Miracle-dz/UniFAR-FTUs huggingface dataset:
A Multi-Agent Team Formation Framework for Classroom Instruction ∗

A challenge in AI education is the creation of interesting te rm projects. An ideal term project is fun, engaging, and allows students to focus on the interesting parts of a problem, rath e than spending several weeks designing infrastructure or co ming up to speed on a complex simulation framework. In this paper, we describe our efforts in designing a multi-agent te am formation environment using the Repast toolkit, which we used successfully for a course project in an upper-level cla ss on intelligent agents. The infrastructure that we develope d resulted in a project that was both enjoyable and pedagogicall y effective, and that could be completed in only a few weeks. We begin with a description of the initial design and deployment of the project, followed by a discussion of problems we encountered, and the changes we have made for future classroom deployments. We conclude with a description of some open issues with our project and how we will address them.
INTER-INFORMANT AGREEMENT ON THE MOTIVATION ASSESSMENT SCALE: ANOTHER FAILURE TO REPLICATE

The present study evaluated inter-informant agreement on the Motivation Assessment Scale across 42 topographies of challenging behaviour in five children with severe intellectual disabilities. The results revealed unacceptably low levels of inter-rater reliability on all sub-scales of the MAS and unacceptably low levels of inter-informant agreement on the purported behavioural function of the rated challenging behaviours.
THE NATIVE AND EXOTIC AVIFAUNA OF EASTER ISLAND : THEN AND NOW La avifauna nativa

The Polynesian colonization of islands in the south Pacific led to one of the greatest extinctions of birds in Earth’s history. An important case study of the historic and prehistoric effects of human activity comes from Easter Island, which has lost most of its native terrestrial biota. We studied the abundance and diversity of the terrestrial (all exotic) and seabird (all native) populations of Easter Island in 2001 and 2003. To assess whether populations have remained stable over ecological time (30 years) we compared our results with published accounts of the island’s historic and prehistoric avifauna. Terrestrial species were quantified using 100 x 100 m quadrat counts and by walking surveys. All known seabird colonies were surveyed from shore or accessed by boat. Five terrestrial exotic species were common, yet they varied 77-fold in abundance. We observed 10 seabird species, of which seven were breeding. We present the first reports of Sharp-tailed Sandpiper, Henderson and Phoenix petrels, as well as anecdotal evidence of egrets and shorebird species previously unknown from the island. Breeding populations of both exotic and native species have remained relatively constant over the last three decades. Native seabird populations remain low and concentrated to several small cliffs and islets. We discuss the importance of our findings in light of conserving the remaining native populations of seabirds on Easter Island.
A Two-Stage Model for Diffusion of Innovations

The objective of this paper is to provide an analytical framework to study the whole process of diffusion of innovations, new products or ideas: we take into account knowledge transfer in a complex society, decisional process for adoption and key features in the spread of new technologies. For this purpose, we propose a probabilistic model based on an interacting population connected through new communication channels (such as social media) where potential adopters are linked with each other at different connection degrees. Our diffusion curve is the result of an emotion driven decision process following the awareness phase. Finally, we are able to recover stylized facts highlighted by the extant literature in the field.
A model for early events in the assembly pathway of cyanobacterial phycobilisomes

Biological self‐assembly is remarkable in its fidelity and in the efficient production of intricate molecular machines and functional materials from a heterogeneous mixture of macromolecules. The phycobilisome, a light‐harvesting structure of cyanobacteria, presents the opportunity to study an in vivo assembly process in detail. The phycobilisome molecular architecture is defined, and crystal structures are available for all major proteins, as are a large sequence database (including a genome sequence) and effective genetic systems exist for some cyanobacteria. Recent studies on subunit interaction, covalent modification, and protein stability suggest a model for the earliest events in the phycobilisome assembly pathway. Partitioning of phycobilisome proteins between degradation and assembly is proposed to be controlled by the interaction equilibria between phycobilisome assembly partners, processing enzymes and chaperones. The model provides plausible explanations for existing observations and makes predictions that are amenable to direct experimental investigation.
Automated detection and differentiation of drusen, exudates, and cotton-wool spots in digital color fundus photographs for diabetic retinopathy diagnosis.

PURPOSE To describe and evaluate a machine learning-based, automated system to detect exudates and cotton-wool spots in digital color fundus photographs and differentiate them from drusen, for early diagnosis of diabetic retinopathy. METHODS Three hundred retinal images from one eye of 300 patients with diabetes were selected from a diabetic retinopathy telediagnosis database (nonmydriatic camera, two-field photography): 100 with previously diagnosed bright lesions and 200 without. A machine learning computer program was developed that can identify and differentiate among drusen, (hard) exudates, and cotton-wool spots. A human expert standard for the 300 images was obtained by consensus annotation by two retinal specialists. Sensitivities and specificities of the annotations on the 300 images by the automated system and a third retinal specialist were determined. RESULTS The system achieved an area under the receiver operating characteristic (ROC) curve of 0.95 and sensitivity/specificity pairs of 0.95/0.88 for the detection of bright lesions of any type, and 0.95/0.86, 0.70/0.93, and 0.77/0.88 for the detection of exudates, cotton-wool spots, and drusen, respectively. The third retinal specialist achieved pairs of 0.95/0.74 for bright lesions and 0.90/0.98, 0.87/0.98, and 0.92/0.79 per lesion type. CONCLUSIONS A machine learning-based, automated system capable of detecting exudates and cotton-wool spots and differentiating them from drusen in color images obtained in community based diabetic patients has been developed and approaches the performance level of retinal experts. If the machine learning can be improved with additional training data sets, it may be useful for detecting clinically important bright lesions, enhancing early diagnosis, and reducing visual loss in patients with diabetes.
The Comparison and Analysis of Scale-Invariant Descriptors based on the SIFT

Based on the feature matching theory about SIFT (Scale-Invariant Feature Transform) keypoints, the concentric circle structure and the color feature vector of scale-invariant descriptor are proposed in this paper. In the concentric circle structure, the radiuses of the concentric circles are proportional to the scale factor, which can achieve the scale invariance. To achieve the rotation invariance, the coordinates of descriptor are also rotated in relation to the point’s orientation. Compared with the square structure of SIFT descriptor, the concentric circle structure not only has simpler computation, but also is more robust to image rotation. The color feature vector chooses the mean values of different color components R, G, B in each subregion of descriptor as the vector’s elements. Compared with the gray feature vector of SIFT descriptor, the color feature vector fully utilizes the image’s color information, having stronger rotation invariance, and obviously decreasing the vector’s dimension, with less computation. After the theory analyses, the experimental results have certified their validity, too. Key-Words: computer vision; feature matching; scale-invariant keypoint; scale-invariant descriptor; concentric circle structure; color feature vector;
Virtual Reality Provides Leisure Time Opportunities for Young Adults with Physical and Intellectual Disabilities

Due to limitations in their physical abilities, adults with cerebral palsy (CP) have relatively few opportunities to engage in independent leisure activities. This pervasive lack of opportunity often leads to the development of dependent behavioral patterns and learned helplessness. The objective of this pilot study was to explore ways in which virtual reality can provide positive and enjoyable leisure experiences during physical interactions with different game-like virtual environments and potentially lead to increased self-esteem and a sense of self-empowerment. The study sample consisted of five young male adults with CP and severe intellectual disabilities who are non-speaking and who use wheelchairs for mobility. Each participant experienced three game-like virtual scenarios via VividGroup's Gesture Xtreme video capture virtual reality (VR) system. The participant's video captured image was processed on the same plane as screen graphical animations that react in real time in response to his movements. Outcome measures included the participants' responses to a five-item presence questionnaire, a 6-item task specific questionnaire and observation of their videotaped performance while participating in the virtual games. Participants' responses to the questionnaire showed a high level of presence in all three scenarios. These participants demonstrated an exceptional degree of enthusiasm during each VR experience; some reacted to the various stimuli via appropriate and goal-oriented responses, in other cases the response was more arbitrary. Documentation of behaviors during and following the VR experiences may provide insight into the important role that VR may play in nurturing their self-esteem and sense of empowerment.
'Just Journalism:' A Moral Debate Framework

The centuries-old lost War Doctrine can be a model for framing the journalistic ethics decision making process—a Just Journalism moral test of intended action against anticipated effects. A just journalism paradigm provides a clear set of criteria to be argued and met in considering action that approaches or crosses such borders of extreme professional practice as deception or intrusions into personal privacy. The debate provides a sharper focus on the effects of actions through balancing intentions, justice, methods, alternatives— and on who should be involved. This article develops a lust Journalism Doctrine by translating Just War criteria into journalistic counterparts. A discussion shows how the criteria can be applied to deception and in evaluating the moral fit of naming of both accused and accuser in a rape case.
Steroid-resistant idiopathic nephrotic syndrome in children: long-term follow-up and risk factors for end-stage renal disease.

INTRODUTION Steroid resistant idiopathic nephrotic syndrome (SRINS) in children is one of the leading causes of progression to chronic kidney disease stage V (CKD V)/end stage renal disease (ESRD). OBJECTIVE The aim of this retrospective study is to evaluate the efficacy of immunosuppressive drugs (IS) and to identify risk factors for progression to ESRD in this population. METHODS Clinical and biochemical variables at presentation, early or late steroid resistance, histological pattern and response to cyclosporine A (CsA) and cyclophosfamide (CP) were reviewed in 136 children with SRINS. The analyzed outcome was the progression to ESRD. Univariate as well as multivariate Cox-regression analysis were performed. RESULTS Median age at onset was 5.54 years (0.67-17.22) and median follow up time was 6.1 years (0.25-30.83). Early steroid-resistance was observed in 114 patients and late resistance in 22. Resistance to CP and CsA was 62.9% and 35% respectively. At last follow-up 57 patients reached ESRD. The renal survival rate was 71.5%, 58.4%, 55.3%, 35.6% and 28.5% at 5, 10, 15, 20 and 25 years respectively. Univariate analysis demonstrated that older age at onset, early steroid-resistance, hematuria, hypertension, focal segmental glomerulosclerosis (FSGS), and resistance to IS were risk factors for ESRD. The Cox proportional-hazards regression identified CsAresistance and FSGS as the only predictors for ESRD. CONCLUSION Our findings showed that CsA-resistance and FSGS were risk factors for ESRD.
Defective thrombus formation in mice lacking coagulation factor XII

Blood coagulation is thought to be initiated by plasma protease factor VIIa in complex with the membrane protein tissue factor. In contrast, coagulation factor XII (FXII)–mediated fibrin formation is not believed to play an important role for coagulation in vivo. We used FXII-deficient mice to study the contributions of FXII to thrombus formation in vivo. Intravital fluorescence microscopy and blood flow measurements in three distinct arterial beds revealed a severe defect in the formation and stabilization of platelet-rich occlusive thrombi. Although FXII-deficient mice do not experience spontaneous or excessive injury-related bleeding, they are protected against collagen- and epinephrine-induced thromboembolism. Infusion of human FXII into FXII-null mice restored injury-induced thrombus formation. These unexpected findings change the long-standing concept that the FXII-induced intrinsic coagulation pathway is not important for clotting in vivo. The results establish FXII as essential for thrombus formation, and identify FXII as a novel target for antithrombotic therapy.
Institutional-Level Monitoring of Immune Checkpoint Inhibitor IrAEs Using a Novel Natural Language Processing Algorithmic Pipeline

Background: Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment but can result in severe immune-related adverse events (IrAEs). Monitoring IrAEs on a large scale is essential for personalized risk profiling and assisting in treatment decisions. Methods: In this study, we conducted an analysis of clinical notes from patients who received ICIs at the Tel Aviv Sourasky Medical Center. By employing a Natural Language Processing algorithmic pipeline, we systematically identified seven common or severe IrAEs. We examined the utilization of corticosteroids, treatment discontinuation rates following IrAEs, and constructed survival curves to visualize the occurrence of adverse events during treatment. Results: Our analysis encompassed 108,280 clinical notes associated with 1,635 patients who had undergone ICI therapy. The detected incidence of IrAEs was consistent with previous reports, exhibiting substantial variation across different ICIs. Treatment with corticosteroids varied depending on the specific IrAE, ranging from 17.3% for thyroiditis to 57.4% for myocarditis. Our algorithm demonstrated high accuracy in identifying IrAEs, as indicated by an area under the curve (AUC) of 0.89 for each suspected note and F1 scores of 0.87 or higher for five out of the seven IrAEs examined at the patient level. Conclusions: This study presents a novel, large-scale monitoring approach utilizing deep neural networks for IrAEs. Our method provides accurate results, enhancing understanding of detrimental consequences experienced by ICI-treated patients. Moreover, it holds potential for monitoring other medications, enabling comprehensive post-marketing surveillance to identify susceptible populations and establish personalized drug safety profiles.
The Meritocracy Myth

al offenders without consideration of individual differences in the youths. One of Zimring’s central arguments in this book is that we need to avoid the automatically harsh punishment for juveniles and instead use a case-by-case system as a basis. He advocates this case-by-case decision-making process at each stage of the adjudication system, from arrest through management and supervision in the community. In regard to Megan’s Law, he discusses the negative effects this will likely have on juvenile sexual offenders as a result of labeling and stigmatizing them. He notes that like many of the laws related to sex offenders, the effects of Megan’s Law have not been empirically documented on adults or juveniles, and he advises extreme caution when labeling and stigmatizing juvenile offenders when such actions produce no concrete benefits. Though readers may not all agree with his suggested reforms, Zimring presents an excellent critique of the problems related to juvenile sexual offenders and the psychological and legal response to them. He emphasizes the need for empirically sound legislation based on scientific evidence, and a reassessment of the treatment and legal process for juvenile sexual offenders. The most important aspect of the book is that it forces us to challenge what we have until now accepted as fact and shows why we must not simply accept unfounded assumptions.
Clinical indicators in surgery: a critical review of the Australian experience

A set of clinical measures (indicators), developed by an Australian Council on Healthcare Standards (ACHS) and Royal Australasian College of Surgeons (RACS) working party, was introduced into the accreditation programme in 1997. Although early qualitative and quantitative reporting by health‐care organizations (HCOs) reflected their value in stimulating change, the number of HCOs reporting data on this set of clinical indicators (CIs) has declined, despite an increase in the number of HCOs reporting data on the CIs programme overall. Possible reasons for this decline were sought.
A Dual-Pathway Neural Network Model of Control Relinquishment in Motor Skill Learning

Cognitive psychologists have long recognized that the acquisition of a motor skill involves a transition from attention-demanding controlled processing to more fluent automatic processing. Neuroscientific studies suggest that controlled and automatic processing rely on two largely distinct neural pathways. The controlled pathway, which includes the prefrontal cortex, is seen as acquiring declarative representations of skills. In comparison, the automatic pathway is thought to develop procedural representations. Automaticity in motor skill learning involves a reduction in dependence on frontal systems and an increased reliance on the automatic pathway. In this paper, we propose a biologically plausible computational model of motor skill automaticity. This model offers a dual-pathway neurocomputational account of the translation of declarative knowledge into procedural knowledge during motor learning. In support of the model, we review some previously reported human experimental results involving the learning of a sequential key pressing task, and we demonstrate, through simulation, howthe model provides a parsimonious explanation for these results.
Regulatory T Cell Suppressive Potency Dictates the Balance between Bacterial Proliferation and Clearance during Persistent Salmonella Infection

The pathogenesis of persistent infection is dictated by the balance between opposing immune activation and suppression signals. Herein, virulent Salmonella was used to explore the role and potential importance of Foxp3-expressing regulatory T cells in dictating the natural progression of persistent bacterial infection. Two distinct phases of persistent Salmonella infection are identified. In the first 3–4 weeks after infection, progressively increasing bacterial burden was associated with delayed effector T cell activation. Reciprocally, at later time points after infection, reductions in bacterial burden were associated with robust effector T cell activation. Using Foxp3 GFP reporter mice for ex vivo isolation of regulatory T cells, we demonstrate that the dichotomy in infection tempo between early and late time points is directly paralleled by drastic changes in Foxp3+ Treg suppressive potency. In complementary experiments using Foxp3 DTR mice, the significance of these shifts in Treg suppressive potency on infection outcome was verified by enumerating the relative impacts of regulatory T cell ablation on bacterial burden and effector T cell activation at early and late time points during persistent Salmonella infection. Moreover, Treg expression of CTLA-4 directly paralleled changes in suppressive potency, and the relative effects of Treg ablation could be largely recapitulated by CTLA-4 in vivo blockade. Together, these results demonstrate that dynamic regulation of Treg suppressive potency dictates the course of persistent bacterial infection.
New Lace and Arsenic: adventures in weak memory with a program logic

We describe a program logic for weak memory (also known as relaxed memory). The logic is based on Hoare logic within a thread, and rely/guarantee between threads. It is presented via examples, giving proofs of many weak-memory litmus tests. It extends to coherence but not yet to synchronised assignment (compare-and-swap, load-logical/store-conditional). It deals with conditionals and loops but not yet arrays or heap. The logic uses a version of Hoare logic within threads, and a version of rely/guarantee between threads, with five stability rules to handle various kinds of parallelism (external, internal, propagation-free and two kinds of in-flight parallelism). There are B and U modalities to handle propagation, and temporal modalities since, Sofar and Ouat to deal with global coherence (SC per location). The logic is presented by example. Proofs and unproofs of about thirty weak-memory examples, including many litmus tests in various guises, are dealt with in detail. There is a proof of a version of the token ring.
Cardiac Magnetic Resonance 2D+T Short- and Long-axis Segmentation via Spatio-temporal SAM Adaptation

Accurate 2D+T myocardium segmentation in cine cardiac magnetic resonance (CMR) scans is essential to analyze LV motion throughout the cardiac cycle comprehensively. The Segment Anything Model (SAM), known for its accurate segmentation and zero-shot generalization, has not yet been tailored for CMR 2D+T segmentation. We therefore introduce CMR2D+T-SAM, a novel approach to adapt SAM for CMR 2D+T segmentation using spatio-temporal adaption. This approach also incorporates a U-Net framework for multi-scale feature extraction, as well as text prompts for accurate segmentation on both short-axis (SAX) and long-axis (LAX) views using a single model. CMR2D+T-SAM outperforms existing deep learning methods on the STACOM2011 dataset, achieving a myocardium Dice score of 0.885 and a Hausdorff distance (HD) of 2.900 pixels. It also demonstrates superior zero-shot generalization on the ACDC dataset with a Dice score of 0.840 and a HD of 4.076 pixels.