Miracle-dz/UniFAR-FTUs huggingface dataset:
Arabidopsis Genes Involved in Acyl Lipid Metabolism. A 2003 Census of the Candidates, a Study of the Distribution of Expressed Sequence Tags in Organs, and a Web-Based Database1

The genome of Arabidopsis has been searched for sequences of genes involved in acyl lipid metabolism. Over 600 encoded proteins have been identified, cataloged, and classified according to predicted function, subcellular location, and alternative splicing. At least one-third of these proteins were previously annotated as “unknown function” or with functions unrelated to acyl lipid metabolism; therefore, this study has improved the annotation of over 200 genes. In particular, annotation of the lipolytic enzyme group (at least 110 members total) has been improved by the critical examination of the biochemical literature and the sequences of the numerous proteins annotated as “lipases. ” In addition, expressed sequence tag (EST) data have been surveyed, and more than 3,700 ESTs associated with the genes were cataloged. Statistical analysis of the number of ESTs associated with specific cDNA libraries has allowed calculation of probabilities of differential expression between different organs. More than 130 genes have been identified with a statistical probability > 0.95 of preferential expression in seed, leaf, root, or flower. All the data are available as a Web-based database, the Arabidopsis Lipid Gene database (http://www.plantbiology.msu.edu/lipids/genesurvey/index.htm). The combination of the data of the Lipid Gene Catalog and the EST analysis can be used to gain insights into differential expression of gene family members and sets of pathway-specific genes, which in turn will guide studies to understand specific functions of individual genes.
The Circadian Clock That Controls Gene Expression in Arabidopsis Is Tissue Specific1

The expression of CHALCONE SYNTHASE(CHS) expression is an important control step in the biosynthesis of flavonoids, which are major photoprotectants in plants. CHS transcription is regulated by endogenous programs and in response to environmental signals. Luciferase reporter gene fusions showed that the CHS promoter is controlled by the circadian clock both in roots and in aerial organs of transgenic Arabidopsis plants. The period of rhythmicCHS expression differs from the previously described rhythm of chlorophyll a/b-binding protein (CAB) gene expression, indicating thatCHS is controlled by a distinct circadian clock. The difference in period is maintained in the wild-type Arabidopsis accessions tested and in the de-etiolated 1 andtiming of CAB expression 1 mutants. These clock-affecting mutations alter the rhythms of both CABand CHS markers, indicating that a similar (if not identical) circadian clock mechanism controls these rhythms. The distinct tissue distribution of CAB andCHS expression suggests that the properties of the circadian clock differ among plant tissues. Several animal organs also exhibit heterogeneous circadian properties in culture but are believed to be synchronized in vivo. The fact that differing periods are manifest in intact plants supports our proposal that spatially separated copies of the plant circadian clock are at most weakly coupled, if not functionally independent. This autonomy has apparently permitted tissue-specific specialization of circadian timing.
Family and Peer Influences in College Plans of High School Students

Data from 612 students in 8ix midwestern high 8chools are analyzed to assess the relative effects of socio-economic background and peer influences on their college plans. The analysis reveals that by the end of the senior year of high school, status in the social system of the 8chool contributes more to variation in college plans than does parents' education. These findings ohallenge the results of several studies which show that the most important source of variation in educational aspirations is the child's 8ocio-economic background.
Energy-Efficient Transmission Scheduling in Mobile Phones Using Machine Learning and Participatory Sensing

Energy efficiency is important for smartphones because they are powered by batteries with limited capacity. Existing work has shown that the tail energy of the third-generation (3G)/fourth-generation (4G) network interface on a mobile device would lead to low energy efficiency. To solve the tail energy minimization problem, some online scheduling algorithms have been proposed, but with a big gap from the offline algorithms that work depending on the knowledge of future transmissions. In this paper, we study the tail energy minimization problem by exploiting the techniques of machine learning and participatory sensing. We design a client-server architecture, in which the training process is conducted in a server, and mobile devices download the constructed predictor from the server to make transmission decisions. A system is developed and deployed on real hardware to evaluate the performance of our proposal. The experimental results show that it can significantly improve the energy efficiency of mobile devices while incurring minimum overhead.
Teaching privacy with ubicomp scenarios in HCI classes

Privacy is a many-faceted concept and, consequently, designing for privacy is a challenging topic to teach. Privacy in ubicomp environments adds to the challenge, since such environments are still rare and people have not gained experience from interacting in them. Scenarios can be used to make the issues concrete for students. We describe three cases, with different scenarios, different pedagogical goals, different levels of students, and different data collection methods, for teaching about privacy using scenarios. We report on the experiences, both the successes and the pitfalls that need to be taken into account.
Interferometric absolute phase determination with TerraSAR-X wideband SAR data

Wideband SAR systems such as TerraSAR-X bring the range resolution down to the order of the carrier wavelength. This opens the possibility to determine not only the fractional phase of SAR interferograms, but also the absolute phase value including the unknown number of integer phase cycles. This possibility enormously helps all interferometric applications such as DEM generation or land surface motion determination. Here we review the basic theory of such processing techniques and show a number of recent results from an ESA study aimed at developing an operational system. Furthermore we show how such techniques can be optimized by the use of customized ‘split-bandwidth’ chirp signals in place of the standard chirps used in contemporary SAR systems.
A monoscopic method for real-time tumour tracking using combined occasional x-ray imaging and continuous respiratory monitoring

Three major linear accelerator vendors offer gantry-mounted single (monoscopic) x-ray imagers. The use of monoscopic imaging to estimate three-dimensional (3D) target positions has not been fully explored. The purpose of this work is to develop and investigate a robust monoscopic method for real-time tumour tracking, combining occasional x-ray imaging and continuous external respiratory monitoring, and compare this with an established stereoscopic method. Monoscopic estimation of 3D target positions is a two-step procedure. Step (1) is similar to the stereoscopic approach using combined occasional x-ray imaging and real-time external respiratory monitoring, i.e. to establish the correlation between the target coordinates T(x, y, z) and the external respiratory signal (R) (sECM: stereoscopic external correlation model). However, in monoscopic estimation, the correlation between the two coordinates (xp, yp) projected on the imager plane and the external respiratory signal (mECM: monoscopic external correlation model) is established. With only a single projection, the component of the 3D target position, which is along the x-ray imaging direction, is unresolved. Therefore, step (2) is used to estimate the unresolved component (z∥) by building a correlation model between the unresolved component and the two other components projected on the imager (ICM: internal correlation model) with a prior 3D target trajectory that may be obtained by 4DCT, MV/kV imaging or 4DCBCT. At the time of prediction, (xp, yp) are estimated from (R) using the correlation model in step (1), and then z∥ is estimated from the estimated (xp, yp) using the correlation model in step (2). The performance of the proposed method was evaluated under various model update intervals and compared with the stereoscopic estimation method using 160 tumour trajectory and external respiratory motion data recorded at 25 Hz from 46 thoracic and abdominal cancer patients who underwent hypofractionated stereotactic radiotherapy by a CyberKnife system. The precision of the input data used in this study to represent tumour motion was assessed using x-ray imaging to be 1.5 ± 0.8 mm. Monoscopic imaging every 30/60 s with updating ICM every 120/180 s can estimate target positions with a 1 mm root-mean-square error (RMSE) for 63/53% or a 2 mm RMSE for 93/91%, respectively. In contrast, stereoscopic x-ray imaging every 30/60 s can estimate target motion within a 1 mm RMSE for 72/58% or a 2 mm RMSE for 95/92%, respectively. The overall 3D error of the monoscopic estimation is approximately 10% higher than comparable stereoscopic imaging methods when the period between imaging is 1 s or more, and 40% higher for continuous imaging. The promising result may be explained by the fact that superior/inferior motion–the major axis of tumour motion–is fully resolved even in the monoscopic view for coplanar treatments, and tumour motion in each dimension is relatively well correlated.
Intracranial aneurysms treated with Guglielmi detachable coils: midterm clinical and radiological outcome in 97 consecutive Chinese patients in Hong Kong.

BACKGROUND AND PURPOSE Use of Guglielmi detachable coils (GDCs) has proved to be a promising endovascular treatment for intracranial aneurysms. This study aimed to evaluate midterm clinical and radiologic outcomes of this treatment in Hong Kong Chinese patients, 68% of whom had small aneurysms (< or =5 mm). METHODS We included 97 consecutive patients in whom GDCs were placed with curative intent. The patients presented with subarachnoid hemorrhage (n = 80) or mass effect (n = 17). The aneurysms measured 5 cm +/- 2.8 mm; 68% were < or =5 mm. All patients were followed up clinically for an average of 54.5 +/- 20.9 months and radiologically with sequential digital subtraction angiography at 6 and 18 months. RESULTS Total occlusion of the aneurysm was successfully achieved in 71.1% of patients after the initial treatment and in 82.5% after subsequent treatments. The retreatment rate was 17.5%. Procedure-related complication and mortality rates were 11.3% and 0%, respectively. The overall mortality was 5%, including mortality due to treatment failure in 1%. Neurologic outcomes were excellent in 77% of patients. Improved neurologic status, unchanged status, and deteriorated status was noted in 61.5%, 22%, and 16.5% of patients, respectively, at the end of the follow-up period. Intrinsic differences existed between Chinese and Western patients regarding the size of the aneurysm at presentation, periprocedural complications, and progression patterns of anatomic outcomes. CONCLUSION Endovascular coiling with GDCs is a reasonably effective and safe treatment for intracranial aneurysms in this group of Hong Kong Chinese patients, with favorable clinical and radiologic outcomes.
An integrative characterization of recurrent molecular aberrations in glioblastoma genomes

Glioblastoma multiforme (GBM) is the most common and malignant primary brain tumor in adults. Decades of investigations and the recent effort of the Cancer Genome Atlas (TCGA) project have mapped many molecular alterations in GBM cells. Alterations on DNAs may dysregulate gene expressions and drive malignancy of tumors. It is thus important to uncover causal and statistical dependency between ‘effector’ molecular aberrations and ‘target’ gene expressions in GBMs. A rich collection of prior studies attempted to combine copy number variation (CNV) and mRNA expression data. However, systematic methods to integrate multiple types of cancer genomic data—gene mutations, single nucleotide polymorphisms, CNVs, DNA methylations, mRNA and microRNA expressions and clinical information—are relatively scarce. We proposed an algorithm to build ‘association modules’ linking effector molecular aberrations and target gene expressions and applied the module-finding algorithm to the integrated TCGA GBM data sets. The inferred association modules were validated by six tests using external information and datasets of central nervous system tumors: (i) indication of prognostic effects among patients; (ii) coherence of target gene expressions; (iii) retention of effector–target associations in external data sets; (iv) recurrence of effector molecular aberrations in GBM; (v) functional enrichment of target genes; and (vi) co-citations between effectors and targets. Modules associated with well-known molecular aberrations of GBM—such as chromosome 7 amplifications, chromosome 10 deletions, EGFR and NF1 mutations—passed the majority of the validation tests. Furthermore, several modules associated with less well-reported molecular aberrations—such as chromosome 11 CNVs, CD40, PLXNB1 and GSTM1 methylations, and mir-21 expressions—were also validated by external information. In particular, modules constituting trans-acting effects with chromosome 11 CNVs and cis-acting effects with chromosome 10 CNVs manifested strong negative and positive associations with survival times in brain tumors. By aligning the information of association modules with the established GBM subclasses based on transcription or methylation levels, we found each subclass possessed multiple concurrent molecular aberrations. Furthermore, the joint molecular characteristics derived from 16 association modules had prognostic power not explained away by the strong biomarker of CpG island methylator phenotypes. Functional and survival analyses indicated that immune/inflammatory responses and epithelial-mesenchymal transitions were among the most important determining processes of prognosis. Finally, we demonstrated that certain molecular aberrations uniquely recurred in GBM but were relatively rare in non-GBM glioma cells. These results justify the utility of an integrative analysis on cancer genomes and provide testable characterizations of driver aberration events in GBM.
Connecting the Past to the Future

This article argues that hate crimes are not a modern-day phenomenon, but extend throughout the history of the United States. Using a definition based on intrinsic justice rather than codified law, selected events in the 17th through early 19th centuries are examined. Comparative analysis indicated similarities and differences between historical and modern events. The distillation of conditions surrounding hate crime dynamics both past and present, along with the examination of current trends suggest the following summary factors: (a) racism is a primary predictor of hate crime through time; (b) the efficiency and degree of harm potential in hate crime is a function of opportunity and technology; (c) hate crimes will occur more frequently and be more difficult to prevent; (d) notwithstanding the repugnant nature of hate crime, many Americans are becoming more sympathetic to the hate crime perpetrator's cause; and (e) hate crime, on some levels, is becoming indistinguishable from domestic terrorism.
Sensitizes TRPV 1 via Activation of TlR 4 in Trigeminal Sensory neurons

Recent studies have demonstrated that the lipopolysaccharide (LPS) receptor (TLR4) is expressed in TRPV1 containing trigeminal sensory neurons. In this study, we evaluated whether LPS activates trigeminal neurons, and sensitizes TRPV1 responses via TLR4. To test this novel hypothesis, we first demonstrated that LPS binds to receptors in trigeminal neurons using competitive binding. Second, we demonstrated that LPS evoked a concentration-dependent increase in intracellular calcium accumulation (Ca)i and inward currents. Third, LPS significantly sensitized TRPV1 to capsaicin measured by (Ca)i, release of calcitonin gene-related peptide, and inward currents. Importantly, a selective TLR4 antagonist blocked these effects. Analysis of these data, collectively, demonstrates that LPS is capable of directly activating trigeminal neurons, and sensitizing TRPV1 via a TLR4-mediated mechanism. These findings are consistent with the hypothesis that trigeminal neurons are capable of detecting pathogenic bacterial components leading to sensitization of TRPV1, possibly contributing to the inflammatory pain often observed in bacterial infections.
Safe Close-Proximity and Physical Human-Robot Interaction Using Industrial Robots

Industrial robots have been employed worldwide in the manufacturing sector for performing tasks quickly, repeatedly and accurately in relatively static environments for over 30 years. In recent years, close physical interaction between industrial robots and human operators has attracted researchers' attention and encouraged a number of technological innovations to turn these robots into human-robot platforms. In this work a specially designed compliant wrist is developed to support dexterous robotic interaction with live proximity and contact feedback. The compliant wrist incorporates a level of compliance into an initially non-compliant manipulator robot which allows the robot to dynamically adapt to the surfaces it approaches or touches. Furthermore, to facilitate human -- robot interactions, the robot must be able to adapt its behaviour to the human partner. Therefore, a real-time path planning method is developed to generate online motion, adapt the robot to dynamic changes in the environment and ensure smooth interactions. The performance of the proposed method is demonstrated through experimental results on a CRS-F3 manipulator.
SentiME++ at SemEval-2017 Task 4: Stacking State-of-the-Art Classifiers to Enhance Sentiment Classification

In this paper, we describe the participation of the SentiME++ system to the SemEval 2017 Task 4A “Sentiment Analysis in Twitter” that aims to classify whether English tweets are of positive, neutral or negative sentiment. SentiME++ is an ensemble approach to sentiment analysis that leverages stacked generalization to automatically combine the predictions of five state-of-the-art sentiment classifiers. SentiME++ achieved officially 61.30% F1-score, ranking 12th out of 38 participants.
Provable Data Possession & Dynamic Audit Services for Integrity Verification in Clouds Environments

Provable data possession (PDP) is a technique for ensuring the integrity of data in storage outsourcing. In this paper, we address the construction of an efficient PDP scheme for distributed cloud storage to support the scalability of service and data migration, in which we consider the existence of multiple cloud service providers to cooperatively store and maintain the clients’ data. We present a cooperative PDP (CPDP) scheme based on homomorphic verifiable response and hash index hierarchy. We prove the security of our scheme based on multi-prover zero-knowledge proof system, which can satisfy completeness, knowledge soundness, and zero-knowledge properties. In addition, we propose a dynamic audit service for verifying the integrity of untrusted and outsourced storage. Our audit service, constructed based on the techniques, fragment structure, random sampling and index-hash table, can support provable updates to outsourced data, and timely abnormal detection. Index: Storage Security, Provable Data Possession, Dynamic Audit, Integrity Verification.
A user-aware broadcast scheme using rate-adaptive coded transmission

A broadcast transmission scheme for multimedia broadcast multicast services (MBMS) is proposed using a coded system with users' feedback in wireless systems. In the proposed transmission scheme, it is possible to adjust the transmission rate with binary users' feedback signals to maximize the overall throughput for a given set of users as a user-ware broadcast transmission scheme. The proposed scheme does not aim at providing reliable transmissions, but maximizing the overall throughput. An adaptive algorithm is proposed to decide the transmission rate adaptively for given channel-user environments using finite-difference stochastic approximation (FDSA). Furthermore, we consider a multi-layer transmission scheme to provide multi-grade MBMS and also derive an adaptive algorithm to adapt multiple transmission rates to given channel-user environments.
Self-learning MIMO-RF receiver systems: Process resilient real-time adaptation to channel conditions for low power operation

Prior research has established that dynamically trading-off the performance of the RF front-end for reduced power consumption across changing channel conditions, using a feedback control system that modulates circuit and algorithmic level "tuning knobs" in real-time, leads to significant power savings. It is also known that the optimal power control strategy depends on the process conditions corresponding to the RF devices concerned. This complicates the problem of designing the feedback control system that guarantees the best control strategy for minimizing power consumption across all channel conditions and process corners. Since this problem is largely intractable due to the complexity of simulation across all channel conditions and process corners, we propose a self-learning strategy for adaptive MIMO-RF systems. In this approach, RF devices learn their own performance vs. power consumption vs. tuning knob relationships "on-the-fly" and formulate the optimum reconfiguration strategy using neural-network based learning techniques during real-time operation. The methodology is demonstrated for a MIMO-RF receiver front-end and is supported by hardware validation leading to 2.5X power savings in minimal learning time.
Attentive Visual Servoing in the MPEG compressed domain for Un-calibrated Motion Parameter Estimation of Road Traffic

An attentive vision system is proposed that estimates traffic motion parameters from MPEG-2 compressed video recorded using an un-calibrated camera mounted on a pan-tilt unit. Compressed domain information from a stream of MPEG-2 video is used to estimate a traffic motion field and infer the 2D frame location of the traffic lanes. With these visual cues attentive visual servoing automatically adjusts camera pose so as to improve the motion parameter estimation process. An existing technique to acquire motion parameters from an un-calibrated camera is used after obtaining an optimal camera pose. This system provides a computationally inexpensive alternative to existing Intelligent Transport Systems for surveillance
Recognition of the Polypeptide Core of Mucin by Monoclonal Antibody MUSE11 against an Adenocarcinoma‐associated Antigen

Monoclonal antibody (MAb) MUSE11 detects an adenocarcinoma‐associated antigen and is useful for the serodiagnosis of pancreas cancer. We established a sandwich enzyme immunoassay using MAb MUSE11 and MAb DP3 against a breast cancer‐associated mucin core protein as a catcher and a tracer, respectively. With this assay system, the binding of the tracer MAb DF3 to an antigen in the human kidney tissue lysate was clearly inhibited by MAb MUSE11. In addition, MAb MUSE11 showed a significant binding activity to the synthetic peptide corresponding to the tandem repeat of a human epithelial mucin core protein. These data suggest that MAb MUSE11 could detect the polypeptide core of a mucin, and may be of use for studying mucin as a gene product.