Miracle-dz/UniFAR-FTUs huggingface dataset:
Mutual regulation of the transcriptional activator NF-cB and its inhibitor, I1cB-a

The NF-#cB transcription factor complex is sequestered in the cytoplasm by the inhibitory protein I#cB-a (MAD-3). Various cellular stimuli relieve this inhibition by mechanisms largely unknown, leading to NF-KB nuclear lo-calization and transactivation of its target genes. It is demonstrated here with human T lymphocytes and monocytes that different stimuli, including tumor necrosis factor a and phorbol 12-myristate 13-acetate, cause rapid degradation of IOcB-a, with concomitant activation of NF-cB, followed by a dramatic increase in IKB-a mRNA and protein synthesis. Transfection studies reveal that the IKB-a mRNA and the encoded protein are potently induced by NF-cB and by homodimers of p65 and of c-Rel. We propose a model in which NF-. cB and IKB-a mutually regulate each other in a cycle: saturating amounts of the inhibitory IKB-a protein are destroyed upon stimulation, allowing rapid activation of NF-KB. Subsequently, IcB-a mRNA and protein levels are qulickly induced by the activated NF-cB. This resurgence of IKB-a protein acts to restore an equilibrium in which NF-KB is again inhibited. NF-KB dimeric transcription regulates gene through decameric cis-acting KB DNA motifs and a p50/p65
in IFN and Wnt Signaling PIASy-Deficient Mice Display Modest Defects

Protein inhibitors of activated STATs (PIAS) represent a small family of nuclear proteins that modulate the activity of many transcription factors and act as E3 ligases for covalent modiﬁcation of proteins with the small ubiquitin-like modiﬁer (SUMO). In particular, PIASy has been shown to inhibit the activation of gene expression by the IFN-responsive transcription factor STAT1 and the Wnt-responsive transcription factor LEF1. To assess the function of PIASy in vivo, we generated and analyzed mice carrying a targeted mutation of the Piasy gene. We ﬁnd that homozygous mutant mice have no obvious morphological defects and have a normal distribution of lymphocyte populations. Molecular analysis of signaling in response to IFN- (cid:1) and Wnt agonists revealed a modest reduction in the activation of endogenous and transfected target genes. Two-dimensional analysis of total proteins and SUMO-modiﬁed proteins in transformed pre-B cells showed no signiﬁcant differences between wild-type mice and homozygous mutant mice. Taken together, our data indicate that PIASy has a modest effect on cytokine and Wnt signaling, suggesting a redundancy with other members of the family of PIAS proteins. The Journal of Immunology, 2004, 173: 6189–6199.
Symbolic Data Augmentation for Assisted Neural Reasoning

Recent progress in various language processing tasks which require multi-step reasoning process in commonsense or scientific domains, are usually achieved by large-scale language models. While these models have achieved decent performance, their parameter number is becoming increasingly difficult for commodity hardware to handle. In this work, we propose a novel data augmentation technique based on symbolic methods SDAR that generates annotations in the text space. The SDAR annotator is an ensemble of multiple sub-annotators, each equipped with a searcher (usually neural) and a symbolic knowledge retriever. The annotations by each subannotator generated are combined and sent along with the original input to the target language model. We demonstrate that SDAR can boost the performance of smaller models to a comparable degree of or even surpass larger models with a magnitude more parameters, and establish the state-of-the-art single model performance on OPENBOOKQA.
The Welfare Consequences of Urban Traffic Regulations

We develop a novel structural model to represent individual transportation decisions and the equilibrium road traffic levels and speeds inside a city. The model has two main advantages relative to the existing frameworks. First, it is a micro-founded equilibrium model with a high level of heterogeneity. The model accounts for individual heterogeneity in access to different transportation modes, values of travel time, and schedule constraints. Furthermore, our model considers heterogeneous road congestion technologies across different areas. The second advantage is that all the model parameters are estimated using multiple publicly available data. We apply our model to the Paris metropolitan area to predict the road traffic equilibria under driving restrictions and road tolls and measure each policy’s welfare consequences. Our results suggest that all the policies decrease individuals’ utilities: the benefits of relaxing road congestion and improving car speeds do not offset the losses for individuals from switching to other transportation modes or to drive outside peak hours. However, road tolls raise significant tax revenues that generate positive total surplus changes when they are redistributed to individuals. In addition, these policies reduce emissions of global and local pollutants. However, they represent only a small gain once converted into monetary terms using standard social values for these emissions. JEL Classification: L9, R41, Q52
Enrich nutritional value for baldy bread fortified with Spirulina ( Arthrospira platensis ) microalgae

: Bread is one of the most popular bakery products, generally made from wheat flour 72% extraction which is limited in vitamins, minerals, antioxidants, and dietary fiber. Therefore, in the present study, wheat flour was fortified with 20% hull-less barley which contained β -glucan as a natural antioxidant and dietary fiber and also, it was supplemented with Spirulina platensis microalgae powder at 2.5, 5.0, 7.5 and 10.0% levels to improve its nutritional quality. The results showed that the Spirulina platensis is rich in proteins, antioxidants, DPPH Radical Scavenging, and dietary fiber and also hull-less barley had contained rich amounts from dietary fiber and β- glucan. The results indicated also that the water absorption, dough development time and stability time increased gradually by increasing the level of Spirulina platensis microalgae powder and 20% hull-less barley. However data showed that the wheat flour ws being replaced with Spirulina platensis microalgae powder at different levels and 20% hull-less barley minimized extensibility and dough energy. The results indicated that 7.5 % the addition of Spirulina platensis have not any negative effects on the shelf life of the loaves of bread and it improved the nutritional value, protein digestibility, and biological evaluation and blood compositions in rats.
T HE E FFECTS OF H IGH I NTENSITY S HORT R EST R ESISTANCE E XERCISE ON M USCLE D AMAGE M ARKERS IN M EN AND W OMEN

Heavens, KR, Szivak, TK, Hooper, DR, Dunn-Lewis, C, Comstock, BA, Flanagan, SD, Looney, DP, Kupchak, BR, Maresh, CM, Volek, JS, and Kraemer, WJ. The effects of high intensity short rest resistance exercise on muscle damage markers in men and women. J Strength Cond Res 28(4): 1041–1049, 2014—Within and between sexes, universal load prescription (as assigned in extreme conditioning programs) creates extreme ranges in individual training intensi-ties. Exercise intensity has been proposed to be the main factor determining the degree of muscle damage. Thus, the purpose of this study was to examine markers of muscle damage in resistance-trained men ( n = 9) and women ( n = 9) from a high intensity (HI) short rest (SR) (HI/SR) resistance exercise protocol. The HI/SR consisted of a descending pyramid scheme starting at 10 repetitions, decreasing 1 repetition per set for the back squat, bench press, and deadlift, as fast as possible. Blood was drawn pre-exercise (pre), immediately postexercise (IP), 15 minutes postexercise (+15), 60 minutes postexercise (+60), and 24 hours postexercise (+24). Women demonstrated signiﬁcant increases in interleukin 6 (IL-6; comparison to women, average concentrations for men signiﬁcantly increased at all time points.
Contextual Inquiry into Programmers’ Use of Mimi and Implications for Embedded DSL Design

Programming tools are increasingly integral to research and analysis in myriad domains, including specialized areas with no formal relation to computer science. Embedded domain-specific languages (eDSLs) have the potential to serve these programmers while placing relatively light implementation burdens on language designers. However, barriers to eDSL usability reduce their practical value and adoption. In this paper, we aim to deepen our understanding of how programmers use eDSLs and identify user needs to inform future eDSL designs. We performed a contextual inquiry (9 participants) with domain experts using Mimi, an eDSL for climate change economics modeling. A thematic analysis identified four key themes, including: the host language has significant and sometimes unexpected impacts on eDSL usability, and users preferentially engage with domain-specific communities and code templates rather than host language resources. The needs uncovered in our study offer implications for future eDSL designs and suggest directions for future language usability research.
Perspectives on Light-Based Disinfection to Reduce the Risk of COVID-19 Transmission during Dental Care

: Severe Acute Respiratory Syndrome 2 (SARS-CoV-2) is a positive-sense single-stranded RNA coronavirus capable of causing potentially lethal pneumonia-like infectious diseases in mammals and birds. The main mechanisms by which SARS-CoV-2 spreads include airborne transmission (aerosols and droplets) and the direct exposure of tissues (conjunctival, nasal, and oral mucosa) to contaminated ﬂuids. The aerosol formation is universal in dentistry due to the use of rotary instruments (handpieces), ultrasonic scalers, and air–water syringes. Several layers of infection control should protect key stakeholders such as dentists, dental staff, and patients. These include the utilization of personal protective equipment, high-volume evacuation systems, pre-procedural mouthwashes, rubber dam, and more recently, antimicrobial photodynamic therapy and intra-oral visible light irradiation. These non-speciﬁc light-based approaches are relatively simple, inexpensive, and effective against viruses, bacteria, and fungi. Therefore, the present perspective review discusses the current efforts and limitations on utilizing biophotonic approaches as adjunct infection control methods to prevent the transmission of SARS-CoV-2 in dental settings. In addition, the present perspective review may positively impact subsequent developments in the ﬁeld, as it offers relevant information regarding the intricacies and complexities of infection control in dental settings.
B Lymphopoiesis in the Thymus

The thymus has been regarded as the major site of T cell differentiation. We ﬁnd that in addition to ab and gd T cells, a signiﬁcant number ( ; 3 3 10 4 per day) of B220 1 IgM 1 mature B cells are exported from the thymus of C57BL/6 mice. Of these emigrating B cells, we estimate that at least ; 2 3 10 4 per day are cells which developed intrathymically, whereas a maximum of ; 0.8 3 10 4 per day are cells which circulated through the thymus from the periphery. The thymus possesses a signiﬁcant number of pro-B and pre-B cells that express CD19, VpreB, l 5, and pax-5. These B cell progenitors were found in the thymic cortex, whereas increasingly mature B cells were found in the corticomedullar and medullary regions. Other lymphoid cells, including NK cells and lymphoid dendritic cells, are not exported from the thymus at detectable levels. Thus, the thymus contributes to the formation of peripheral pools of B cells as well as of ab and gd T cells. The Journal of Immunology, 2000, 164: 5221–5226. hymocyte progenitors migrate from hematopoietic tis-sues, such as the bone marrow, to the thymus where they proliferate, mature, and undergo a stringent selection pro-cess resulting in the export of self-tolerant TCR ab T cells and TCR gd T cells. During their tenure in the thymus, maturing thymocytes interact with the thymic microenvironment, which provides the appropriate cellular and/or soluble factors to enable thymocyte proliferation, development, and selection. This microenvironment includes several types of thymic epithelial cells, bone marrow-derived dendritic cells, macrophages, bone marrow derived B cells, and several mesenchymal elements. Thymic epithelial cells produce
Malignant giant cell tumor of toe

Abstract Introduction: A giant cell tumor of soft tissue (GCST) is a benign soft tissue tumor that often occurs subcutaneously in the extremities. Rare cases of malignant GCST have been reported, but its pathogenesis remains unclear. Patients concerns: We report a case of a 68-year-old man who noticed a painless mass on his second toe one and a half years ago. He visited the Department of Dermatology at our hospital. Magnetic resonance imaging revealed a soft tissue tumor, surrounding the distal aspect of the second toe. Diagnosis: A biopsy of the tumor was performed by a dermatologist, and it revealed a malignant giant cell tumor of the toe. Interventions: He was referred to our department and underwent lay amputation for wide-margin resection. Outcomes: No recurrence or metastasis was observed 5 years after treatment. Conclusion : Malignant GCST should be treated with wide-margin resection immediately after its diagnosis.
Real-Time Integration of Segmentation Techniques for Reduction of False Positive Rates in Fire Plume Detection Systems during Forest Fires

Governmental offices are still highly concerned with controlling the escalation of forest fires due to their social, environmental and economic consequences. This paper presents new developments to a previously implemented system for the classification of smoke columns with object detection and a deep learning-based approach. The study focuses on identifying and correcting several False Positive cases while only obtaining a small reduction of the True Positives. Our approach was based on using an instance segmentation algorithm to obtain the shape, color and spectral features of the object. An ensemble of Machine Learning (ML) algorithms was then used to further identify smoke objects, obtaining a removal of around 95% of the False Positives, with a reduction to 88.7% (from 93.0%) of the detection rate on 29 newly acquired daily sequences. This model was also compared with 32 smoke sequences of the public HPWREN dataset and a dataset of 75 sequences attaining 9.6 and 6.5 min, respectively, for the average time elapsed from the fire ignition and the first smoke detection.
Factors Influencing the Therapeutic Efficacy of the PSMA Targeting Radioligand 212Pb-NG001

Simple Summary Prostate-specific membrane antigen (PSMA) is a protein overexpressed in metastatic castration-resistant prostate cancer and a promising target for targeted radionuclide therapy. PSMA-targeted alpha therapy is of growing interest due to the high-emission energy and short range of alpha particles, resulting in a prominent cytotoxic potency. This study assesses the influence of various factors on the in vitro and in vivo therapeutic efficacy of the alpha particle generating PSMA-targeting radioligand 212Pb-NG001. Abstract This study aimed to determine the influence of cellular PSMA expression, radioligand binding and internalization, and repeated administrations on the therapeutic effects of the PSMA-targeting radioligand 212Pb-NG001. Cellular binding and internalization, cytotoxicity, biodistribution, and the therapeutic efficacy of 212Pb-NG001 were investigated in two human prostate cancer cell lines with different PSMA levels: C4-2 (PSMA+) and PC-3 PIP (PSMA+++). Despite 10-fold higher PSMA expression on PC-3 PIP cells, cytotoxicity and therapeutic efficacy of the radioligand was only 1.8-fold better than for the C4-2 model, possibly explained by lower cellular internalization and less blood-rich stroma in PC-3 PIP xenografts. Mice bearing subcutaneous PC-3 PIP xenografts were treated with 0.2, 0.4, and 0.8 MBq of 212Pb-NG001 that resulted in therapeutic indexes of 2.7, 3.0, and 3.5, respectively. A significant increase in treatment response was observed in mice that received repeated injections compared to the corresponding single dose (therapeutic indexes of 3.6 for 2 × 0.2 MBq and 4.4 for 2 × 0.4 MBq). The results indicate that 212Pb-NG001 can induce therapeutic effects at clinically transferrable doses, both in the C4-2 model that resembles solid tumors and micrometastases with natural PSMA expression and in the PC-3 PIP model that mimics poorly vascularized metastases.
Geometry of learning: A data-driven understanding with neighborhood and graph methods

Deep learning has shown great success in learning complex data patterns while being able to make good predictions on unseen data points. However, the limited understanding of these systems hinders further progress and application to several domains in the real world. This predicament is exemplified by the time-consuming model selection, privacy of training data, and explainability of obtained predictions in the presence of adversarial examples and model perturbations. In this proposal, we propose to study local neighborhood and graph based tools to improve the analysis and design of deep learning. In particular, our approach is aimed at characterizing the mappings induced by a deep neural network based on the input-output geometry of the data used for learning them. Unlike previous works that focus on mathematical modeling or approximations of the components in neural networks, our goal is to develop and lay the foundation for a data-driven language for describing and comparing deep learning models. Concretely, we will pursue the following tasks. First, we will develop metrics that take into account the local and global data geometry, rather than just considering pairwise distances between points. Second, we will study the stability of deep learning systems using proposed geometric metrics. In particular, we will characterize the connections between optimization and data geometry, and its impact on generalization. Finally, we will make use of the understandings gained to develop approaches for the adaptivity and transferability of deep learning systems. The proposed research will focus on theoretical and practical aspects of the design and analysis of deep learning. For example, (i) on the theoretical front, we will develop statistical results linking the developed geometric properties to that of data distribution, number of parameters, and the size of training data; (ii) on the algorithmic and practical front, we propose to develop efficient methods for obtaining proposed geometric metrics such that it can be used for large scale parameter and model selection without incurring severe computational overhead.
Agreement attraction error and timing profiles in continuous speech

Studies of agreement attraction in language production have shown that speakers systematically produce verb agreement errors in the presence of a local noun whose features differ from that of the agreement controller. However, in attraction experiments, these errors only ever occur in a subset of trials. In the present study, we applied a naturalistic scene-description paradigm to investigate how attraction affects the distribution of errors and the time-course of correctly inflected verbs. We conducted our experiment both in the lab and in an unsupervised web-based setting. The results were strikingly similar across the experimental settings for both the error and timing analyses, demonstrating that it is possible to conduct production experiments via the internet with a high level of similarity to those done in the lab. The experiments replicated the basic number attraction effect, though they elicited comparable interference from both singular and plural local nouns, challenging common assumptions about a strong plural markedness effect in attraction. We observed slowdowns before correct verbs that paralleled the distribution of agreement errors, suggesting that the process resulting in attraction can be active even when no error is produced. Our results are easily captured by a model of agreement attraction in which errors arise at the point of computing agreement, rather than reflecting earlier errors made during initial encoding of the subject number.
Salicylic Acid in Plant Symbioses: Beyond Plant Pathogen Interactions

Simple Summary Plants form beneficial symbioses with endophytes, arbuscular mycorrhizal fungi, and nitrogen-fixing rhizobia. In addition to their role in plant growth and development, these microorganisms enhance host plant tolerance to a wide range of environmental stress. Salicylic acid (SA) is widely known to play essential roles in plant defense against pathogens. In addition, SA has been shown to be involved in plant–microbe symbiotic interactions. In this review, we summarize the impact of SA on symbiotic interactions and on defense priming by beneficial microbes. Abstract Plants form beneficial symbioses with a wide variety of microorganisms. Among these, endophytes, arbuscular mycorrhizal fungi (AMF), and nitrogen-fixing rhizobia are some of the most studied and well understood symbiotic interactions. These symbiotic microorganisms promote plant nutrition and growth. In exchange, they receive the carbon and metabolites necessary for their development and multiplication. In addition to their role in plant growth and development, these microorganisms enhance host plant tolerance to a wide range of environmental stress. Multiple studies have shown that these microorganisms modulate the phytohormone metabolism in the host plant. Among the phytohormones involved in the plant defense response against biotic environment, salicylic acid (SA) plays an important role in activating plant defense. However, in addition to being a major actor in plant defense signaling against pathogens, SA has also been shown to be involved in plant–microbe symbiotic interactions. In this review, we summarize the impact of SA on the symbiotic interactions. In addition, we give an overview of the impact of the endophytes, AMF, and rhizobacteria on SA-mediated defense response against pathogens.
ETHICAL BEHAVIOUR OF FUTURE MANAGERS: STUDENTS FROM THE PROVINCE OF KENITRA AS A CASE STUDY :

The purpose of this paper is to determine management sciences students’ perceptions of business ethics. To achieve its objectives, the study uses the ATBEQ "Attitudes Toward Business Ethics Questionnaire" as a tool through the four economic dimensions of Stevens (1979), namely, Machiavellianism, Social Darwinism, Objectivism and Relativism. Moreover, the present survey analyses the influence of demographic variables such as age, gender and level of training on these students’ behaviour. The results of this study confirm that demographic and personal characteristics are important factors influencing students' attitudes towards business ethics. Moreover, the expected results also show that there are no significant differences with respect to the ethical behaviour adopted by management sciences students. It is believed that this study, based on the analysis of students' attitude towards ethics in business, can contribute to understanding their future behaviour in ethical decision-making as future managers.
It’s Time to Disagree: Young People’s Self- efficacy for Political Disagreement in Norway

Discussion about political and social issues in school matter for a wide array of democratic skills and competences such as political engagement, participation, and knowledge. However, little research has been done on what impact characteristics of the discussion climate in classrooms can have on young people’s engagement with political disagreements and conflicts. This article applies structural equation modelling (SEM) to survey data from the 2016 Norwegian International Civic and Citizenship study (ICCS) to show how discussions about social and political issues in the classroom setting can serve as an arena for building young peoples’ self- efficacy for political disagreements. The analysis also considers the role of political interest and socioeconomic background.