Miracle-dz/UniFAR-FTUs huggingface dataset:
Konrad-zuse-zentrum F ¨ Ur Informationstechnik Berlin Improving Strong Branching by Domain Propagation Improving Strong Branching by Domain Propagation

One of the essential components of a branch-and-bound based mixed-integer linear programming (MIP) solver is the branching rule. Strong branching is a method used by many state-of-the-art branching rules to select the variable to branch on. It precomputes the dual bounds of potential child nodes by solving auxiliary linear programs (LPs) and thereby helps to take good branching decisions that lead to a small search tree. In this paper, we describe how these dual bound predictions can be improved by including domain propagation into strong branching. Domain propagation is a technique MIP solvers usually apply at every node of the branch-and-bound tree to tighten the local domains of variables. Computational experiments on standard MIP instances indicate that our improved strong branching method significantly improves the quality of the predictions and causes almost no additional effort. For a full strong branching rule, we are able to obtain substantial reductions of the branch-and-bound tree size as well as the solving time. Moreover, the state-of-the-art hybrid branching rule can be improved this way as well.
AAC intervention does not hinder natural speech production for children with autism, but natural speech gains tend to be small

Data sources: The reference lists of previously published and unpublished studies relating to augmentative and alternative communication (AAC) and autism were searched. This search was followed by one of general-purpose databases—including the Cumulative Index of Nursing and Allied Health (CINAHL), Educational Resources Information Clearinghouse (ERIC), Linguistics and Language Behaviour Abstracts (LLBA), MEDLINE, and PsycINFO—using the pearl-growing strategy (Schlosser, Wendt, Bhavnani, & Nail-Chiwetalu, 2006). As this strategy yielded only three references, the keyword ‘speech development’ was dropped and replaced with free-text words using search terms specific to each database. These included combinations of terms such as ‘augmentative and alternative communication’, ‘communication systems’, ‘sign language’, ‘autism’, ‘autistic disorder’, ‘communication skills training’, and ‘speech’. The researchers searched databases for doctoral dissertations and masters thesis, including the ProQuest Digital Dissertations database. They also searched publisherrelated databases for articles in press or that were published electronically prior to publication in print. Finally, the researchers contacted active researchers in AAC and autism via email and asked them to nominate any relevant additional studies that were not on an attached list of included and excluded studies.
ECL-LIRIS at TrecVid 2011: Semantic Indexing

This is the first time that our team participate TRECVID. This paper summarizes our approach submitted to Semantic Indexing (SIN) task in TRECVID 2011. Our approach adopts bag-of-features method to transform original visual and audio features into histogram features, using pre-trained codebook. After feature transformation, one-versus-others SVMs with Chi-square kernel are trained. In decision step, averaged probability is calculated as a final score to rank shots. Under this framework, we tested 4 visual features including dense grid SIFT, color SIFT, OLBPC and DAISY together with 1 audio feature consisting of MFCC with delta and acceleration. Our audio visual combination model achieves best results in terms of mean xinfAP. Besides, considering the huge amount of data this year, we employed several speedup strategies such as k-means clustering with GPU acceleration and homogeneous kernel map. All these efforts rank us at the 12 th out of 19 teams in full run and the 13 th out of 27 teams in the light run test.
Students' Experiences in Sport-Based Physical Education: [More Than] Apologies are Necessary

Those of us who have been participants in sport for much of our lives often find it a time-consuming and irrelevant task to defend the joys and rewards of physical activity to the uninformed or the uninitiated. Some physical education teachers are amazed at the energy they must spend motivating students to dress and participate in physical activity at the lowest intensity levels (Ennis, 1995). Even physiologists are modifying the “criteria” for health-enhancing exercise to make it more palatable for the majority of Americans who enjoy a sedentary lifestyle and are unconcerned with target heart rate zones. While many Americans watch sport, far fewer participate in sport as aphysical activity. Corlett, in his efforts to focus on the benefits of sport, glazes over the problems insidious in some sporting contexts. I will focus on problems plaguing sport-based, public school physical education that lead to discriminatory and abusive practices. I am most concerned with the policies used to perpetuate discrimina.
Cluster-Based Normalization Layer for Neural Networks

Deep learning faces significant challenges during the training of neural networks, including internal covariate shift, label shift, vanishing/exploding gradients, overfitting, and computational complexity. While conventional normalization methods, such as Batch Normalization, aim to tackle some of these issues, they often depend on assumptions that constrain their adaptability. Mixture Normalization faces computational hurdles in its pursuit of handling multiple Gaussian distributions. This paper introduces Cluster-Based Normalization (CB-Norm) in two variants - Supervised Cluster-Based Normalization (SCB-Norm) and Unsupervised Cluster-Based Normalization (UCB-Norm) - proposing a groundbreaking one-step normalization approach. CB-Norm leverages a Gaussian mixture model to specifically address challenges related to gradient stability and learning acceleration. For SCB-Norm, a supervised variant, the novel mechanism involves introducing predefined data partitioning, termed clusters, to normalize activations based on the assigned cluster. This cluster-driven approach creates a space that conforms to a Gaussian mixture model. On the other hand, UCB-Norm, an unsupervised counterpart, dynamically clusters neuron activations during training, adapting to task-specific challenges without relying on predefined data partitions (clusters). This dual approach ensures flexibility in addressing diverse learning scenarios. CB-Norm innovatively uses a one-step normalization approach, where parameters of each mixture component (cluster in activation space) serve as weights for deep neural networks. This adaptive clustering process tackles both clustering and resolution of deep neural network tasks concurrently during training, signifying a notable advancement in the field.
What Are You Doing? What Am I Doing?

Psychology ought to describe how and explain why we human beings live our lives as we do, which necessarily comes down to how and why we engage in the actions and have the subjective experiencings that we do. Our physical actions are themselves in part subjective phenomena, because actions are not simply body movements but also essentially involve intentions, beliefs about specific causation, and a sense of voluntariness. Thus, whatever else it is, psychology is inescapably the science of explaining the personally subjective. It is time for psychology to openly embrace its subjective subject-matter as such, which would open up a vast domain still waiting to be systematically studied. The physical actions of persons are not simply self-proclaiming. They often require being skillfully discerned and interpreted and can often be made more or differently meaningful by a somewhat different discernment or interpretation, even sometimes to the actors themselves. This is the fundamental reason that body movement description is insufficient for providing the terms for scientific accounts of how we live and enact our lives, there being in general no satisfactorily objective way, once the nature of what physical actions really are is made clear, to establish just what action or actions have occurred in any sequence of body movements. Whether or not a finger was moved from one position to another, with what velocity it was moved, and similar physical facts may be objectively established, but such facts do not themselves indicate the possible actions -if anywhich thereby have occurred, any more than the mere shape of written words or an audiogram of speech conveys the linguistic meanings of (or the actions implicit in) any particular writing or speech. Such considerations as those of actor-perceived situational contexts and actor’s cultural customs, body movement capabilities, personal experiencings of wants, intentions, beliefs. are properly taken into account in the defining \\server05\productn\T\THE\25-2\THE203.txt unknown Seq: 2 13-JUL-06 12:28 258 Journal of Theoretical and Philosophical Psy. Vol. 25, No. 2, 2005 and interpretation of human actions. This can sometimes be a rather
Intracoronary Autologous Cardiac Progenitor Cell Transfer in Patients With Hypoplastic Left Heart Syndrome: The TICAP Prospective Phase 1 Controlled Trial

Rationale: Hypoplastic left heart syndrome (HLHS) remains a lethal congenital cardiac defect. Recent studies have suggested that intracoronary administration of autologous cardiosphere-derived cells (CDCs) may improve ventricular function. Objective: The aim of this study was to test whether intracoronary delivery of CDCs is feasible and safe in patients with hypoplastic left heart syndrome. Methods and Results: Between January 5, 2011, and January 16, 2012, 14 patients (1.8±1.5 years) were prospectively assigned to receive intracoronary infusion of autologous CDCs 33.4±8.1 days after staged procedures (n=7), followed by 7 controls with standard palliation alone. The primary end point was to assess the safety, and the secondary end point included the preliminary efficacy to verify the right ventricular ejection fraction improvements between baseline and 3 months. Manufacturing and intracoronary delivery of CDCs were feasible, and no serious adverse events were reported within the 18-month follow-up. Patients treated with CDCs showed right ventricular ejection fraction improvement from baseline to 3-month follow-up (46.9%±4.6% to 52.1%±2.4%; P=0.008). Compared with controls at 18 months, cardiac MRI analysis of CDC-treated patients showed a higher right ventricular ejection fraction (31.5%±6.8% versus 40.4%±7.6%; P=0.049), improved somatic growth (P=0.0005), reduced heart failure status (P=0.003), and lower incidence of coil occlusion for collaterals (P=0.007). Conclusions: Intracoronary infusion of autologous CDCs seems to be feasible and safe in children with hypoplastic left heart syndrome after staged surgery. Large phase 2 trials are warranted to examine the potential effects of cardiac function improvements and the long-term benefits of clinical outcomes. Clinical Trial Registration: URL: http://www.clinicaltrials. gov. Unique identifier: NCT01273857.
Minimal Cellular Resolutions of Path Ideals

In this paper, we prove that the path ideals of both paths and cycles have minimal cellular resolutions. Specifically, these minimal free resolutions coincide with the Barile-Macchia resolutions for paths, and their generalized counterparts for cycles. Our result on cycles marks the first instance in the literature where the minimal free resolution of edge ideals of cycles has been established. Furthermore, edge ideals of cycles represent the first class of ideals that lack a minimal Barile-Macchia resolution, yet have a minimal generalized Barile-Macchia resolution.
A Modular Safety Filter for Safety-Certified Cyber-Physical Systems

Nowadays, many control systems are networked and embed communication and computation capabilities. Such control architectures are prone to cyber attacks on the cyberinfrastructure. Consequently, there is an impellent need to develop solutions to preserve the plant's safety against potential attacks. To ensure safety, this paper introduces a modular safety filter approach that is effective for a variety of cyber-attack types. This solution can be implemented in combination with existing control and detection algorithms, effectively separating safety from performance. The safety filter does not require information on the reliability of the received command or the feature of the used anomaly detector. It can be implemented in conjunction with high-performance, resilient controllers, to achieve both high performance during normal operation and safety during an attack. As an illustrative example, we have shown the effectiveness of the proposed design considering a multi-agent formation task involving 20 mobile robots. The simulation results testify that the safety filter operates effectively during false data injection and intelligent attacks.
The Relationship Between Resources and Performance in Further Education Colleges

This paper uses data on Further Education (FE) colleges in England to examine the relationship between resources and performance. We model the relationship between inspection scores and resource levels to investigate whether colleges with greater expenditures perform better in terms of their inspections scores. Our findings, similar to others using different functional specifications, are that there is no evident positive link between unit resource levels and performance, but that a positive link between size and performance can be substantiated. The implications of this for policy and future research are discussed.
Kurzbericht

Abstract Focus on surgical workflow A recent report predicted an increase in demand for surgical services to be as high as 14 to 47% in the workload of all surgical fields by 2020 [1]. Difficulties which are already now apparent in the OR will be amplified in the near future and it is therefore necessary to address this situation and to develop strategies to handle the workload. Appropriate use of information and communication technology (ICT) and mechatronic (MT) systems as part of a re-engineered workflow is considered by many experts a significant contribution to solve the problem. A number of special workshops and seminars which have addressed this and related problems have taken place in recent years in Europe and in the USA. The most notable recent meetings in the USA with a focus on surgical workflow issues were.
Weighted Spherical Harmonic Representation and Its Application to Cortical Analysis

We present a novel weighted spherical harmonic (SPHARM) representation of cortical surfaces and its application to a cortical thickness analysis in autism. The weighted-SPHARM is a hierarchical smoothing technique given as the solution to a parabolic partial differential equation. The weighted-SPHARM generalizes the classical-SPHARM with an additional parameter that modulates the high frequency content of data. We introduce a new algorithm called the iterative residual fitting (IRF) and address the problem of determining the optimal degree of the weighted-SPHARM. As an illustration, our unified framework has been applied in detecting the regions of abnormal behavior-structure correlation in a group of autistic subjects.
New approaches in the management of multiple sclerosis

Multiple sclerosis (MS) is a central nervous system chronic inflammatory disease that is characterized by an extensive and complex immune response. Scientific advances have occurred in immunology, pathophysiology, and diagnostic and clinical assessment tools, and recent discovery of unique therapeutic targets has spurred numerous Phase II and Phase III clinical trials. Reductions in MS relapse rates and improvements in T₂ or gadolinium-enhancing lesion burdens have been reported from Phase III trials that include fingolimod, alemtuzumab, cladribine, and rituximab. Promising Phase II trial data exist for teriflunomide, daclizumab, laquinimod, and fumarate. The optimism created by these favorable findings must be tempered with evaluation of the adverse effect profile produced by these new agents. Given the discovery of progressive multifocal leukoencephalopathy with the use of natalizumab, ongoing vigilance for rare and life-threatening reactions due to new agents should be paramount. Patients with MS often experience difficulty with ambulation, spasticity, and cognition. Recent clinical trial data from two Phase III dalfampridine-SR trials indicate certain patients receive benefits in ambulation. This article provides an overview of data from clinical trials of newer agents of potential benefit in MS.
Saturation and reification in adjectival diathesis1

The study of adjectival diathesis alternations lags behind the study of verbal diathesis and nominalization. This paper aims to diminish the gap by applying to the adjectival domain theoretical tools with proven success elsewhere. We focus on evaluative adjectives, which display a systematic alternation between a basic variant (John was rude) and a derived one (That was rude of John). The alternation brings about a cluster of syntactic and semantic changes – in the semantic type of the predicate, its valency and the mode of argument projection. We argue that the adjectival variants are related by the joint application of two operators: a lexical saturation operator (also seen in verbal passive) and a syntactic reification operator (also seen in nominalization). The analysis straightforwardly extends to similar alternations with Subject- and Object-Experiencer adjectives (proud, irritating). Among its important implications are (i) lexical saturation is not restricted to external arguments (internal ones may also be saturated), and (ii) ‘referential’ (R) roles are not restricted to nominal predicates (adjectives may assign them as well).
Identification of Culprit Lesions After Transient Ischemic Attack by Combined 18F Fluorodeoxyglucose Positron-Emission Tomography and High-Resolution Magnetic Resonance Imaging

Background and Purpose— Carotid endarterectomy is currently guided by angiographic appearance on the assumption that the most stenotic lesion visible at angiography is likely to be the lesion from which future embolic events will arise. However, risk of plaque rupture, the most common cause of atherosclerosis-related thromboembolism, is dictated by the composition of the plaque, in particular the degree of inflammation. Angiography may, therefore, be an unreliable method of identifying vulnerable plaques. In this study, plaque inflammation was quantified before endarterectomy using the combination of 18F fluorodeoxyglucose positron (FDG)-emission tomography (PET) and high-resolution MRI (HRMRI). Methods— Twelve patients, all of whom had suffered a recent transient ischemic attack, had a severe stenosis in the ipsilateral carotid artery, and were awaiting carotid endarterectomy underwent FDG-PET and HRMRI scanning. A semiquantitative estimate of plaque inflammation was calculated for all of the lesions identified on HRMRI. Results— In 7 of 12 patients (58%), high FDG uptake was seen in the lesion targeted for endarterectomy. In the remaining 5 patients, FDG uptake in the targeted lesion was low. In these 5 patients, 3 had nonstenotic lesions identified on HRMRI that exhibited a high level of FDG uptake. All 3 of the highly inflamed nonstenotic lesions were located in a vascular territory compatible with the patients’ presenting symptoms. Conclusions— Our data suggest that angiography may not always identify the culprit lesion. Combined FDG-PET and HRMRI can assess the degree of inflammation in stenotic and nonstenotic plaques and could potentially be used to identify lesions responsible for embolic events.
Compressive Sensing-Based Speech Enhancement

This study proposes a speech enhancement method based on compressive sensing. The main procedures involved in the proposed method are performed in the frequency domain. First, an overcomplete dictionary is constructed from the trained speech frames. The atoms of this redundant dictionary are spectrum vectors that are trained by the K-SVD algorithm to ensure the sparsity of the dictionary. For a noisy speech spectrum, formant detection and a quasi-SNR criterion are first utilized to determine whether a frequency bin in the spectrogram is reliable, and a corresponding mask is designed. The mask-extracted reliable components in a speech spectrum are regarded as partial observations and a measurement matrix is constructed. The problem can therefore be treated as a compressive sensing problem. The K atoms of a K-sparsity speech spectrum are found using an orthogonal matching pursuit algorithm. Because the K atoms form the speech signal subspace, the removal of the noise projected onto these K atoms is achieved by multiplying the noisy spectrum with the optimized gain that corresponds to each selected atom. The proposed method is experimentally compared with the baseline methods and demonstrates its superiority.
Efficient Data Access Paths for Mixed Vector-Relational Search

The rapid growth of machine learning capabilities and the adoption of data processing methods using vector embeddings sparked a great interest in creating systems for vector data management. While the predominant approach of vector data management is to use specialized index structures for fast search over the entirety of the vector embeddings, once combined with other (meta)data, the search queries can also become selective on relational attributes - typical for analytical queries. As using vector indexes differs from traditional relational data access, we revisit and analyze alternative access paths for efficient mixed vector-relational search. We first evaluate the accurate but exhaustive scan-based search and propose hardware optimizations and alternative tensor-based formulation and batching to offset the cost. We outline the complex access-path design space, primarily driven by relational selectivity, and the decisions to consider when selecting an exhaustive scan-based search against an approximate index-based approach. Since the vector index primarily avoids expensive computation across the entire dataset, contrary to the common relational knowledge, it is better to scan at lower selectivity and probe at higher, with a cross-point between the two approaches dictated by data dimensionality and the number of concurrent search queries.
Multiple Antenna Systems With Inherently Decoupled Radiators

In multiple antenna systems mutual coupling needs to be minimized. We propose an alternative novel decoupling technique, investigating several multiple antenna configurations for small handsets through measurements and numerical simulations. The influence of different novel designs on performance metrics such as total loss, antenna isolation and envelope correlation coefficient are investigated. By varying antenna impedance bandwidth and antenna location with respect to the handset, both planar inverted F antenna (PIFA) and inverted F antennas (IFA) were investigated in different UMTS frequency bands in proximity with the user's body. Results show that antennas may experience very different losses and envelope correlation coefficients depending on their relative position with respect to the handset, as the influence of the user's hand is not symmetrical in most cases. Narrow-band antennas are inherently decoupled when integrated on the same handset, while also other parameters such as frequency duplex distance and interaction with the user's body influence the mutual coupling.