Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigating paranormal phenomena: Functional brain imaging of telepathy

Aim: “Telepathy” is defined as “the communication of impressions of any kind from one mind to another, independently of the recognized channels of sense”. Meta-analyses of “ganzfield” studies as well as “card-guessing task” studies provide compelling evidence for the existence of telepathic phenomena. The aim of this study was to elucidate the neural basis of telepathy by examining an individual with this special ability. Materials and Methods: Using functional MRI, we examined a famous “mentalist” while he was performing a telepathic task in a 1.5 T scanner. A matched control subject without this special ability was also examined under similar conditions. Results: The mentalist demonstrated significant activation of the right parahippocampal gyrus after successful performance of a telepathic task. The comparison subject, who did not show any telepathic ability, demonstrated significant activation of the left inferior frontal gyrus. Conclusions: The findings of this study are suggestive of a limbic basis for telepathy and warrant further systematic research.
THE STAINING REACTIONS OF CHORDOMA 111 iw iT

Although chordoma is a rare tumour well over 300 cases have been reported, and the excellent published descriptions of both pathological and clinical features leave little to be added (Stewart, 1922; Cappell, 1928; Mabrey, 1935; Dahlin and MacCarty, 1952). The pathological diagnosis depends on the recognition of the physaliphorous or " bubble-bearing" cells which are the most striking feature of the histological picture. These cells (Fig. 1) often attain great size and usually occur in groups or cords with an epithelial pattern; they are distinguished by the presence of numerous clear vacuoles of varying size which are separated by faintly eosinophil cytoplasm, the cell having almost an aerated appearance. The groups of cells are separated by a matrix or ground substance which has a similar frothy vacuolated appearance to the cell cytoplasm. In some areas -mainly the older parts of the tumour-the cells collapse to nondescript stellate and fusiform varieties and are often separated quite widely by this frothy ground substance (Fig. 2). Biopsy from such an area presents considerable difficulty and has often led to an erroneous diagnosis of chondrosarcoma, especially when the tumour occurs in one of the less common sites such as a spinal vertebral body. In these circumstances some staining reaction which would distinguish between the ground substance of cartilage (more particularly neoplastic cartilage) and chordoma would be invaluable. The present paper presents from this point of view a study of material from six cases of chordoma.
Enhanced testing performance via unbiased test sets

The test generation task involves two separate questions which are: (1) What should the next test be? and (2) Have enough tests been selected to achieve an acceptable defective part level? Historically, the same fault set (usually the stuck-at-fault set) has been used to answer both questions. When both questions use the same fault set, a statistical bias is introduced to the answer of the second question. In this paper, we propose the use of independent models for answers to the two questions above, and we show, via probabilistic analysis as well as experiments, that the result is a superior test set selection method. <<ETX>>
An Adaptive CPU Scheduling for Embedded Operating Systems using Genetic Algorithms

This paper explains novel CPU scheduling approach for embedded operating Systems. In this approach we have used genetic algorithm (GA). Proposed Adaptive algorithm combines both EDF and GA based algorithms, Basically the new algorithm uses EDF algorithm but when the system becomes overloaded, it will switch to GA based scheduling algorithm. Again, when the overload disappears, the system will switch to EDF algorithm. Therefore the proposed algorithm takes the advantages of both algorithms and overcome their limitations. We have simulated, proposed adaptive algorithm along with both EDF and GA based algorithms for real time systems. The performance is measured in terms of Success Ratio and Effective CPU Utilization. From analysis and experiments it reveals that the proposed algorithm is fast as well as efficient in both under loaded and overloaded conditions.
Joint Range of Rényi Entropies

The exact range of the joined values of several R\'{e}nyi entropies is determined. The method is based on topology with special emphasis on the orientation of the objects studied. Like in the case when only two orders of R\'{e}nyi entropies are studied one can parametrize upper and lower bounds but an explicit formula for a tight upper or lower bound cannot be given.
Detection of anomalous events from unlabeled sensor data in smart building environments

This paper presents a robust unsupervised learning approach for detection of anomalies in patterns of human behavior using multi-modal smart environment sensor data. We model the data using a Gaussian Mixture Model, where the features are weighted based on their discriminative ability and are simultaneously clustered. The number of clusters in this approach is automatically chosen using the Minimum Message Length (MML) criterion. The weight of non-discriminative features is driven towards zero which results in a form of dimensionality reduction. Our results indicate that, in practical applications involving unlabeled, high-dimensional multi-modal sensor data from smart building environments, feature weighting achieves higher accuracy in detecting anomalous events with lower false alarm rates compared to using traditional Gaussian Mixtures.
Jazz: An Extensible 2D+Zooming Graphics Toolkit in Java

Jazz is a new general-purpose toolkit that supports applications using zooming object-oriented 2D graphics. It is built entirely in Java using Java2D, and thus runs on all platforms that support Java 2. It supports zooming, internal cameras, and lenses in a similar style to Pad++, but does so in a general purpose manner without a specific focus on zooming. Jazz is primarily a "scenegraph" for 2D graphics that is analogous to Sun's Java3D and SGI's OpenInventor in their support for 3D scenegraphs. This paper describes Jazz and discusses the issues of using a scenegraph for 2D graphics. We discuss the Jazz architecture, and how applications can build on top of it.
Impedance control of electro hydraulic servo system using input output linearization

In this paper, we present an impedance control method for electro hydraulic servo systems (EHSSs). The definition of impedance is a transfer function from external force to velocity error. By the proposed method, the transfer function from external force to velocity error becomes the desired transfer function. And we calculate the steady-state position and velocity error. Simulation results validate the effectiveness of proposed method and the steady-state position and velocity error.
Long-term chromospheric activity of non-eclipsing RS CVn-type stars

Context. The IUE database provides several UV high and low-resolution spectra of RS CVn-type stars from 1978 to 1996. In particular, many of these stars were monitored continuously during several seasons by IUE. Aims. Our main purpose is to study the short and long-term chromospheric activity of the RS CVn systems most observed by IUE: HD 22 468 (V711 Tau, HR 1099, K1IV+G5V), HD 21 242 (UX Ari, K0IV+G5V), and HD 224 085 (II Peg, K2IV). Methods. We first obtained the Mount Wilson index S from the IUE high and low-resolution spectra. Secondly, we used the Lomb
LibME—automatic extraction of 3D ligand‐binding motifs for mechanistic analysis of protein–ligand recognition

Identifying conserved binding motifs is an efficient way to study protein–ligand recognition. Most 3D binding motifs only contain information from the protein side, and so motifs that combine information from both protein and ligand sides are desired. Here, we propose an algorithm called LibME (Ligand‐binding Motif Extractor), which automatically extracts 3D binding motifs composed of the target ligand and surrounding conserved residues. We show that the motifs extracted by LibME for ATP and its analogs are highly similar to well‐known motifs reported by previous studies. The superiority of our method to handle flexible ligands was also demonstrated using isocitric acid as an example. Finally, we show that these motifs, together with their visual exhibition, permit better investigating and understanding of protein–ligand recognition process.
Analyzing business intelligence maturity

Business intelligence (BI) has fundamentally changed how companies conduct their business. In literature, the focus has been on volume-operation companies that provide services to millions of customers. In contrast, complex-systems companies have fewer customers and pursue customer needs by providing more customised products and services. This paper presents the results of a case study conducted at a complex-systems company, with the overall aim to identify how complex-systems companies may take advantage of BI. A framework was used to measure the BI maturity of the company. In addition, we also explain the current maturity level of the case company, based on critical factors for success adopted from the literature. In doing so, we also contribute important details regarding factors that must be considered by organisations, in order to leverage their analytical capability. Finally, we also propose topics that need to be further investigated, in order to increase current knowledge regarding BI usage and maturity in complex-systems companies.
Max Regional Aggregate over Sensor Networks

Nowadays, wireless sensor networks are widely used in many environmental monitoring applications. However, due to the limitation of the current hardware technology, sensors are often battery powered and it is very difficult to change batteries. Therefore, for applications over wireless sensor networks, it is a critical issue to save the energy of sensors. Many attempts have been made to answer various types of queries energy-efficiently, such as max, top-k, and skylines. However, all of them return the readings of individual sensors that satisfy the query constraint. In practice, query results based on individual sensor readings are unreliable because sensor readings are often noisy. Thus, in this paper, we present a new type of query, max aggregate query over a region (i.e. max regional aggregate), which aims to find a fixed-size region whose regional aggregate is the maximum among all the possible regions with the same size. Compared to traditional max queries, max regional aggregate is more reliable in detecting events. Designing an energy-efficient approach to answer max regional aggregate is non-trivial because a huge number of regions need to be investigated. Thus, in this paper, we propose a novel two-level sampling approach, with region and sensor sampling, to collect the sensor readings intelligently and compute the approximate max regional aggregate based on the collected results. Specifically, region sampling is used to select regions and sensor sampling isused to choose the sensors within a selected region. Our extensive simulation results demonstrate that the proposed two-level sampling approach can answer the max regional aggregate energy-efficiently with a desirable accuracy.
An Energy-Efficient MCDS-based Routing Algorithm for Wireless Sensor Networks: Learning Automata Approach

Wireless sensor networks which are used to monitor and control a specific area, are made of many small sensor nodes; they are compressed and spread in an environment. One of the most challenges in these types of networks is Energy limitation which has direct influence on sensor network lifetime. Unicast routing in wireless sensor networks is a way for data delivery to a receiver. In this paper we are intended to present a unicast routing algorithm in wireless sensor networks, and we make a virtual backbone out of Minimum Connected Dominating Set (MCDS). This virtual backbone is initiated according to Energy level, Neighboring, and distance from Sink node. So, to this end we use an algorithm based on learning automata named UMCDS- LA deal with the unicast routing problem. Finally, we simulate proposed method by ns2 simulator. Thus the results show high performance of the proposed algorithm. Streszczenie. W artykule zaprezentowano algorytm routowania typu unicast w sieci bezprzewodowej (ang. Wireless Sensor Network). Szkielet sieci oparty zostal na strukturze typu MCDS (ang. Minimum Connected Dominating Set). Do realizacji wykorzystano algorytm oparty na automacie uczącym sie UMCDS-LA. Metode przebadano na symulatorze ns2. (Energowydajny algorytm routowania w sieciach bezprzewodowych oparty na strukturze MCDS - automaty uczące sie)
Convergence of lateral dynamic measurements in the plasma membrane of live cells from single particle tracking and STED-FCS

Fluorescence correlation spectroscopy (FCS) in combination with the super-resolution imaging method STED (STED-FCS), and single-particle tracking (SPT) are able to directly probe the lateral dynamics of lipids and proteins in the plasma membrane of live cells at spatial scales much below the diffraction limit of conventional microscopy. However, a major disparity in interpretation of data from SPT and STED-FCS remains, namely the proposed existence of a very fast (unhindered) lateral diffusion coefficient, ⩾5 µm2 s−1, in the plasma membrane of live cells at very short length scales, ≈⩽ 100 nm, and time scales, ≈1–10 ms. This fast diffusion coefficient has been advocated in several high-speed SPT studies, for lipids and membrane proteins alike, but the equivalent has not been detected in STED-FCS measurements. Resolving this ambiguity is important because the assessment of membrane dynamics currently relies heavily on SPT for the determination of heterogeneous diffusion. A possible systematic error in this approach would thus have vast implications in this field. To address this, we have re-visited the analysis procedure for SPT data with an emphasis on the measurement errors and the effect that these errors have on the measurement outputs. We subsequently demonstrate that STED-FCS and SPT data, following careful consideration of the experimental errors of the SPT data, converge to a common interpretation which for the case of a diffusing phospholipid analogue in the plasma membrane of live mouse embryo fibroblasts results in an unhindered, intra-compartment, diffusion coefficient of ≈0.7–1.0 µm2 s−1, and a compartment size of about 100–150 nm.
How Much Do Public Schools Really Cost? Estimating the Relationship between House Prices and School Quality

This paper investigates the relationship between housing prices and the quality of public schools in the Australian Capital Territory. To disentangle the effects of schools and other neighbourhood characteristics on the value of residential properties, we compare sale prices of homes on either side of high school attendance boundaries. We find that a 5 percent increase in test scores (approximately one standard deviation) is associated with a 3.5 percent increase in house prices. Our result is in line with private school tuition costs, and accords with prior research from Britain and the United States. Estimating the effect of school quality on house prices provides a possible measure of the extent to which parents value better educational outcomes.
Reduced-Order Observer Design for Switched Descriptor Systems With Unknown Inputs

This paper presents a systematical reduced-order observer design method for a class of switched descriptor systems containing unknown inputs (UIs) in both the dynamic and the output equations. Generally speaking, when the output of the system contains UIs, the reduced-order observer design will become much more challenging. In order to overcome the difficulty brought by the UIs in the output, first, by introducing a new UI vector, a new equivalent system is obtained, which does not contain UIs in the corresponding output any more. Then, for the purpose of reduced-order observer design, the observer matching condition (OMC) and the minimal phase condition (MPC) are discussed, and it is shown that the new general system maintains both the OMC and the MPC. Subsequently, based on the discussions on the existence conditions, a reduced-order unknown input observer is developed to asymptotically estimate the state of the original system. Finally, an electronic circuit example is given to show the effectiveness of the proposed method.
Psychiatric evaluation of juvenile delinquents under probation in the context of recidivism

ABSTRACT OBJECTIVE: High rates of psychiatric disorders and comorbidities have been reported in the juvenile justice system, and both phenomena are thought to contribute to repetitive offending. Although extensive research on the prevalence of psychiatric disorders in juvenile offenders has been conducted in European countries and the USA, epidemiological research concerning this issue is limited in Turkish population. The aim of the present study is to examine psychiatric diagnoses, comorbidity patterns, psychometric properties, and the factors related to recidivism defined as reconvictions, in juveniles under probation in Turkey. METHODS: We conducted face-to-face interviews with volunteers. This study sample consisted of 55 individuals (Female/Male = 4/51) who were in the Istanbul Anatolian Probation Department. The participants’ age ranged from 14 to 18 years (mean age = 17.22 ± 0.62). Diagnoses were established based on the Kiddie Schedule for Affective Disorders and Schizophrenia for School Age Children Present and Lifetime Version. A detailed sociodemographic form, Wechsler Intelligence Scale, Child Depression Inventory, and Beck Anxiety Inventory were used for assessment. The subjects were divided into two groups based on the number of conviction: Group 1 consisted of 65% of the sample (n = 36) with one conviction and Group 2 consisted of 35% of the sample (n = 19) with more than one conviction. We examined the psychometric properties that might predict recidivism through the logistic regression analysis. RESULTS: We ascertained that 67.3% of the juveniles had at least one psychiatric disorder, and 45.5% had two or more comorbid psychiatric disorders. The most common diagnosis was attention deficit hyperactivity disorder (ADHD) (43.6%), and followed by depressive mood disorders (34.5%). Juveniles in Group 2 were less educated, had low levels of verbal, performance and total intelligence quotient (IQ) score, had more numbers of psychiatric diagnoses, particularly depressive mood disorders and history of substance use disorders (p < .05). Having a higher number of psychiatric diagnoses and having comorbidity of both externalizing (i.e. ADHD, conduct disorder) and internalizing disorders (i.e. depressive mood disorders, anxiety disorders) were significantly higher in Group 2 (p < .05). Total duration of education (OR = 0.470, 95% CI = 0.257–0.861, p < .05) and having at least one psychiatric disorder (OR = 10.64, 95% CI = 1.642–68.954, p < .05) were found to predict multiple convictions. CONCLUSION: Juveniles in the justice system are faced with multiple psychiatric disorders, along with social/environmental adversities. There is a need of a holistic approach addressing multiple areas to prevent repetitive offending behaviour. Accordingly, in addition to legal sanctions, evaluation and interventions regarding mental health will contribute to improve for both psychosocial well-being of delinquent juveniles and prevention strategies for recidivism.
LEARNING AND TEACHING " SCIENTIFIC CONCEPTS " : VYGOTSKY ' S IDEAS REVISITED

In his chapter in Thinking and Speech on the development of scientific concepts, Vygotsky (1987, chap.6, hereafter DSC) initiated a discussion of an issue that continues to be of fundamental importance for education, namely that of the relationship between the development of what might be called decontextualized, formal thinking and school instruction. However, despite the insightful and many-faceted nature of his exploration of this issue, I shall argue that the account he offers needs to be significantly enriched, first by setting it in the context of his other theoretical writings and, second, by expanding it to take account of more recent developments in the relevant fields. {1}
On the design of green reconfigurable router toward energy efficient internet

A great deal of research has contributed to the energy efficiency of battery-operated devices in the area of wireless communications, but recently, the energy consumption of the underlying network infrastructure has started to attract more attention as people have become aware of the significant fraction of energy consumed by the Internet of all the energy we consume. We argue that the architecture of routers in constructing the Internet can be improved so as to fully utilize chances to save energy related to transmission equipment. A green reconfigurable router is thus presented for this purpose.
Probabilistic Interpretations and Extensions for a Family of 2D PCA-style Algorithms

Recently there have been several 2D or higher-order PCAstyle dimensionality reduction algorithms, but they mostly lack probabilistic interpretations and are difficult to apply with, e.g., incomplete data. We propose a probabilistic framework to better understand the 2D and higher-order PCA-style algorithms, and show that it takes several existing algorithms as its (non-probabilistic) special cases. Efficient learning algorithms are proposed, and the stationary points are theoretically analyzed. Empirical studies on several benchmark data and real-world cardiac ultrasound images demonstrate the strength of this framework.
On the Feasibility of Large-Scale Infections of iOS Devices

While Apple iOS has gained increasing attention from attackers due to its rising popularity, very few large scale infections of iOS devices have been discovered because of iOS' advanced security architecture. In this paper, we show that infecting a large number of iOS devices through botnets is feasible. By exploiting design flaws and weaknesses in the iTunes syncing process, the device provisioning process, and in file storage, we demonstrate that a compromised computer can be instructed to install Apple-signed malicious apps on a connected iOS device, replace existing apps with attacker-signed malicious apps, and steal private data (e.g., Facebook and Gmail app cookies) from an iOS device. By analyzing DNS queries generated from more than half a million anonymized IP addresses in known botnets, we measure that on average, 23% of bot IP addresses demonstrate iOS device existence and Windows iTunes purchases, implying that 23% of bots will eventually have connections with iOS devices, thus making a large scale infection feasible.