. The fuzzy control theory is introduced to study the controlling problem of the double inverted pendulum in this paper.The dimensions of input vari- eties of a fuzzy controller are depressed by designing a fusion function using the optimization control theory,and it reduces the rules of fuzzy control. Theory and experiment prove that this fuzzy control arithmetic is effective and feasible.
Cycles and Harmonic Forms on Locally Symmetric Spaces

Abstract Two constructions of cohomology classes for congruence subgroups of unit groups of quadratic forms over totally real number fields are given and shown to coincide. One is geometric, using cycles, and the other is analytic, using the oscillator (Weil) representation. Considerable background material on this representation is given.
SIMULATION OF HORIZONTAL TWO-PHASE SLUG FLOWS USING THE TWO-FLUID MODEL WITH A CONSERVATIVE AND NON- CONSERVATIVE FORMULATION

The two-fluid model has been widely used on the simulation of two-phase flows in pipelines. The model consists of two sets of conservation equations - mass and linear momentum - for the liquid and gas phases on its transient, one-dimensional form. The "slug capturing methodology" involves the numerical solution of the equations using a finite volume formulation, which is capable of naturally predicting the onset of slugging from stratified flow regime, as well as the growth and collapse of the slugs. When a slug is formed the gas volume fraction is zero, and as a result the gas momentum equation becomes singular. A non-conservative and a conservative approach were employed to handle the problem. Although the non-conservative approach is more stable, it is also too dissipative.
Protecting Modbus/TCP-Based Industrial Automation and Control Systems Using Message Authentication Codes

Critical infrastructure (CI), such as energy and water distribution systems, is essential for the stability and well-being of the modern society. Industrial automation and control systems (IACSs) form the backbone of CIs and enable the operation of such systems in a safe and reliable manner. However, with the increasing use of industrial Ethernet communication protocols, such as Modbus-over-TCP (Modbus/TCP), once air-gapped IACSs are becoming vulnerable to potential cybersecurity threats. This paper presents a novel method for enhancing the cybersecurity of Modbus/TCP-based IACSs by implementing an authentication method based on message authentication codes (MACs). To provide partial protection of communication even when communicating with legacy Modbus/TCP peers, we propose a novel supervising device that analyzes exchanged messages and verifies the authenticity of the protected messages. To experimentally verify the protection method, a water-treatment cyber-physical system (CPS) was implemented as a digital twin in a programmable logic controller (PLC). The underlying MAC is the Chaskey-12, lightweight MAC defined in IEC 29192-6. It was implemented in the PLC program using the programming languages defined in IEC 61131-3. As an additional contribution, the presented implementation allows protection of communication between PLCs and other Modbus/TCP peers installed in existing IACSs without hardware or firmware modifications. The results show that the method provides protection against network attacks without significantly affecting performance, also demonstrating the feasibility of such protection in IACSs.