Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting Bladerow Interactions Using a Multistage Time-Linearized Navier-Stokes Solver

A multistage frequency domain (time-linearized/nonlinear harmonic) Navier-Stokes unsteady flow solver has been developed for predicting unsteady flows induced by bladerow interactions. In this paper, the time-linearized option of the salver has been used to analyze unsteady flows in a subsonic turbine test stage and the DLR transonic counterrotating shrouded propfan. The numerical accuracy and computational efficiency of the time-linearized viscous methods have been demonstrated by comparing predictions with test data and nonlinear time-marching solutions for these two test cases. It is concluded that the development of efficient frequency domain approaches enables unsteady flow predictions to be used in the design cycles to tackle aeromechanics problems.
DP2Dataset Protection by Data Poisoning

Data poisoning can be served as an effective way to protect the dataset from surrogate training, whereby the performance of the surrogate model could be greatly influenced if trained with poisoned dataset. This paper focuses on an advanced scenario where the attacker might be an experienced malicious employee who has the white-box access to the dataset and black-box access (can only query) to original business model (e.g. MLaaS model). Under this condition, three main requirements must be satisfied: imperceptibility, robustness and stealthiness. In this paper, we propose a novel dataset protection method by data poisoning dubbed DP2 to meet the requirements. To achieve imperceptibility and robustness, we propose a poisoning mechanism which is conducted by a designed dual-U-Net-based poisoning network, by training with the reference mapping strategy and the corresponding noise layer, the imperceptibility and robustness can be both achieved. As for stealthiness, we propose a recover-net to eliminate the perturbation, so that the business model with black-box access could be an enclose version of the recover-net and the original business model. Besides, based on the recover-net, the poisoned dataset could be re-applied for the normal use. Various experiments indicate superior performance of the proposed scheme in the view of imperceptibility and robustness compared with other schemes. The solution which makes the poisoned data recoverable greatly ensures the stealthiness, and the derived recoverability of poisoned data could be utilized in other scenarios.
Maximum common subgraph isomorphism algorithms and their applications in molecular science: a review

The intuitive description of small and large molecules using graphs has led to an increasing interest in the application of graph concepts for describing, analyzing, and comparing small molecules as well as proteins. Graph theory is a well‐studied field and many applications are present in various scientific disciplines. Recent literature describes a number of successful applications to biological problems. One of the most applied concepts aims at finding a maximal common subgraph (MCS) isomorphism between two graphs. We review exact MCS algorithms, especially designed for graphs obtained from small and large molecules, and give an overview of their successful applications. © 2011 John Wiley & Sons, Ltd. WIREs Comput Mol Sci 2011 1 68–79 DOI: 10.1002/wcms.5
Measurements of polytropic index in the January 10–11, 1997 magnetic cloud observed by WIND

The polytropic index γ is a key parameter in the modeling of interplanetary magnetic clouds. In contrast to other models, the self‐similar model of Osherovich et al [1993a] suggested γ < 1 in clouds. The first measurements [Osherovich et al, 1993b] showed that γ ≈ γe = 0.4 ‐ 0.5 in magnetic clouds demonstrating the dominant role of electrons over protons (Te/Tp ≈ 6‐7 at 1 AU). For the January 10‐11, 1997 cloud observed by WIND, we found that the polytropric relation Te = FNeγe−1 is valid with γe = 0.52 ± 0.04 and F = 1.97 105 ± 0.12 105 (cgs units) over the number density range 1 < Ne < 10 cm−3. The constant F is half the value found for other clouds studied at 1 AU, while γe is essentially the same. We believe that the small value of F should be attributed to a later stage of the self‐similar evolution of this cloud as compared to other clouds studied previously at 1 AU.
Quality of relationship between adult children caregivers and parents with dementia

The main effects for associations between psychosocial stressors and caregiver outcomes are well established, but little is known about the mechanisms of these relationships. Aims of this study were to examine the hypotheses that satisfaction with family relationships (SF) is a mechanism by which quality of relationship (QR) between adult children caregiver and parents with Alzheimer’s disease (AD) influences depression, life satisfaction (LF), and self-rated health (SRH) among these caregivers. The participants were 716 Brazilian adult children who cared for their parents with AD and related disorders. Regression-based path analysis was performed; a PROCESS, bias-corrected and accelerated bootstrapping method was used to test confidence intervals. The relationships between QR and both depression (B = .3263, p < .001) and SRH (B = .3263, p < .001), were fully mediated by SF. The relationship between QR and LF was partially mediated by SF. The primary finding is that SF is one mechanism by which QR relates to depressive symptomatology, self-rated health, and life satisfaction.
Design, Synthesis, Molecular Docking and Antifungal Evaluation of Mixed Heterocyclic Moieties Containing Pyridine, 1,3,4-Oxadiazole and 1,2,3-Triazol Rings

In the current study, derivatives containing pyridine, 1,3,4-oxadiazole and 1,2,3-triazole heterocycles in their structures have been synthesized, 1,2,3-triazole moiety was synthesized using click chemistry, a powerful modular synthesis approach, and evaluated for in-vitro antifungal activity. When compared to the regular medicine Fluconazole, one derivative (5a) showed superior fungicidal action. Prior to synthesis, an in silico computational analysis was conducted to determine the binding interactions of these synthesized compounds in the active sites of the fungal enzyme sterol 14-demethylase (CYP51) through molecular docking via Genetic Optimization for Ligand Docking (GOLD) suite v.5. 6.2. Most of the tested compounds in molecular docking showed significant activities compared with fluconazole as reference compound due to their hydrogen bonding interaction with key amino acids in Sterol 14-demethylase enzyme Tyr116 and iron metal, and these results are compatible with their in vitro anti-fungal study.
Demystifying The Role Of Culture In Coaching Relationships

This capstone examines the role of culture and cross-cultural competence in coaching relationships. The business world is becoming increasingly globalized, with workers interacting across geographic and linguistic and cultural differences. In addition, many American companies are actively diversifying their leadership teams, which increases cultural differences in C-suites and beyond. These individuals need to develop significant cross-cultural competence in order to effectively engage with one another. Coaches working with these diverse and globalized companies need to both develop their own cultural competency and grow their expertise in coaching others to develop cultural competency. In this study I engaged in intensive coaching with two Asian–American women, reflected on each of the coaching sessions, and analyzed the content of the sessions as well as my reflections. My findings include the following: Aspects of a coach's culture influence how they perceive and engage with a client; aspects of a client's culture influence how they perceive and engage with a coach; clients and coaches make assumptions about each other based on a number of factors, including race; and the identities of coaches and clients are expressed and negotiated through stories. This capstone raises many interesting questions for future examination, including what strategies can be deployed beyond awareness of cultural differences and building more inclusive coaching models. Comments Submitted to the Program of Organizational Dynamics, College of Liberal and Professional Studies in the School of Arts and Sciences in Partial Fulfillment of the Requirements for the Degree of Master of Science in Organizational Dynamics at the University of Pennsylvania Advisor: Erek Ostrowski, PhD This thesis or dissertation is available at ScholarlyCommons: https://repository.upenn. edu/od_theses_msod/143 DEMYSTIFYING THE ROLE OF CULTURE IN COACHING RELATIONSHIPS
Systematic Analysis of a Pyroptosis-Related Signature to Predict the Prognosis and Immune Microenvironment of Lower-Grade Glioma

Current treatments for lower-grade glioma (LGG) do not effectively improve life expectancy rates, and this is a major global health concern. Improving our knowledge of this disease will ultimately help to improve prevention, accurate prognosis, and treatment strategies. Pyroptosis is an inflammatory form of regulated cell death, which plays an important role in tumor progression and occurrence. There is still a lack of effective markers to evaluate the prognosis of LGG patients. We collected paraffin-embedded tissue samples and prognostic information from 85 patients with low-grade gliomas and fabricated them into a tissue microarray. Combining data from public databases, we explored the relationship between pyroptosis-related genes (PRGs) and the prognoses of patients with LGG and investigated their correlations with the tumor microenvironment (TME) by means of machine learning, single-cell, immunohistochemical, nomogram, GSEA, and Cox regression analyses. We developed a six-gene PRG-based prognostic model, and the results have identified CASP4 as an effective marker for LGG prognosis predictions. Furthermore, the effects on immune cell infiltration may also provide guidance for future immunotherapy strategies.
Deep Learning for Knock Occurrence Prediction in SI Engines

This research aims to predict knock occurrences by deep learning using in-cylinder pressure history from experiments and to elucidate the period in pressure history that is most important for knock prediction. Supervised deep learning was conducted using in-cylinder pressure history as an input and the presence or absence of knock in each cycle as a label. The learning process was conducted with and without cost-sensitive approaches to examine the influence of an imbalance in the numbers of knock and non-knock cycles. Without the cost-sensitive approach, the prediction accuracy exceeded 90% and both the precision and the recall were about 70%. In addition, the trade-off between precision and recall could be controlled by adjusting the weights of knock and non-knock cycles in the cost-sensitive approach. Meanwhile, it was found that including the pressure history of the previous cycle did not influence the classification accuracy, suggesting little relationship between the combustion behavior of the previous cycle and knock occurrence in the following cycle. Moreover, learning the pressure history up to 10° CA before a knock improved the classification accuracy, whereas learning it within 10° CA before a knock did not noticeably affect the accuracy. Finally, deep learning was conducted using data, including multiple operating conditions. The present study revealed that deep learning can effectively predict knock occurrences using in-cylinder pressure history.
Computational study of multi-color InGaN/GaN nanowire LEDs with continuously varied indium composition

Gallium nitride based light emitting diodes have emerged as powerful devices which could replace incandescent and fluorescent lamps within the next years. The development of phosphor-free white LEDs is an ongoing field of research because of the lack of high efficiency green LEDs. A promising approach is the growth of InGaN/GaN nanowires with a continuously varied Indium content along the structure. The graded mole fraction profile is supposed to yield a multitude of emission colors due to many emission levels which can sum up to white light emission. The formation of strain and polarization charges is reduced because of the incremental varying lattice constants in combination with the facility of lateral relaxation of the wire. We report on the computational analysis of those nanowire structures in order to understand the electroluminescent behavior. The simulation software calculates the electrostatic potential and the carrier densities in the entire structure by solving the Poisson and the drift/diffusion equations in three dimensions. The luminescence is determined on the basis of a free carrier theory and enters the continuity equations as recombination term with strain and polarization effects included. This comprehensive physical model is employed to analyze carrier injection and luminescence for a white light-emitter design.
Prediction of speech privacy between rooms

The main purpose of sound insulation is usually to provide an appropriate level of speech privacy between rooms. However, the desired privacy is not always reached if, e.g. the background noise level of receiving room has not been considered or rooms are very small. This is often the case in dwellings and office rooms. Thus, sound reduction index does not correlate well with speech privacy. The aim of this study is to present a simple and validated model to predict the speech privacy between two arbitrary rooms when basic room and wall parameters are known. Speech privacy was described using Speech Transmission Index, STI. STI can be determined when the speech effort, room dimensions, early decay times of the rooms and background noise level of the reception room are known. The model was validated in several cases. The model is useful when economic optimization is appreciated. It can lead to major reductions or increments of conventional recommendations for Rw value, especially, when room dimensions are u.
Advances in antibody-drug conjugates for gynecologic malignancies

Purpose of review Antibody-drug conjugates (ADCs) represent a new class of drugs that combine a surface receptor-targeting antibody linked to a cytotoxic molecule delivering the potent cytotoxic payload directly to tumor cells. This review summarizes the current literature demonstrating their use in the treatment of gynecologic malignancies. Recent findings Tisotumab vedotin is the first U.S. Food and Drug Administration (FDA) approved ADC for the treatment of gynecologic cancers. While in the phase 3 randomized controlled trial in platinum resistant ovarian cancer patients, FORWARD 1, mirvetuximab did not meet its primary endpoint of progression-free survival. But we await more recent data from the two ongoing phase 3 trials of mirvetuximab in recurrent ovarian cancer patients. HER2/neu, Napi2b, mesothelin, and human trophoblast cell-surface marker (Trop-2) overexpression have also been exploited as excellent targets by novel ADCs in multiple tumors including ovarian, endometrial, and cervical cancers. Summary Current evidence strongly supports the use of ADCs and ongoing clinical trials will provide further information into the potential of making these drugs part of current standard practice allowing patients to be treated with a higher level of personalized cancer care.
Nearby Galaxy Flows Modeled by the Light Distribution

The observed distribution of light in the Local Supercluster has been used to determine the expected velocities of galaxies if the assumptions are valid that nonexpansion motions are generated by gravitational perturbations and that mass is distributed like the light. Since detailed knowledge of the light distribution extends to only 3000 km s −1 , three extra sources are added at large distances: one associated with the Great Attractor, one loosely with the Perseus-Pisces Supercluster region, and one with the Shapley Concentration at a distance corresponding to 13,800 km s −1
Recent Advances and Future Prospects of Molecular Imprinting Polymers as a Recognition Sensing System for Food Analysis: A Review

Molecular imprinting polymers (MIPs) have been widely used to produce stable polymeric materials due to their highly selective binding sites to determine the analyte (target molecule) in food products. MIPs begin with a complex compound between the template molecule and the functional monomers that can be polymerized when there is a closely crossed link. MIPs left specific cavities after the removal of templates during washing, which complements the size and shape of the templates. The use of MIPs has contributed to novel advances in materials science, polymer science, natural science, and other multi-disciplinary systems. Optical chemical sensor is an exciting field in MIPs today due to comprehend the unique affirmation limit of associated polymers giving stable polymers with high molecular recognition capabilities. MIPs display a wide extent of relevance, incredible flexibility, security, and high selectivity; their internal affirmation districts can be explicitly gotten together with design molecules to achieve specific affirmation. This review covers the various achievements of sensors used in laboratory analyses. The advancement in the development of MIPs is evaluated with an accentuation on the preparation principle, the discovery process, the molecular recognition mechanism and future perspectives and challenges for MIPs in building an optical chemical sensor.
Predefined-Time Adaptive Fuzzy Control for a Class of Nonlinear Systems With Output Hysteresis

The adaptive fuzzy predefined-time tracking control problem for a class of nonlinear systems with output hysteresis is investigated in this article. An inverse model is utilized to capture the output hysteresis phenomenon, and then, the Nussbaum-type function technique is utilized to overcome the difficulty of unknown time-varying control gain caused by output hysteresis. An adaptive fuzzy control scheme under the backstepping framework is developed using the predefined-time stability criterion. Different from the existing predefined-time design approaches, the adaptive law designed in this article is represented as a nonlinear differential equation. Theoretical analysis demonstrates that all signals of the closed-loop systems are bounded, and the tracking error can converge to the neighborhood near the origin within an expected settling time. The developed scheme's feasibility is verified by an example of an electromechanical system.
Ultrafast mid-infrared spectroscopy of the charge- and spin-ordered nickelates

We discuss the mid-infrared optical response of a charge and spin-ordered nickelate in the ultrafast time domain. A strong photo-induced modulation of the optical reflectivity is observed on the sub-picosecond timescale, indicating the transient filling and recovery of the pseudogap in the mid-infrared charge transport. A variational Kramers-Kronig analysis of equilibrium reflectivity data is extended to time-resolved experiments, allowing us to extract the optical conductivity despite a comparatively limited frequency range of tunable femtosecond parametric sources. The fast dynamics of the spectral weight transfer supports an electronic origin of the mid-infrared pseudogap in nickelates.
A randomized controlled trial evaluating the effectiveness of narrative therapy on resilience of orphaned and abandoned children fostered in SOS children’s village

ABSTRACT Background: Narrative Therapy is an efficacious treatment approach widely practiced for various psychological conditions. However, few studies have examined its effectiveness on resilience, a robust determinant of one’s mental health, and there has been no randomized controlled trial in sub-Saharan Africa. Objective: This study sought to evaluate the efficacy of narrative therapy for the resilience of orphaned and abandoned children in Rwanda. Method: This study was a ‘parallel randomized controlled trial’ in which participants (n = 72) were recruited from SOS Children’s Village. Half of the participants (n = 36) were randomly allocated to the intervention group and the rest to the delayed narrative therapy group. For the intervention group, children attended ten sessions (55 min each) over 2.5 months. Data were collected using the Child and Youth Resilience Measure (CYRM) and analyzed using mixed ANOVA within SPSS version 28. Result: The results from ANOVA indicated a significant main effect of time and group for resilience total scores. Of interest, there was a significant time by group interaction effect for resilience. Pairwise comparison analyses within-group showed a significant increase in resilience in the intervention group, and the effect size was relatively large in this group. Conclusion: Our findings highlight the notable efficacy of narrative therapy for children’s resilience in the intervention group. Therefore, health professionals and organizations working with orphaned and abandoned children will apply narrative therapy to strengthen their resilience and improve mental health. Trial registration: Pan African Clinical Trial Registry identifier: PACTR202107499406828. HIGHLIGHTS The effect size of narrative therapy for resilience was relatively large in the intervention group. Narrative therapy is an efficacious approach for resilience elevation in orphaned and abandoned children. Close attention should be paid to the implementation of narrative therapy for strengthening children’s resilience as an everyday tool in foster care.
On Some Patterns of Reduction

The notion of reduction in the natural sciences has been assimilated to the notion of inter-theoretical explanation. Many philosophers of science (following Nagel) have held that the apparently ontological issues involved in reduction should be replaced by analyses of the syntactic and semantic connections involved in explaining one theory on the basis of another. The replacement does not seem to have been especially successful, for we still lack a plausible account of inter-theoretical explanation. I attempt to provide one.
New Bio-Based Polymer Sorbents out of Terpene Compounds or Vegetable Oils: Synthesis, Properties, Analysis of Sorption Processes

This research presents a synthesis and characterization of new bio-based polymer sorbents. Natural origin substances such as terpenes (citral, limonene, and pinene) or vegetable oils (argan, linseed, and rapeseed oils) were used as monomers, and divinylbenzene was applied as the cross-linker. The newly prepared polymers were characterized by means of ATR-FTIR, TG/DTG and titration methods (acid and iodine values), and N2 physisorption experiments. Tests of sorption ability were carried out by a dynamic solid phase extraction method using a mixture of four phenols or single-component pharmaceutical solutions (salicylic acid, aspirin, ibuprofen, paracetamol, and ampicillin). The performed studies revealed that the terpene-based polymers possessed better-developed porous structures (420–500 m2/g) with more uniform pores than oil-based ones. However, the surface of the oil-based sorbents was more acidic in nature. The sorption tests showed that both the porosity and acidity of the surface significantly influenced the sorption. Recoveries of up to 90% were obtained for 2,4 dichlorophenol from C-DVB, L-DVB, and Ro-DVB. The lowest affinity to the polymers exhibited phenol (5–45%), aspirin (1–7%), and ampicillin (1–7%). A 70% recovery was achieved for ibuprofen from C-DVB. In-depth data analysis allowed the influence of various factors on the sorption process of test compounds of the studied polymers to be elucidated.