Miracle-dz/UniFAR-FTUs huggingface dataset:
Home Photo Indexing using Learned Visual Keywords

With rapid advances in sensor, storage, processor, and communication technologies, consumers can now afford to create, store, process, and share large digital photo collections. With more and more digital photos accumulated, consumers need effective and efficient tools to index and retrieve relevant photos. In this paper, we propose a novel image representation called Visual Keyword Histogram (VKH) for content-based indexing and retrieval. Visual keywords are domain-relevant visual prototypes (e.g. faces, foliage, buildings etc) with both perceptual appearance and textual semantics. Collectively, VKHs are computed over spatial tessellation to represent the distribution of visual keywords in various parts of an image. To construct a vocabulary of visual keywords, an incremental neural network is adopted to learn visual keywords from examples. This allows us to build domain-specific visual vocabularies rapidly and incrementally. We demonstrate our approach on 2400 home photos with 15 semantic queries.
Loosely Coupled Optimistic Replication for Highly Available, Scalable Storage

People are becoming increasingly reliant on computing devices and are trusting increasingly important data to persistent storage. These systems should protect this data from failure and ensure that it is available anytime, from anywhere. Unfortunately, traditional mechanisms for ensuring high availability suffer from the complexity of maintaining consistent, distributed replicas of data. This paper describes Mammoth, a novel (cid:2)le system that uses a loosely-connectedset of nodes to replicate data and maintain consistency. The key idea of Mammoth is that (cid:2)les and directories are stored as histories of immutable versions and that all meta-data is stored in append-only change logs. Users specify availability policies for their (cid:2)les and the system uses these policies to replicate certain, but not necessarily all, versions to remote nodes to protect them from a variety of failures. Because (cid:2)le data is immutable, it can be freely replicated without complicating the (cid:2)le’s consistency. File and directory meta-data is replicated using an optimistic policy that allows partitioned nodes to read and write whatever (cid:2)le versions are currently accessible. When network partitions heal, inconsistent meta-data is reconciled by merging the meta-data updates made in each partition; con(cid:3)icting updates manifest as branches in the (cid:2)le’s or directory’s history and can thus can be further resolved by higher-level software or users. We describe our design and the implementation and performance of an early prototype.
Research on Failure Detector in Remote Disaster-tolerant System

Failure detector is one of the key components for remote disaster-tolerant systems. In this paper, a flexible hierarchical architecture is designed and the detection component is divided from decision-making. In doing so, failure detector can be applied to remote disaster-tolerant system and can meet the requirements of different applications. An adaptable failure detection algorithm is put forward considering message delay and message loss and clock synchronization. This algorithm can adapt itself to the change of network condition and applications’ requirements. The algorithm has been implemented in a remote disaster-tolerant system and the test results showed that the error rate is greatly decreased using the algorithm.
The Absorption of Talent into Finance: Evidence from U.S. Banking Deregulation

The U.S. banking sector has grown substantially since the 1970s and has become more skill-intensive over time. This paper exploits variation in banking deregulation across U.S. states between 1997 and 2008 to test whether the banking sector absorbs talent at the expense of the real sectors in the economy. I find that the relaxation of interstate branching restrictions disproportionately reduces the labour productivity of skill-intensive manufacturing industries. This result also holds if changes in bank lending following deregulation are controlled for. My findings suggest that banking deregulation increases the demand for skilled labour of banks. The diversion of skilled individuals into banks and away from real sectors leads to labour productivity declines especially in those industries which rely heavily on skilled labour.
Cerebral 1H MRS alterations in recreational 3,4‐methylenedioxymethamphetamine (MDMA, “ecstasy”) users

3,4‐Methylenedioxymethamphetamine (MDMA) is an illicit drug that has been associated with serotonergic axonal degeneration in animals. This study evaluates neurochemical abnormalities in recreational MDMA users. Twenty‐two MDMA users and 37 normal subjects were evaluated with magnetic resonance imaging (MRI) and proton magnetic resonance spectroscopy (1H MRS) in the mid‐frontal, mid‐occipital, and parietal brain regions. 1H MRS showed normal N‐acetyl (NA) compounds in all brain regions. The myo‐inositol (MI) concentration (+16.3%, P = 0.04) and the MI to creatine (CR) ratio (+14.1%, P = 0.01) were increased in the parietal white matter of MDMA users. The cumulative lifetime MDMA dose showed significant effects on [MI] in the parietal white matter and the occipital cortex. The normal NA concentration suggests a lack of significant neuronal injury in recreational MDMA users. However, the usage‐related increase in MI suggests that exposure to MDMA, even at recreational doses, may cause increased glial content. J. Magn. Reson. Imaging 1999;10:521–526. © 1999 Wiley‐Liss, Inc.
The role of MicroRNAs in Osteoclasts and Osteoporosis

Osteoclasts are the exclusive cells of bone resorption. Abnormally activating osteoclasts can lead to low bone mineral density, which will cause osteopenia, osteoporosis, and other bone disorders. To date, the mechanism of how osteoclast precursors differentiate into mature osteoclasts remains elusive. MicroRNAs (miRNAs) are novel regulatory factors that play an important role in numerous cellular processes, including cell differentiation and apoptosis, by post-transcriptional regulation of genes. Recently, a number of studies have revealed that miRNAs participate in bone homeostasis, including osteoclastic bone resorption, which sheds light on the mechanisms underlying osteoclast differentiation. In this review, we highlight the miRNAs involved in regulating osteoclast differentiation and bone resorption, and their roles in osteoporosis.
Ultrafast Long-Range Charge Separation in Organic Semiconductor Photovoltaic Diodes

Early Separation In photovoltaic devices, electrons excited by the absorption of light must travel across a junction, while the positively charged “holes” they leave behind effectively migrate in the opposite direction. If the electrons and holes do not separate efficiently, they can recombine and fail to produce any appreciable current. Gélinas et al. (p. 512, published online 12 December; see the Perspective by Bredas) studied this separation process by ultrafast optical absorption spectroscopy in thiophene-derived donor-fullerene acceptor systems common in organic photovoltaics and report a rate significantly faster than simple charge diffusion would suggest. The results implicate a coherent charge delocalization process, likely to involve fullerene π-electron states. Ultrafast spectroscopy shows electrons and holes separating faster than simple diffusion would imply in organic photovoltaics. [Also see Perspective by Bredas] Understanding the charge-separation mechanism in organic photovoltaic cells (OPVs) could facilitate optimization of their overall efficiency. Here we report the time dependence of the separation of photogenerated electron hole pairs across the donor-acceptor heterojunction in OPV model systems. By tracking the modulation of the optical absorption due to the electric field generated between the charges, we measure ~200 millielectron volts of electrostatic energy arising from electron-hole separation within 40 femtoseconds of excitation, corresponding to a charge separation distance of at least 4 nanometers. At this separation, the residual Coulomb attraction between charges is at or below thermal energies, so that electron and hole separate freely. This early time behavior is consistent with charge separation through access to delocalized π-electron states in ordered regions of the fullerene acceptor material.
Connective Tissue and Bacterial Deposits on Silicone Sheet and ePTFE Barrier Membranes in Guided Periodontal Tissue Regeneration

The aim of this study was to compare connective tissue and bacterial deposits on silicone sheets (SS) and expanded polytetrafluoroethylene membranes (ePTFE) used as barrier membranes in guided tissue regeneration (GTR) for periodontal treatment. Eighteen intrabony periodontal lesions from 18 patients were first surgically treated by GTR and either SS or ePTFE were used as barrier membranes. Four to six weeks after the first operation, membranes were retrieved from surgical sites and processed for the scanning electron microscopy. Quantitative study of deposits on the lesion-facing surfaces of membranes was performed. The differences between the number of fields of connective tissue and bacteria on SS and ePTFE were analyzed by the Chi-square test at the level of 0.05 significance. The result showed no significant difference between the number of fields of connective tissue on the surfaces of SS and ePTFE (p=0.875). However, the number of fields of bacteria found on SS were significantly less than those found on ePTFE (p<0.001). The comparable number of fields of connective tissue deposits on both types of membranes suggests that the degree of healing under both types of membranes was also comparable. Therefore, SS can be used as a barrier membrane in GTR for periodontal treatment.
Packet routing with arbitrary end-to-end delay requirements

We study the problem of scheduling packets to meet an arbitrary set of delay requirements. Consider a connectionoriented network in which a set of sessions is defined. Each session i follows a fixed route and requests an end-to-end delay requirement A;. The packet injections for each session are subject to a specified session rate and burst size; the packet movement is restricted to one packet per link per time step. If an arbitrary set of delay requirements is schedulable for every link in isolation and for every session in isolation, we present a simple distributed protocol in which every session i achieves a delay bound of O((a + log &)A;). Here, u is a term that depends logarithmically on the burst sizes; m is the number of links in the network and prnin is the smallest session rate. In addition, we show the existence of a schedule that achieves a hound of O(aAi). We also construct an example to show that the a factor cannot be removed in general. Hence, per-session schedulability and per-link schedulability is not sufficient to guarantee network schedulability for arbitrary delay requirements. This provides a contrast with previous work in that the bounds are not simply composed of a per-link delay bound and a per-session bound. Finally, we examine the problem of route selection in which the session routes are not given (I priori. Our aim is to choose the routes so that the delay requirements can be met.
Predicting Cross-Core Performance Interference on Multicore Processors with Regression Analysis

Despite their widespread adoption in cloud computing, multicore processors are heavily under-utilized in terms of computing resources. To avoid the potential for negative and unpredictable interference, co-location of a latency-sensitive application with others on the same multicore processor is disallowed, leaving many cores idle and causing low machine utilization. To enable co-location while providing QoS guarantees, it is challenging but important to predict performance interference between co-located applications. We observed that the performance degradation of an application can be represented as a piecewise predictor function of the aggregate pressures on shared resources from all cores. Based on this observation, we propose to adopt regression analysis to build a predictor function for an application. Furthermore, the prediction model thus obtained for an application is able to characterize its contentiousness and sensitivity. Validation using a large number of single-threaded and multi-threaded benchmarks and nine real-world datacenter applications on two different platforms shows that our approach is also precise, with an average error not exceeding 0.4 percent.
Performance evaluation and optimization of random memory access on multicores with high productivity

The slow progress in memory access latencies in comparison to CPU speeds has resulted in memory accesses dominating code performance. While architectural enhancements have benefited applications with data locality and sequential access, random memory access still remains a cause for concern. Several benchmarks have been proposed to evaluate the random memory access performance on multicore architectures. However, the performance evaluation models used by the existing benchmarks do not fully capture the varying types of random access behaviour arising in practical applications. In this paper, we propose a new model for evaluating the performance of random memory access that better captures the random access behaviour demonstrated by applications in practice. We use our model to evaluate the performance of two popular multicore architectures, the Cell and the GPU. We also suggest novel optimizations on these architectures that significantly boost the performance for random accesses in comparison to conventional architectures. Performance improvements on these architectures typically come at the cost of reduced productivity considering the extra programming effort involved. To address this problem, we propose libraries that incorporate these optimizations and provide innovatively designed programming interfaces that can be used by the applications to achieve good performance without loss of productivity.
A framework for visualization of soccer video using motion trajectories: presenting insights into tactics and performance

Recently, a fast-developing trend has been to enhance the experience of sporting events beyond the scores, player information and statistics associated with the sport. Systems have been designed to provide additional information, especially spatial data for better comprehension of broadcast events. The paper presents a visualization framework designed for deeper analysis of soccer video, providing further insights into tactics and performance. This framework analyzes broadcast soccer video to obtain motion trajectories of ball and players, and offers a rich set of visualization options based on this trajectory data. Our approach can be applied in (1) the goal event, to analyze team collaboration for training support, or (2) the foul event, to verify referee decisions, especially for some controversial situations.
The Bitter Barricading of Prostaglandin Biosynthesis Pathway: Understanding the Molecular Mechanism of Selective Cyclooxygenase-2 Inhibition by Amarogentin, a Secoiridoid Glycoside from Swertia chirayita

Swertia chirayita, a medicinal herb inhabiting the challenging terrains and high altitudes of the Himalayas, is a rich source of essential phytochemical isolates. Amarogentin, a bitter secoiridoid glycoside from S. chirayita, shows varied activity in several patho-physiological conditions, predominantly in leishmaniasis and carcinogenesis. Experimental analysis has revealed that amarogentin downregulates the cyclooxygenase-2 (COX-2) activity and helps to curtail skin carcinogenesis in mouse models; however, there exists no account on selective inhibition of the inducible cyclooxygenase (COX) isoform by amarogentin. Hence the computer-aided drug discovery methods were used to unravel the COX-2 inhibitory mechanism of amarogentin and to check its selectivity for the inducible isoform over the constitutive one. The generated theoretical models of both isoforms were subjected to molecular docking analysis with amarogentin and twenty-one other Food and Drug Authority (FDA) approved lead molecules. The post-docking binding energy profile of amarogentin was comparable to the binding energy profiles of the FDA approved selective COX-2 inhibitors. Subsequent molecular dynamics simulation analysis delineated the difference in the stability of both complexes, with amarogentin-COX-2 complex being more stable after 40ns simulation. The total binding free energy calculated by MMGBSA for the amarogentin-COX-2 complex was −52.35 KCal/mol against a binding free energy of −8.57 KCal/mol for amarogentin-COX-1 complex, suggesting a possible selective inhibition of the COX-2 protein by the natural inhibitor. Amarogentin achieves this potential selectivity by small, yet significant, structural differences inherent to the binding cavities of the two isoforms. Hypothetically, it might block the entry of the natural substrates in the hydrophobic binding channel of the COX-2, inhibiting the cyclooxygenation step. To sum up briefly, this work highlights the mechanism of the possible selective COX-2 inhibition by amarogentin and endorses the possibility of obtaining efficient, futuristic and targeted therapeutic agents for relieving inflammation and malignancy from this phytochemical source.
Finding Semantic Similarity in Raw Text: the Deese Antonyms

As more and more text becomes readily available in electronic form, much interest is being generated by finding ways of automatically extracting information from subsets of this text. While manual indexing and automatic keyword indexing are well known, both have drawbacks. Recent research on robust syntactic analysis and statistical correlations promises that some of the intuitive advantages of manual indexing can be retained in a fully automatic system. Here I present an experiment performed with my system SEXTANT which extracts semantically similar words from raw text. Using statistical methods combined with robust syntactic analysis, SEXTANT was able to find many of the intuitive pairings between semantically similar words studied by Deese [Deese, 1954].
Atmospheric Corrosion Modelling with SVM Based Feature Selection

Atmospheric corrosion has caused more and more losses and costs these years, so the world begin to pay much attention to this problem. In this paper, we mainly discuss the feature selection of a small subset of several important environmental factors from many relevant ones. With our experimental data with very small sample size, a model of corrosion rate is built. After specialized data preprocessing, we introduce the novel method of feature selection based on Support Vector Machine (SVM). We demonstrate experimentally that the factors selected by this algorithm yield better modelling precision. Least Square (LS) based feature selection method is also included in our experiment to reveal the superiority of SVM algorithm in our problem.
Tracer Leakage from Modeled Agulhas Rings

In a numerical, isopycnal, ocean model the mixing is investigated with the environment of two idealized Agulhas rings, one that splits, and one that remains coherent. The evolution of a passive tracer, initially contained within the rings, shows that tracer leakage is associated with the formation of filaments in the early stage of ring evolution. These filaments reach down to the thermocline. In the deepest layers leakage occurs on a larger scale. Self-advection of the rings is very irregular, and it is not possible to compute a Lagrangian boundary in order to estimate the transport of leakage from the rings. To describe the processes that govern tracer leakage, in a coordinate frame moving with the ring a kinematic separatrix is defined in the streamfunction field for the nondivergent flow. Initially, filaments arise because of the elongation of the ring, which is mainly governed by an m = 2 instability that is collaborating with differential rotation. Because of beta, the symmetry is destroyed related to the separatrix associated with a stagnation point in the flow. The filament upstream of the stagnation point grows much faster and is associated with the bulk of tracer leakage. Mixing is enhanced by time dependence of the separatrix. As a result, there are no large differences between the leakage from a coherent ring, where the m = 2 instability equilibrates, and from a splitting ring, where the m = 2 instability keeps growing, which confirms that the amount of leakage is mainly governed by the ring's initial deformation combined with unsteady self-advection of the ring and not by the splitting of the ring. The decay of tracer content in the thermocline shows that in the first months up to 40% of the ring water can be mixed with the environment. In deeper layers the decay of tracer content may reach up to 90%.
Spatio-temporal reasoning for traffic scene understanding

In this paper we introduce a system for semantic understanding of traffic scenes. The system detects objects in video images captured in real vehicular traffic situations, classifies them, maps them to the OpenCyc1 ontology and finally generates descriptions of the traffic scene in CycL or cvasi-natural language. We employ meta-classification methods based on AdaBoost and Random forest algorithms for identifying interest objects like: cars, pedestrians, poles in traffic and we derive a set of annotations for each traffic scene. These annotations are mapped to OpenCyc concepts and predicates, spatiotemporal rules for object classification and scene understanding are then asserted in the knowledge base. Finally, we show that the system performs well in understanding traffic scene situations and summarizing them. The novelty of the approach resides in the combination of stereo-based object detection and recognition methods with logic based spatio-temporal reasoning.
Professional relationships and decision making in social work: Lessons from a Scottish case study of secure accommodation decision making

There has been a great deal written in recent years about the complexities of social work decision making and the need for a more ecological conceptualisation of the decision-making task in child welfare and protection. This article outlines some of the findings from a PhD study of secure accommodation decision making in Scotland which sought to understand the dynamics of local social work decision making in cases where children and young people pose a significant risk to themselves and/or others. Observations of decision-making meetings, interviews and focus groups were used to develop a multidimensional perspective on decision-making practices in one large urban local authority. Professional relationships were found to impact on information gathering, ‘thinking through’ decisions and managing emotions, ‘working’ the decision-making system to the benefit of your referral and having your assessment accepted by others. Trust emerged as an important quality in relationships between professionals who share decision-making responsibilities. Drawing on theories of trust, relationships and decision making, the article challenges the dominant rational choice model of social work decision making and develops new links between theory and practice by highlighting the importance of understanding the impact of professional relationships when seeking to improve social work decision making. The article also emphasises the need for further research to enhance our understanding of the multiplicity of ways that professional relationships can impact on decision-making practice and its outcomes.