Miracle-dz/UniFAR-FTUs huggingface dataset:
Process Hijacking 1

Process checkpointing is a basic mechanism required for providing High Throughput Computing service on distributively owned resources. We present a new process checkpoint and migration technique, called process hijacking, that uses dynamic program re-writing techniques to add checkpointing capability to a running program. Process hijacking makes it possible to checkpoint and migrate proprietary applications that cannot be re-linked with a checkpoint library, and it makes it possible to dynamically hand off an ordinary running process to a distributed resource management system such as Condor. We discuss the problems of adding checkpointing capability to a program already in execution: (1) loading new code into the running process, and (2) replacing functions of the process with calls to dynamically loaded functions. We use the DynInst API process editing library, augmented with a new call for replacing functions, to solve these problems. We discuss problems associated with migrating a hijacked process: (1) safely restoring the dynamically assembled address space of the hijacked process from a checkpoint, and (2) preserving the uncheckpointable operating system state of the hijacked process for migration. We preserve uncheckpointable operating system state by spawning a shadow process from the hijacked process. We have used process hijacking to migrate a variety of programs, including a running, unmodified Java VM. We show that the migration performance of hijacking is comparable to that of Condor.
Additive Interaction of the Cannabinoid Receptor I Agonist Arachidonyl-2-chloroethylamide with Etomidate in a Sedation Model in Mice

Background:Both propofol and volatile anesthetics have been reported to interact with the endocannabinoid system. The purpose of this study was to evaluate the effect of selective agonists for cannabinoid receptor types 1 and 2 on etomidate-induced sedation. Methods:A controlled, blinded, experimental study was performed in 20 mice that received intraperitoneal injections of etomidate, the cannabinoid1 receptor agonist arachidonyl-2-chloroethylamide (ACEA), the cannabinoid2 receptor agonist JWH 133 alone, and both ACEA and JWH 133 combined with etomidate. The cannabinoid1 receptor antagonist AM 251 and the cannabinoid2 receptor antagonist AM 630 were administered 10 min before the delivery of ACEA and JWH 133, respectively. Each drug combination was applied to 6–8 mice of these 20 study animals. Sedation was monitored by a Rota-Rod (Ugo Basile, Comerio, Italy). Isobolographic analysis was used for evaluation of pharmacologic interaction. Results:Single drug administration of etomidate and ACEA produced dose- and time-dependent decreased time on the Rota-Rod (P < 0.05). No sedative effect was seen after JWH 133. Etomidate-induced sedation was significantly increased and prolonged with ACEA (P < 0.05), but not with JWH 133. Isobolographic analysis revealed an additive interaction between ACEA and etomidate that was antagonized by the cannabinoid1 receptor antagonist AM 251. The cannabinoid1 receptor antagonist had no effect on etomidate alone. Conclusions:Etomidate-induced sedation was increased and prolonged by activation of the cannabinoid1 receptor, but not of the cannabinoid2 receptor, in mice. However, this interaction was only additive.
The impact of adopting Basel III liquidity coverage ratio, stable funding ratio, and leverage ratio on lending in the Malawian banking sector

This paper examines the impact of adopting Basel III Liquidity Coverage Ratio, Stable Funding Ratio, and Leverage Ratio on lending in the Malawian banking sector. Malawi’s banking industry regulators are planning to transition to Basel III from the current Basel II regime. This paper pioneers an assessment of the implications of this move for the banking industry. The study uses monthly data for the period January 2010 to December 2022, the Feasible Generalised Least Square (FGLS) Panel Regression model with bank-specific variables (X) and macroeconomic controls (Z). The study finds that Tier 1 has a positive and significant impact on Malawi’s banking sector lending growth, while Tier 2 has a negative and insignificant impact on banking sector-wide lending growth effects. The non-risk weighted asset Basel III leverage ratios have significant and negative impacts on Malawi’s bank sector lending growth. And that the liquidity coverage ratio (LCR) had a positive and significant effect in explaining variability in lending in Malawi banking overall, while the introduction of the stable funding ratio (SFR) had a positive and significant impact on banking sector-wide lending growth effects. The study also found that the Basel III Capital and Liquidity Rules have different effects on firm-level lending for the 8 banks in Malawi.
Si-based unreleased hybrid MEMS-CMOS resonators in 32nm technology

This work presents the first unreleased Silicon resonators fabricated at the transistor level of a standard CMOS process, and realized without any release steps or packaging. These unreleased bulk acoustic resonators are driven capacitively using the thin gate dielectric of the CMOS process, and actively sensed with a Field Effect Transistor (FET) incorporated into the resonant body. FET sensing using the high fT, high performance transistors in CMOS amplifies the mechanical signal before the presence of parasitics. This enables RF-MEMS resonators at orders of magnitude higher frequencies than possible with passive devices. First generation CMOS-MEMS Si resonators with Acoustic Bragg Reflectors are demonstrated at 11.1 GHz with Q~17 and a total footprint of 5μm × 3μm using IBM's 32nm SOI technology.
Dwq : Esprit Long Term Research Project, No 22469 What Can Knowledge Representation Do for Semi-structured Data? What Can Knowledge Representation Do for Semi-structured Data?

The problem of modeling semi-structured data is important in many application areas such as multimedia data management, biological databases, digital libraries, and data integration. Graph schemas (Buneman et al. 1997) have been proposed recently as a simple and elegant formalism for representing semistructured data. In this model, schemas are represented as graphs whose edges are labeled with unary formulae of a theory, and the notions of conformance of a database to a schema and of subsumption between two schemas are defined in terms of a simulation relation. Several authors have stressed the need of extending graph schemas with various types of constraints, such as edge existence and constraints on the number of outgoing edges. In this paper we analyze the appropriateness of various knowledge representation formalisms for representing and reasoning about graph schemas extended with constraints. We argue that neither First Order Logic, nor Logic Programming nor Frame-based languages are satisfactory for this purpose, and present a solution based on very expressive Description Logics. We provide techniques and complexity analysis for the problem of deciding schema subsumption and conformance in various interesting cases, that differ by the expressive power in the specification of constraints.
Visual Analysis of Large Graphs: State‐of‐the‐Art and Future Research Challenges

The analysis of large graphs plays a prominent role in various fields of research and is relevant in many important application areas. Effective visual analysis of graphs requires appropriate visual presentations in combination with respective user interaction facilities and algorithmic graph analysis methods. How to design appropriate graph analysis systems depends on many factors, including the type of graph describing the data, the analytical task at hand and the applicability of graph analysis methods. The most recent surveys of graph visualization and navigation techniques cover techniques that had been introduced until 2000 or concentrate only on graph layouts published until 2002. Recently, new techniques have been developed covering a broader range of graph types, such as time‐varying graphs. Also, in accordance with ever growing amounts of graph‐structured data becoming available, the inclusion of algorithmic graph analysis and interaction techniques becomes increasingly important. In this State‐of‐the‐Art Report, we survey available techniques for the visual analysis of large graphs. Our review first considers graph visualization techniques according to the type of graphs supported. The visualization techniques form the basis for the presentation of interaction approaches suitable for visual graph exploration. As an important component of visual graph analysis, we discuss various graph algorithmic aspects useful for the different stages of the visual graph analysis process. We also present main open research challenges in this field.
Estimating Various Kinds of Peer Effects on Academic Performance ∗ †

This paper explicitly models peer network formation and explores different channels through which peer effects influence student achievement. Using unique data from a survey I designed and implemented for this study, the “Secondary Education Survey in Hong Kong”(SESHK), I estimate an econometric model to show how peer connections are formed and quantify peer effects. This paper focuses on four separate types of peer networks: friends, studymates, emotional supporters, and seatmates. Additionally, students can be affected by their peers through three different channels, namely cognitive abilities, personality traits, and behavioral spillovers. I estimate the magnitudes of these peer effects on academic performance through all three channels and all four networks. Peer effects are identified through a combination of explicitly modeling peer selection (see Brock and Durlauf (2003)) and additional set of instruments available in my data. Empirical results show that friends and studymates are endogenously formed which lead to overestimation of peer effects in traditional exogenous peer formation models. All investigated peer types show positive peer effects but the effect for seating proximity is relatively weaker. Peers are also found to have significant effects through particular cognitive abilities or personality traits. Smart studymates and conscientious friends positively affect a student’s mathematics score, while conscientious studymates and smart friends do not have such an effect. The results show that understanding the formation of different types of peers is important in peer effect estimation. JEL Classification Numbers: D85, I21
DAEDALUS at PAN 2014: Guessing Tweet Author's Gender and Age

This paper describes our participation at PAN 2014 author profiling task. Our idea was to define, develop and evaluate a simple machine learning classifier able to guess the gender and the age of a given user based on his/her texts, which could become part of the solution portfolio of the company. We were interested in finding not the best possible classifier that achieves the highest accuracy, but to find the optimum balance between performance and throughput using the most simple strategy and less dependent of external systems. Results show that our software using Naive Bayes Multinomial with a term vector model representation of the text is ranked quite well among the rest of participants in terms of accuracy.
Frequency-domain Compressive Channel Estimation for Frequency-Selective Hybrid mmWave MIMO Systems

Channel estimation is useful in millimeter wave (mmWave) MIMO communication systems. Channel state information allows optimized designs of precoders and combiners under different metrics such as mutual information or signal-to-interference-noise (SINR) ratio. At mmWave, MIMO precoders and combiners are usually hybrid, since this architecture provides a means to trade-off power consumption and achievable rate. Channel estimation is challenging when using these architectures, however, since there is no direct access to the outputs of the different antenna elements in the array. The MIMO channel can only be observed through the analog combining network, which acts as a compression stage of the received signal. Most of prior work on channel estimation for hybrid architectures assumes a frequency-flat mmWave channel model. In this paper, we consider a frequency-selective mmWave channel and propose compressed-sensing-based strategies to estimate the channel in the frequency domain. We evaluate different algorithms and compute their complexity to expose trade-offs in complexity-overhead-performance as compared to those of previous approaches.
Music Tempo (Speed) Classification

Music tempo (speed) is one of the most important features of a song. With successful classification of the tempo of song, content-based music browsing may utilize this feature and search/recommend songs in the same category of tempo. With some paper survey we noticed that prior works were focused on the numerical tempo value instead of the human perceptual speed of song. We proposed Inter-Onset Interval (IOI) reliability feature to present a soft tempo information for SVM. The onset detection algorithm in [4] was implemented to extract the beat onset timing, and the detection result is applied to SVM [6] as training features. The model trained via SVM can classify slow and medium songs with high accuracy; however, the fast songs are not highly correctly classified. We consider improving the feature for fast songs as future work.
Gossip vs. Markov Chains, and Randomness-Efficient Rumor Spreading

We study gossip algorithms for the rumor spreading problem which asks one node to deliver a rumor to all nodes in an unknown network, and every node is only allowed to call one neighbor in each round. In this work we introduce two fundamentally new techniques in studying the rumor spreading problem: First, we establish a new connection between the rumor spreading process in an arbitrary graph and certain Markov chains. While most previous work analyzed the rumor spreading time in general graphs by studying the rate of the number of (un-)informed nodes after every round, we show that the mixing time of a certain Markov chain suffices to bound the rumor spreading time in an arbitrary graph. Second, we construct a reduction from rumor spreading processes to branching programs. This reduction gives us a general framework to derandomize the rumor spreading and other gossip processes. In particular, we show that, for any n-vertex expander graph, there is a protocol which informs every node in O(log n) rounds with high probability, and uses O(log n · log log n) random bits in total. The runtime of our protocol is tight, and the randomness requirement of O(log n · log log n) random bits almost matches the lower bound of Ω(log n) random bits. We further show that, for many graph families (defined with respect to the expansion and the degree), O(poly log n) random bits in total suffice for fast rumor spreading. These results give us an almost complete understanding of the role of randomness in the rumor spreading process, which was extensively studied over the past years.
Current status of fish diversity of Barganat Dam North Waziristan Agency, KPK, Pakistan

The objective of the research work was to find out the diversity of fish fauna of bargant dam locate din North Waziristan Agency, Federally Administered Tribal Areas, Pakistan. In the present study 10 species were identified Barilius vagra, Cyprinus carpio, Puntius sarana, Cirrhinus mrigala, Ctenopharyngodon idella, Labeo rohita, Hypophthalmichthys molitrix, Oreochromis niloticus, Oreochromis aureus, Tor tor, so from the present it may be concluded that barganat dam is favorable for fish survival and hatchery.
Upscaling of mass transfer rate coefficient for the numerical simulation of dense nonaqueous phase liquid dissolution in heterogeneous aquifers

Mass transfer from entrapped dense nonaqueous phase liquids (DNAPLs) in heterogeneous aquifers takes place in natural, three‐dimensional groundwater flow fields. However, mass transfer processes are characterized in the laboratory in columns or flow cells under conditions of one‐dimensional or two‐dimensional water flow. Dissolution data generated in these test systems are used to determine empirical parameters of correlations that relate a dimensionless form of a mass transfer coefficient (Sherwood number) to other dimensionless groups that capture the basic processes contributing to mass transfer (e.g., Reynolds and Schmidt numbers). These phenomologically based empirical correlations, which are referred to as Gilland‐Sherwood models, are not directly applicable in predicting the dissolution of DNAPLs in the field as they do not capture the effects of aquifer heterogeneity and DNAPL entrapment morphology (referred to as DNAPL entrapment architecture). Numerical simulation of DNAPL dissolution requires the discretization of the problem domain into computational grid blocks and assignment of an effective mass transfer coefficient to each of these blocks containing DNAPL. A methodology for upscaling is needed to determine the grid‐scale effective mass transfer coefficient from the laboratory‐determined empirical correlations. It is our hypothesis that the upscaled effective mass transfer coefficient needs to contain information on the field‐scale heterogeneity and DNAPL entrapment architecture. This hypothesis was tested through a Monte‐Carlo‐based numerical experiment using a laboratory‐validated dissolution model with the goal of developing and testing an upscaling method. The developed upscaling method involves the use of geostatistical parameters that capture the aquifer heterogeneity and the DNAPL entrapment architecture. These parameters were determined to be the variance of log hydraulic conductivity, correlation lengths, and the normalized second moments of DNAPL mass distribution in the entrapment zone. Monte Carlo numerical simulation experiments combined with inverse modeling were used in this theoretical development and to determine parameters of the proposed upscaled Gilland‐Sherwood mass transfer correlation. Through these numerical modeling studies, the upscaled mass transfer correlation was successfully verified. Sensitivity analyses indicate that the normalized second moment, which describes the spreading of DNAPL mass in the vertical directions, was the most sensitive parameter in simulating the mass transfer at large scales.
Intravenous thrombolysis in a patient with left atrial myxoma with acute ischemic stroke

Intravenous thrombolysis (IVT) is an accepted therapy in patients with acute ischemic stroke presenting within 3-4.5 hours of symptom onset. Selection of the patient for thrombolysis depends on the careful assessment for the risk of post thrombolysis symptomatic haemorrhage (6.2-8.9%) which may be fatal. Atrial myxomas which are the commonest tumors of the heart are associated with stroke due to tumor/clot embolism. There are very few case reports of IVT and its outcome in patients with atrial myxoma with stroke. Some have reported successful thrombolysis, while others have reported intracerebral bleeding. In this report we describe our experience of IVT in atrial myxoma patient with ischemic stroke and review the relevant literature.
The Influence of Servant Leadership on The Character of Teachers at Catholic Junior High School Stella Maris Tomohon

Servant Leadership is a leadership concept oriented towards serving others. The practice of Servant Leadership is also carried out by teachers in schools, with each having their own unique characteristics. This research aims to understand the reality of Servant Leadership and teacher characteristics, as well as to analyze whether there is an influence of servant leadership on teacher characteristics at Catholic Junior High School Stella Maris Tomohon. This research is of the quantitative type, with the research variables being Servant Leadership (X) and Teacher Characteristics (Y). Data were collected using questionnaires. The analysis technique used was simple regression analysis. The results of hypothesis testing show that the Servant Leadership variable (X) has a significant positive influence on the Teacher Characteristics variable (Y). This is because the significance value 0.014 < probability 0.05 and the calculated T value is greater than the tabled T value 2.034 (3.138 < 2.034). For leaders at Catholic Junior High School Stella Maris Tomohon, it is important to consider input from others, especially teachers and staff. For teachers at Catholic Junior High School Stella Maris Tomohon, it is important to always pay attention to their characteristics as teachers, which include being humble, skilled at managing time, respecting the process, being open-minded, and being confident as important indicators in shaping teacher characteristics.
Cloud removal for hyperspectral remotely sensed images based on hyperspectral information fusion

ABSTRACT Hyperspectral remote sensing plays an important role in a wide variety of fields. However, its specific application for land surface analysis has been constrained due to the different shapes of thick, opaque cloud cover. The reconstruction of missing information obscured by clouds in remote-sensing images is an area of active research. However, most of the available cloud-removal methods are not suitable for hyperspectral images, because they lose the spectral information which is very important for hyperspectral analysis. In this article, we developed a new spectral resolution enhancement method for cloud removal (SREM-CR) from hyperspectral images, with the help of an auxiliary cloud-free multispectral image acquired at different times. In the fixed hyperspectral image, spectra of the cloud cover pixels are reconstructed depending on the relationship between the original hyperspectral and multispectral images. The final resulting image has the same spectral resolution as the original hyperspectral image but without clouds. This approach was tested on two experiments, in which the results were compared by visual interpretation and statistical indices. Our method demonstrated good performance.
A novel algorithm to remove electrical cross‐talk between surface EMG recordings and its application to the measurement of short‐term synchronisation in humans

Pairs of discharges of single motor units recorded in the same or different muscles often show synchronisation above chance levels. If large numbers of units are synchronous within and between muscles then the synchrony will be measurable in population recordings such as surface EMG. Measuring synchrony between surface EMG recordings has a number of practical and scientific advantages compared with single motor units recorded from intramuscular electrodes. However, the measurement of such synchrony in the time domain between surface EMGs is complicated because the recordings are contaminated by electrical cross‐talk. In this study we recorded surface EMG simultaneously from five hand and forearm muscles during a precision grip task. Using a novel ‘blind signal separation’ algorithm, we were able to remove electrical cross‐talk. The cross‐talk‐corrected EMGs could then be used to assess task‐dependent modulation in both oscillatory (15‐30 Hz) and non‐oscillatory synchrony (all other frequencies). In agreement with previous studies, the oscillatory component was maximal during steady holding but abolished during movement. By contrast, the non‐oscillatory component of the EMG synchrony appeared remarkably constant throughout all phases of the task. We conclude that surface EMG recordings can be of considerable use in the assessment of population synchrony changes, providing that electrical cross‐talk between nearby channels is removed using a statistical signal processing technique. Our results show a striking difference in the task‐dependent modulation of oscillatory and non‐oscillatory synchrony between muscles during a dynamic precision grip task.