Miracle-dz/UniFAR-FTUs huggingface dataset:
Critical Analysis of Middleware Architectures for Large Scale Distributed Systems

Distributed computing is increasingly being viewed as the next phase of Large Scale Distributed Systems (LSDSs). However, the vision of large scale resource sharing is not yet a reality in many areas - Grid computing is an evolving area of computing, where standards and technology are still being developed to enable this new paradigm. Hence, in this paper we analyze the current development of middleware tools for LSDS, from multiple perspectives: architecture, applications and market research. For each perspective we are interested in relevant technologies used in undergoing projects, existing products or services and useful design issues. In the end, based on this approach, we draw some conclusions regarding the future research directions in this area.
Catching Falling Knives: Speculating on Market Overreaction

Market participants often invest in order to acquire information that pertains to the market itself (e.g. order flow) rather than to fundamentals. This enables them to infer more information from past trades. I show that agents trading on such information, typically high-frequency traders, decrease the likelihood of short-lived mispricings by trading against price pressure. In the long-run however, such countervailing speculation amounts to signal-jamming, slowing down price discovery. These traders insure the market against short-run crashes by "catching falling knives". Higher adverse selection and slower convergence form the "premium" paid by other market participants. JEL Classification: D82, G0, G12, G14
Optimizing Single-Phase Downloads over Random Duration Links in Mobile Networks

Short range vehicle to vehicle and device to device communications are of growing interest due to their utility for vehicular safety and infotainment applications as well as for improving the capacity of cellular networks. These mobile systems are characterized by ephemeral, stochastic links. We consider a fundamental problem in this domain — how to maximize the amount of useful content downloaded by a client from a server over an encounter that lasts a random amount of time. We assume that the distribution of link duration is known or estimated a priori based on historical as well as real-time measurements. We present MERLIN (Maximum Expected download over Random LINks), a single-phase file request protocol that is provably optimal. We evaluate MERLIN comprehensively via simulations based on both ideal link duration distributions as well as empirical distributions obtained from real vehicular mobility traces (from Taxis in Shanghai and Buses in Chicago).
Load Balancing in Wireless Mesh Network: a Survey

Wireless Mesh network (WMN) is a state of the art networking standard for next generation of wireless network. The construction of these networks is basis of a network of wireless routers witch forwarding each other’s packets in a multi-hop manner. All users in the network can access the internet via Gateways nodes. Because of the high traffic load towards gateway node, it will become congested. A load balancing mechanism is required to balance the traffic among the gateways and prevent the overloading of any gateway. In this paper, weinvestigatedifferent load balancing techniques in wireless mesh networks to avoid congestion in gateways,as well as we survey the effective parameters that is used in these techniques.
Basic symptoms and ultrahigh risk criteria: symptom development in the initial prodromal state.

Symptom development during the prodromal phase of psychosis was explored retrospectively in first-episode psychosis patients with special emphasis on the assumed time-related syndromic sequence of "unspecific symptoms (UN)-predictive basic symptoms (BS)-attenuated psychotic symptoms (APS)-(transient) psychotic symptoms (PS). " Onset of syndromes was defined by first occurrence of any of their respective symptoms. Group means were inspected for time differences between syndromes and influence of sociodemographic and clinical characteristics on the recalled sequence. The sequence of "UN-BS/APS-PS" was clearly supported, and both BS and, though slightly less, APS were highly sensitive. However, onset of BS and APS did not show significant time difference in the whole sample (N = 126; 90% schizophrenia), although when each symptom is considered independently, APS tended to occur later than first predictive BS. On descriptive level, about one-third each recalled an earlier, equal and later onset of BS compared with APS. Level of education showed the greatest impact on the recall of the hypothesized sequence. Thereby, those with a higher school-leaving certificate supported the assumed sequence, whereas those of low educational background retrospectively dated APS before BS. These findings rather point out recognition and recall bias inherent to the retrospective design than true group characteristics. Future long-term prospective studies will have to explore this conclusively. However, as regards the criteria, the results support the notion of BS as at least a complementary approach to the ultrahigh risk criteria, which may also allow for an earlier detection of psychosis.
Toward flexible control of the temporal mapping from concurrent program events to animations

As parallel and distributed computers become more widely available and used, the already important process of understanding and debugging concurrent programs will rake on even greater importance. We believe that visualization can help in the process. We discuss heretofore unaddressed issues in the visualization of concurrent programs, and present the Animation Choreographer. The Animation Choreographer allows users to view, manipulate, and explore the set of alternate feasible orderings of the program execution under study, both through the Choreographer interface and in the context of the selected visualizations, thus providing the user with a variety of temporal perspectives on the computation. <<ETX>>
Face recognition using Deep PCA

In this paper, we propose a new deep learning method called Deep PCA (DPCA) for face recognition. Our method performs deep learning through hierarchically projecting face image vectors to different feature subspaces and obtaining the representations from different projections. Specifically, we perform a two-layer ZCA whitening plus PCA structure for learning hierarchical features. The whole feature representation of each face image can be extracted by concatenating the representations from the first and second layers. Our approach learns deep representations from the data, by utilizing information from the first layer to produce a new and different representation, making it more discriminative. Experimental results on the widely used FERET and AR databases are presented to show the efficiency of the proposed approach.
Development of Interactive Multimedia Courseware (e-CRAFT) for Craft Education.

The way of teaching and learning traditional crafts have always used traditional apprenticeship learning methods where the expert facilitates transfer of practice skill sets to novices. As a craft has been taught in conventional approach, the students and experts have been facing several problems especially when expert needs to teach a group of students. An appropriate mapping of craft education and Information and Communication Technologies using Multimedia technology for instance, has the potential in transforming traditional craft learning into more flexible environment. This paper reports on a research project on development of an interactive multimedia courseware package for teaching and learning traditional craft called e-CRAFT. The e-CRAFT is specially designed for songket weaving course taught to certificate and diploma students from Fakulti Seni Kraf Tenunan in their first year study at Institut Kraf Negara, Malaysia (National Craft Institute). The courseware was developed in a web-based environment and overall development process was based on the Dick and Carey's process model and conceptual Instructional Design framework. It is made up of eight learning modules: Introduction, Materials & Tools, Knowing Motifs, Learn How to Weave, Quizzes & Test, Online Discussion, Glossary and Help module. In order to test whether the courseware is suitable in terms of usability, pilot testing was done to a sample of 10 students. The results from pilot test received positive feedback which signifies the courseware is considered acceptable for effectiveness study and help for further improve of the e-CRAFT courseware.
Reinforcement learning and automatic categorization

The categorization process defines sensor and action categories from elementary sensor readings and basic actions so that the necessary elements for solving a task are correctly perceived and manipulated. In reinforcement learning, a previous categorization process is needed to define sensor and action categories with special requirements that we analyze and that, in general, are difficult to achieve, especially in complex tasks such as those that arise when working with autonomous robots. We show how these special requirements should be relaxed and we sketch a reinforcement learning algorithm that uses a less restrictive form of sensory categorization than existing algorithms. Additionally, we show how a given sensory categorization can be improved so that it better fits the demands of the previous algorithm.
Novel outer bounds and capacity results for the interference channel with conferencing receivers

Capacity bounds for the two-user interference channels with cooperative receivers via conferencing links of finite capacities are investigated. Capacity results known for these communication scenarios are limited to a very few special cases of the one-sided channels. One of the major challenges in analyzing such cooperative networks is how to establish efficient capacity outer bounds for them. In this paper, by applying new techniques, novel capacity outer bounds are established for the interference channels with conferencing receivers. Using the outer bounds, several new capacity results are proved for interesting channels with unidirectional cooperation in strong and mixed interference regimes. A fact is that a conferencing link (between receivers) may be utilized to provide one receiver with information about its corresponding signal or its non-corresponding signal (interference signal). As an interesting consequence, it is demonstrated that both strategies can be helpful to achieve capacity. Lastly, for the case of Gaussian interference channel with conferencing receivers, it is argued that our outer bound is strictly tighter than the previous one derived by Wang and Tse.
Pokémon DRIVE: towards increased situational awareness in semi-automated driving

Recent advances in vehicle automation have led to excitement and discourse in academia, industry, the media, and the public. Human factors such as trust and user experience are critical in terms of safety and customer acceptance. One of the main challenges in partial and conditional automation is related to drivers' situational awareness, or a lack thereof. In this paper, we critically analyse state of the art implementations in this arena and present a proactive approach to increasing situational awareness. We propose to make use of augmented reality to carefully design applications aimed at constructs such as amplification and voluntary attention. Finally, we showcase an example application, Pokémon DRIVE, that illustrates the utility of our proposed approach.
Gender discrimination in biological motion displays based on dynamic cues

Studies of human locomotion have found that male and female walkers differ in terms of lateral body sway, with males tending to swing their shoulders from side to side more than their hips, and females tending to swing their hips more than their shoulders. Experiments reported here demonstrate that naive viewers can identify the gender of the figure in a biological motion display very reliably when the display contains gender-specific lateral body sway. Sensitivity to gender is high even for displays containing only a fraction of a step cycle. This dynamic cue dominates structural cues based on torso shape (‘centre-of-moment’) when the cues are set in opposition. It is mediated by gender-specific differences in the velocity of shoulder and hip dots, not by positional differences in shoulder and hip dots during the step cycle.
The fundamental plane of galaxy clusters.

In the three—dimensional space defined by the logarithms of central velocity dispersion σ, effective radius R e and mean effective surface brightness I e, elliptical galaxies are confRned in a narrow plane (Dressler et al. 1987; Djorgovski & Davis 1987). Here we discuss the observational evidence for the existence of an analogous relation for galaxy clusters (Schaeffer et al., 1993).
Predictive and Prognostic Biomarkers of Respiratory Diseases due to Particulate Matter Exposure

Air pollution is getting severe and concerns about its toxicity effects on airway and lung disease are also increasing. Particulate matter (PM) is major component of air pollutant. It causes respiratory diseases, such as asthma, chronic obstructive pulmonary disease, lung cancer, and so on. PM particles enter the airway and lung by inhalation, causing damages to them. Especially, PM2.5 can penetrate into the alveolus and pass to the systemic circulation. It can affect the cardiopulmonary system and cause cardiopulmonary disorders. In this review, we focused on PM-inducing toxicity mechanisms in the framework of oxidative stress, inflammation, and epigenetic changes. We also reviewed its correlation with respiratory diseases. In addition, we reviewed biomarkers related to PM-induced respiratory diseases. These biomarkers might be used for disease prediction and early diagnosis. With recent trend of using genomic analysis tools in the field of toxicogenomics, respiratory disease biomarkers associated with PM will be continuously investigated. Effective biomarkers derived from earlier studies and further studies might be utilized to reduce respiratory diseases.
MeDetect: Domain Entity Annotation in Biomedical References Using Linked Open Data

Recently, with the ever-growing use of textual medicine records, annotating domain entities has been regarded as an important task in the biomedical field. On the other hand, the process of interlinking open data sources is being actively pursued within the Linking Open Data (LOD) project. The number of entities and the number of properties describing semantic relationships between entities within the linked data cloud are very large. In this paper, we propose a knowledge-incentive approach based on LOD for entity annotation in the biomedical field. With this approach, we implement MeDetect, a prototype system to solve the problems mentioned above. The experimental results verify the effectiveness and efficiency of our approach.
State High School Exit Exams: Trends in Test Programs, Alternate Pathways, and Pass Rates.

Most of the states require students to pass the exams in certain subject areas with specific cut scores, but some states permit students to graduate without passing every subject. For example, Maryland employs a compensatory scoring system so students may meet the graduation testing requirement by achieving a combined passing score on the four tests. Since May 2008, Alabama has adopted the credit-based endorsement system wherein students are required to take tests in five subject areas, but only need to pass three (reading, mathematics, and one other in science, language arts, or social studies) to graduate with “diplomas with endorsements. ” 9 Ohio and Texas allow students who have passed part of EOC exams to graduate.
On the Measurement of Duty Cycle and Channel Occupancy Rate

Duty cycle (DC) and channel occupancy rate (COR) measurements are important to characterize the availability of white space for cognitive radio systems (CRSs). The COR is related to the real occupancy of channels considered by a CRS but despite its importance it has not yet been widely considered for spectrum use measurements. Spectrum use measurements have typically used detection with a single threshold. In order to improve sensitivity, we utilize the localization algorithm based on double-thresholding (LAD) with the adjacent cluster combining (ACC) to spectrum use measurements and propose a modified version of it. We theoretically analyze the probability of false alarm after the LAD processing in a realistic case with correlation among samples and theoretically analyze the probability of detection after the LAD ACC processing. We propose COR estimation algorithm based on hard decision fusion of the frequency domain decisions. Measurement and theoretical results confirm the accurate DC and COR estimation and the significant sensitivity gains with the proposed algorithms.
Effect of Combined Treatment Using Wilfortrine and Paclitaxel in Liver Cancer and Related Mechanism

Background Liver cancer is a common malignant tumor with high mortality. Currently, effective medicines against liver cancer are still lacking. Paclitaxel is a wide-spectrum anti-tumor agent, while wilfortrine has been shown to have an inhibitory effect on the proliferation of liver cancer cells. This study thus investigated the potential effect of paclitaxel combined with wilfortrine on cultured liver cancer cells and related mechanisms, in order to provide evidence for pathogenesis and treatment of liver cancer. Material/Methods Liver cancer cell line HpeG2 was divided into control, paclitaxel, wilfortrine, and combined treatment groups. Cell proliferation was tested by MTT, while invasion was detected in Transwell chamber assay. Apoptotic protein Bcl-2 and Bax expression levels were further quantified using real-time PCR and Western blotting. Results Both of those 2 drugs can effectively inhibit cancer cell proliferation, depress invasion ability, increase Bcl-2 expression, and elevate Bax expression levels (p<0.05 in all cases). The combined therapy had better treatment efficacy compared to either of those drugs alone (p<0.05). Conclusions The combined treatment using wilfortrine and paclitaxel can inhibit proliferation and invasion of liver cancer cells via down-regulating Bcl-2 and up-regulating Bax, with better efficacy than single use of either drug.
Predicting New Product Success with Prediction Markets in Online Communities

The prediction of new product success is still a challenging task. Traditional market research tools are expensive, time consuming, and error prone. Prediction markets have been introduced as a viable alternative. Utilizing inputs from various participants in game‐like environments, they have been shown to produce accurate results by combining dispersed knowledge via market‐based aggregation mechanisms. While most previous studies use employees or experts as a sample, we test whether online consumer communities can be used to predict the sale of new skis via prediction markets. Sixty‐two users took part in the study. The prediction market was open for 12 days before the main skiing season 2010/2011 began. The outcomes of the prediction markets were compared with the actual sales numbers provided by the ski producers. The mean average errors were between 2.74% and 9.09% in the four markets. Overall, it can be concluded that the prediction markets based on consumer communities produce accurate results.
Adaptive Trajectory Tracking and Stabilization for Omnidirectional Mobile Robot with Dynamic Effect

Abstract This paper presents an adaptive backstepping control method for trajectory tracking and stabilization of an omnidirectional wheeled mobile robot with parameter variations and uncertainties caused by friction and slip. The dynamic model of the robot with three independent driving omnidirectional wheels equally spaced at 120 degrees from one another is briefly introduced. With the dynamic model, the adaptive controller to achieve both trajectory tracking and stabilization is synthesized via adaptive backstepping approach. Experimental results are conducted to show the merit of the proposed control method.
The Nigerian Revolution and the Biafran War

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Heterogeneous Expression of T-type Ca2+ Channels Defines Different Neuronal Populations in the Inferior Olive of the Mouse

The neurons in the inferior olive express subthreshold oscillations in their membrane potential. This oscillatory activity is known to drive synchronous activity in the cerebellar cortex and plays a role in motor learning and motor timing. In the past years, it was commonly thought that olivary neurons belonged to a unique population of oscillating units and that oscillation properties were exclusively dependent on network settings and/or synaptic inputs. The origin of olivary oscillations is now known to be a local phenomenon and is generated by a combination of conductances. In the present work, we show the existence of at least two neuronal populations that can be distinguished on the basis of the presence or absence of low-voltage activated Ca2+ channels. The expression of this channel determines the oscillatory behavior of olivary neurons. Furthermore, the number of cells that express this channel is different between sub nuclei of the inferior olive. These findings clearly indicate the functional variability within and between olivary sub nuclei.
Tissue-Autonomous Function of Drosophila Seipin in Preventing Ectopic Lipid Droplet Formation

Obesity is characterized by accumulation of excess body fat, while lipodystrophy is characterized by loss or absence of body fat. Despite their opposite phenotypes, these two conditions both cause ectopic lipid storage in non-adipose tissues, leading to lipotoxicity, which has health-threatening consequences. The exact mechanisms underlying ectopic lipid storage remain elusive. Here we report the analysis of a Drosophila model of the most severe form of human lipodystrophy, Berardinelli-Seip Congenital Lipodystrophy 2, which is caused by mutations in the BSCL2/Seipin gene. In addition to reduced lipid storage in the fat body, dSeipin mutant flies accumulate ectopic lipid droplets in the salivary gland, a non-adipose tissue. This phenotype was suppressed by expressing dSeipin specifically within the salivary gland. dSeipin mutants display synergistic genetic interactions with lipogenic genes in the formation of ectopic lipid droplets. Our data suggest that dSeipin may participate in phosphatidic acid metabolism and subsequently down-regulate lipogenesis to prevent ectopic lipid droplet formation. In summary, we have demonstrated a tissue-autonomous role of dSeipin in ectopic lipid storage in lipodystrophy.
24.8dBm power handling 60GHz Transmit/Receive switch using series and shunt FETs in 90nm Si-CMOS process

90 nm Si-CMOS high power handling Transmit/Receive (T/R) Switch is proposed for 60 GHz wireless applications. By adopting series and shunt FETs circuit configuration and by employing large FET gate width of 320 μm, high transmit power handling capability is achieved. Since the use of large FET gate width degrades the insertion loss and isolation in the receive mode, a microstrip line is connected between the source and drain to make resonance with Coff of the FET at 60 GHz in off-state. Simulated result shows that the designed T/R switch has over 1 W transmit power handling capability at 60 GHz. Fabricated results show the linear transfer characteristics up to 24.8 dBm at 60 GHz and 36.5 dBm at 36 GHz in transmit mode. Both upper limits comes from the limitation of measurement setup and we expect that this T/R switch has over 1 W power handling at 60 GHz.