Miracle-dz/UniFAR-FTUs huggingface dataset:
Neoadjuvant Accelerated Concomitant Boost Radiotherapy and Multidrug Chemotherapy in Locally Advanced Rectal Cancer: A Dose-Escalation Study

ObjectivesTo determine the maximal and safely dose of preoperative radiotherapy and concurrently intensified chemotherapy regimen (raltitrexed plus oxaliplatin) in locally advanced rectal cancer patients. MethodsPatients with cT3-T4 and/or cN≥1 or locally recurrent rectal cancer were sequentially assigned to 4 treatment schedules of chemoradiation: standard radiotherapy (50.4 Gy/5.5 wk) plus raltitrexed (cohort A), accelerated radiotherapy (55 Gy/5 wk) plus raltitrexed (cohort B), standard radiotherapy plus raltitrexed and oxaliplatin (cohort C), accelerated radiotherapy plus raltitrexed and oxaliplatin (cohort D). Patients were treated in cohorts of 6 to 12 per group. The maximal tolerated dose was exceeded if more than one-third of patients in a given cohort experienced dose-limiting toxicity (DLT). DLT was defined as any grade ≥3 toxicity according to the Radiation Therapy Oncology Group criteria. ResultsForty-six consecutive patients were enrolled. In cohort A, 6 patients received the planned treatment with no DLT. In cohort B, 1 of 8 patients experienced a DLT. In cohort C, a DLT occurred in 2 of 6 patients and therefore, a cohort expansion was required. Three of 16 patients treated at this dose level experienced a DLT. In addition, cohort D was expanded and DLT was found in 4 of 16 patients. Therefore, the maximal tolerated dose was not exceeded at any treatment level. ConclusionsAn intensified regimen of chemoradiotherapy delivering raltitrexed and oxaliplatin concurrently with concomitant boost radiotherapy (55 Gy/5 wk) can be safely administered in patients with locally advanced rectal cancer. On the basis of these results, this intensified regimen could be tested in a phase II study.
Harmony Search PSO Clustering for Tumor and Cancer Gene Expression Dataset

Enormous quantity of gene expression data from diverse data sources are accumulated due to the modern advancement in microarray technology that leads to major computational challenges. The foremost step towards addressing this challenge is to cluster genes which reveal hidden gene expression patterns and natural structures to find the interesting patterns from the underlying data that in turn helps in disease diagnosis and drug development. Particle Swarm Optimization (PSO) technique is extensively used for many practical applications but fails in finding the initial seeds to generate clusters and thus reduces the clustering accuracy. One of the meta-heuristic optimization algorithms called Harmony Search is free from divergence and helps to find out the near-global optimal solutions by searching the entire solution space. This paper proposes a novel Harmony Search Particle Swarm Optimization (HSPSO) clustering algorithm and is applied for Brain Tumor, Colon Cancer, Leukemia Cancer and Lung Cancer gene expression datasets for clustering. Experimental results show that the proposed algorithm produces clusters with better compactness and accuracy, in comparison with K-means clustering, PSO clustering (swarm clustering) and Fuzzy PSO clustering.
HbMADS4, a MADS-box Transcription Factor from Hevea brasiliensis, Negatively Regulates HbSRPP

In plants MADS-box transcription factors (TFs) play important roles in growth and development. However, no plant MADS-box gene has been identified to have a function related to secondary metabolites regulation. Here, a MADS-box TF gene, designated as HbMADS4, was isolated from Hevea brasiliensis by the yeast one-hybrid experiment to screen the latex cDNA library using the promoter of the gene encoding H. brasiliensis small rubber particle protein (HbSRPP) as bait. HbMADS4 was 984-bp containing 633-bp open reading frame encoding a deduced protein of 230 amino acid residues with a typical conserved MADS-box motif at the N terminus. HbMADS4 was preferentially expressed in the latex, but little expression was detected in the leaves, flowers, and roots. Its expression was inducible by methyl jasmonate and ethylene. Furthermore, transient over-expression and over-expression of HbMADS4 in transgenic tobacco plants significantly suppressed the activity of the HbSRP promoter. Altogether, it is proposed that HbMADS4 is a negative regulator of HbSRPP which participates in the biosynthesis of natural rubber.
Sensitivity analysis of the power grid vulnerability to large-scale cascading failures

This paper revisits models of cascading failures in the transmission system of the power grid. It has been recently shownthat since power flows are governed by the laws of physics,these models significantly differ from epidemic/percolationbased models. Yet, while some numerical results have been recently obtained based on these models, there is a need to investigate the sensitivity of the results to various parameters and to evaluate the models' accuracy. In this paper, through numerical experiments with real grid data, we study the effects of geographically correlated outages and the resulting cascades. We consider a wide range of parameters, such as the power lines' Factor of Safety and the sensitivity of the lines to power flow spikes. Moreover, we compare our numerical results to the actual events in a recent blackout in the San Diego area (Sept. 2011), thereby demonstrating that the model's predictions are consistent with real events.
Concurrent estimation of singing voice F0 and phonemes by using spectral envelopes estimated from polyphonic music

The scarcity of available multi-track recordings constitutes a severe constraint on the training of probabilistic models for voice extraction from polyphonic music. We propose a novel training method to estimate a spectral envelope of a singing voice that makes it possible to train the models from a polyphonic music without segregating a singing voice. We implement this method as an extension to the existing W-PST method, which concurrently estimates singing voice fundamental frequency (F0) and phoneme from polyphonic music. The novel training method is based on random sampling from probabilistic distributions. We conducted experiments on concurrent F0 and phoneme estimation and confirm the effectiveness of our method.
An exploration of reflective practice in the helping professions

To date there has been little exploratory research about the experience of trainee clinical psychologists. What is not known from the literature is how trainee clinical psychologists perceive reflective practice within clinical training and how the process of being a ‘novice’ alongside the increased introspection of reflective practice feels in terms of self-concept. The first chapter of the thesis reviews the relevant literature investigating the use of reflective practice within mental health settings. The review indicates that although reflective practice might offer some valuable contributions to working in these settings there are often difficulties with ongoing implementation. A number of methodological limitations of the studies are discussed and the implications of reflective practice for professional practice are considered. Chapter two presents an empirical study that explores trainee clinical psychologists’ experiences of reflective practice within the setting of clinical training, using Interpretative Phenomenological Analysis. A preliminary model of reflective activity within clinical psychology training is proposed, indicating that self-reflection lies at the heart of reflective practice. Implications for clinical training, psychologist self-care and future research are discussed.
Genome Sequence of Stenotrophomonas maltophilia PML168, Which Displays Baeyer-Villiger Monooxygenase Activity

ABSTRACT Stenotrophomonas maltophilia PML168 was isolated from Wembury Beach on the English Coast from a rock pool following growth and selection on agar plates. Here we present the permanent draft genome sequence, which has allowed prediction of function for several genes encoding enzymes relevant to industrial biotechnology, including a novel flavoprotein monooxygenase.
Learning user profiles for personalized information dissemination

Personalized information systems represent the recent effort of delivering information to users more effectively in the modern electronic age. This paper illustrates how a supervised adaptive resonance theory (ART) system, called fuzzy ARAM (adaptive resonance associative map), can be used to learn user profiles for personalized information dissemination. ARAM learning is online, fast, and incremental. Acquisition of new knowledge does not require re-training on previously learned cases. ARAM integrates both user-defined and system-learned knowledge in a single framework. Therefore inconsistency between the two knowledge sources will not arise. ARAM has been used to develop a personalized news system (PIN). Preliminary experiments have verified that PIN is able to provide personalized news by adapting to user's interests in an online manner and generalizing them to new information on-the-fly.
Combining Generative and Discriminative Model Scores for Distant Supervision

Distant supervision is a scheme to generate noisy training data for relation extraction by aligning entities of a knowledge base with text. In this work we combine the output of a discriminative at-least-one learner with that of a generative hierarchical topic model to reduce the noise in distant supervision data. The combination significantly increases the ranking quality of extracted facts and achieves state-of-the-art extraction performance in an end-to-end setting. A simple linear interpolation of the model scores performs better than a parameter-free scheme based on nondominated sorting.
Finding the Exhaustive List of Small Fully Absorbing Sets and Designing the Corresponding Low Error-Floor Decoder

This work provides an efficient exhaustive search algorithm for finding all small fully absorbing sets (FASs) of any arbitrary low-density parity-check (LDPC) code. The proposed algorithm is based on the branch-&-bound principle for solving NP-complete problems. In particular, given any LDPC code, the problem of finding all FASs of size less than t is formulated as an integer programming problem, for which a new branch-&-bound algorithm is devised with new node selection and tree-trimming mechanisms. The resulting algorithm is capable of finding all FASs of size <; 7 for LDPC codes of length <; 1000. When limiting the FASs of interest to those with the number of violated parity-check nodes <; 3, the proposed algorithm is capable of finding all such FASs of size <; 14 for LDPC codes of lengths <; 1000. The resulting exhaustive list of small FASs is then used to devise a new efficient post-processing low-error floor LDPC decoder. The numerical results show that by exploiting the exhaustive list of small FASs, the proposed post-processing decoder can significantly lower the error-floor performance of a given LDPC code. For various example codes of length <; 3000, the proposed post-processing decoder lowers the error floor by a couple of orders of magnitude when compared to the standard belief propagation decoder and by an order of magnitude when compared to other existing low error-floor decoders.
The synaptic mechanisms underlying binaural interactions in rat auditory cortex

In vitro studies suggest that the intracellular C terminus of Neuroligin1 (NL1) could play a central role in the maturation of excitatory synapses. However, it is unknown how this activity affects synapses in vivo, and whether it may impact the development of complex behaviors. To determine how NL1 influences the state of glutamatergic synapses in vivo, we compared the synaptic and behavioral phenotypes of mice overexpressing a full-length version of NL1 (NL1FL) with mice overexpressing a version missing part of the intracellular domain (NL1∆C). We show that overexpression of full-length NL1 yielded an increase in the proportion of synapses with mature characteristics and impaired learning and flexibility. In contrast, the overexpression of NL1∆C increased the number of excitatory postsynaptic structures and led to enhanced flexibility in mnemonic and social behaviors. Transient overexpression of NL1FL revealed that elevated levels are not necessary to maintain synaptic and behavioral states altered earlier in
Adaptive resource scheduling for energy efficient QRD processor with DVFS

This paper presents an energy efficient adaptive QR decomposition scheme for Long Term Evolution Advance (LTE-A) downlink system. The proposed scheme provides a performance robustness to fluctuating wireless channels while maintaining lower workload on a reconfigurable hardware. A statistic based algorithm-switching strategy is employed in the scheme to achieve workload reduction and stable computing resource requirement for QR decomposition. With run time resource allocation, computing resources are assigned to highest performance gain segments to reduce performance loss. By utilizing the dynamic voltage and frequency scaling (DVFS) technique, we further exploit the potential of power saving in various workload situation while maintaining fixed throughput. The proposed technique brings power reduction upto 57.8% in EVA-5 scenario and 24.4% with a maximum SNR loss of 1dB in EVA-70 scenario, when mapped on a coarse grain reconfigurable vector-based platform.
Dihydropteroate Synthase of Mycobacterium leprae and Dapsone Resistance

ABSTRACT Two Mycobacterium leprae genes, folP1 andfolP2, encoding putative dihydropteroate synthases (DHPS), were studied for enzymatic activity and for the presence of mutations associated with dapsone resistance. Each gene was cloned and expressed in a folP knockout mutant of Escherichia coli(C600ΔfolP::Kmr). Expression ofM. leprae folP1 in C600ΔfolP::Kmr conferred growth on a folate-deficient medium, and bacterial lysates exhibited DHPS activity. This recombinant displayed a 256-fold-greater sensitivity to dapsone (measured by the MIC) than wild-type E. coli C600, and 50-fold less dapsone was required to block (expressed as the 50% inhibitory concentration [IC50]) the DHPS activity of this recombinant. When the folP1 genes of several dapsone-resistant M. leprae clinical isolates were sequenced, two missense mutations were identified. One mutation occurred at codon 53, substituting an isoleucine for a threonine residue (T53I) in the DHPS-1, and a second mutation occurred in codon 55, substituting an arginine for a proline residue (P55R). Transformation of the C600ΔfolP::Kmr knockout with plasmids carrying either the T53I or the P55R mutant allele did not substantially alter the DHPS activity compared to levels produced by recombinants containing wild-type M. leprae folP1. However, both mutations increased dapsone resistance, with P55R having the greatest affect on dapsone resistance by increasing the MIC 64-fold and the IC50 68-fold. These results prove that thefolP1 of M. leprae encodes a functional DHPS and that mutations within this gene are associated with the development of dapsone resistance in clinical isolates of M. leprae. Transformants created with M. leprae folP2 did not confer growth on the C600ΔfolP::Kmrknockout strain, and DNA sequences of folP2 from dapsone-susceptible and -resistant M. leprae strains were identical, indicating that this gene does not encode a functional DHPS and is not involved in dapsone resistance in M. leprae.
A Natural Deletion of the HoxC Cluster in Elasmobranch Fishes

Sequence analysis shows that sharks and batoids lack one of four Hox gene clusters once thought necessary for development. Hox proteins are a metazoan-specific family of transcription factors that are required for developmental patterning. The genomic arrangement of Hox genes into four paralogous clusters is a primitive feature of jawed vertebrates. By using high-throughput sequencing, we demonstrate the absence of all HoxC transcripts from embryos of the shark Scyliorhinus canicula and the skate Leucoraja erinacea and the absence of all HoxC genes and two HoxC-associated microRNAs from the genome of L. erinacea. These data suggest a loss of the entire HoxC cluster in elasmobranch fishes and represent evidence for the natural deletion of an entire Hox cluster in vertebrates.
An EMG-driven exoskeleton hand robotic training device on chronic stroke subjects: Task training system for stroke rehabilitation

An exoskeleton hand robotic training device is specially designed for persons after stroke to provide training on their impaired hand by using an exoskeleton robotic hand which is actively driven by their own muscle signals. It detects the stroke person's intention using his/her surface electromyography (EMG) signals from the hemiplegic side and assists in hand opening or hand closing functional tasks. The robotic system is made up of an embedded controller and a robotic hand module which can be adjusted to fit for different finger length. Eight chronic stroke subjects had been recruited to evaluate the effects of this device. The preliminary results showed significant improvement in hand functions (ARAT) and upper limb functions (FMA) after 20 sessions of robot-assisted hand functions task training. With the use of this light and portable robotic device, stroke patients can now practice more easily for the opening and closing of their hands at their own will, and handle functional daily living tasks at ease. A video is included together with this paper to give a demonstration of the hand robotic system on chronic stroke subjects and it will be presented in the conference.
Designing various component analysis at will

This paper provides a generic framework of component analysis (CA) methods introducing a new expression for scatter matrices and Gram matrices, called Generalized Pairwise Expression (GPE). This expression is quite compact but highly powerful: The framework includes not only (1) the standard CA methods but also (2) several regularization techniques, (3) weighted extensions, (4) some clustering methods, and (5) their semi-supervised extensions. This paper also presents quite a simple methodology for designing a desired CA method from the proposed framework: Adopting the known GPEs as templates, and generating a new method by combining these templates appropriately.
Procedural Generation of Sculptural Forms

Software methods in Mathematica are presented for creating visually interesting 3D forms to be produced on solid freeform fabrication (SFF) machines. Concise examples demonstrate fundamental techniques of procedural design that can be combined and extended in many creative ways. This overview should interest non-programmers who attend mathematical art exhibits of SFF objects and wonder where to begin to produce their own ideas.
The difference between psychology and engineering students on emotional intelligence : a study into the construct validity of emotional intelligence

The criterion groups validity of emotional intelligence according to Mayer & Salovey (1997), ability model of emotional intelligence was investigated. Specifically, psychology (n=207) and engineering (n=195) students were compared on the Mayer, Salovey and Caruso Emotional Intelligence Test version 2 (MSCEIT). The primary factor structure of the MSCEIT was found to be valid with some revisions needed in terms of the reliability and content of. the MSCEIT. The second-order factor structure of the MSCEIT was partially confirmed. In terms of the criterion groups validity of emotional intelligence, psychology students were found to exhibit higher levels of the ability to manage emotions in relationships, the ability to understand emotion as well as the ability to facilitate emotions. Engineering and Psychology students exhibited the same level of general emotional management and the ability to accurately identify emotion. Therefore the construct validity of emotional intelligence was partially confirmed.
Report on the Fourth International Workshop on Self-Managing Database Systems ( SMDB 2009 )

The Fourth International Workshop on Self-Managing Database Systems took place on March 29th, 2009 in Shanghai, China, on the day before ICDE. The SMDB workshops bring together researchers and practitioners interested in making data management systems easier to deploy and operate effectively. Topics of interest range from “traditional” management issues, such as database physical design, system tuning, and resource allocation to more recent challenges around scalable and highly-available data services in cloud computing environments. The SMDB Workshops are sponsored by the IEEE TCDE Workgroup on Self-Managing Database Systems. The SMDB 2009 program began with a keynote presentation by James Hamilton, Vice President and Distinguished Engineer with Amazon Web Services. This was followed by five technical papers, presented in two sessions. The workshop concluded with a panel discussion on “grand challenges” in database self-management. More information about the workshop program, including links to papers and presentation slides, can be found at the SMDB 2009 web site, at http://db.uwaterloo. ca/tcde-smdb/smdb09.
Galactic structure from the Calar Alto Deep Imaging Survey (CADIS)

We used 1627 faint (15.5 ≤ R ≤ 23) stars in five fields of the Calar Alto Deep Imaging Survey (CADIS) to estimate the structure parameters of the Galaxy. The results were derived by applying two complementary methods: first by fitting the density distribution function to the measured density of stars perpendicular to the Galactic plane, and second by modelling the observed colors and apparent magnitudes of the stars in the field, using Monte Carlo simulations. The best-fitting model of the Galaxy is then determined by minimising the C-statistic, a modified χ 2 . O ur model includes a double exponential for the stellar disk with scaleheights h1 and h2 and a power law halo with exponent α. 24 480 different parameter combinations have been simulated. Both methods yield consistent results: the best fitting parameter combination is α = 3. 0( or α = 2.5, if we allow for a flattening of the halo with an axial ratio of (c/a) = 0.6), h1 = 300 pc, h2 = 900 pc, and the contribution of thick disk stars to the disk stars in the solar neighbourhood is found to be between 4 and 10%.
Feasibility of MACE for calving traits for non-Holstein breeds

International genetic evaluation for calving traits for Ayrshire (AYS), Brown Swiss (BSW), Jersey (JER), and Simmental (SIM) breeds were studied. 6, 3, 4, and 2 countries participated in the study for the four breeds respectively. Editing were done on a minimum of 50 calvings and 50 daughters for direct and maternal effects respectively. Average estimated correlations for direct calving ease were 0.59, 0.72, and 0.51; for maternal calving ease 0.43, 0.72, and 0.69; for direct stillbirth 0.37, 0.36, and 0.03; for maternal stillbirth 0.16, -0.03, and 0.00 for AYS, BSW, and JER, respectively. Genetic correlations for calving performance for AYS were post processed into windows and with use of HOL prior information as well as previous used correlations. Average post processed correlations for AYS were 0.78 and 0.73 for direct calving ease and maternal calving ease, respectively. It can be concluded that: -genetic correlations looked reasonable for calving ease traits supporting the feasibility of international genetic evaluation, whereas results are more variable for stillbirth and international genetic evaluation for this trait may be more questionable. -post processing had a large impact on genetic correlations.