Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient Algorithm of Chinese String Sort in User-Defined Sequence

Existing sort algorithms are difficult to implement Chinese string sort in user-defined sequence. This paper proposes an efficient string sort method in user-defined character order. On the basis of the consecutive numbers which used to define the custom order of characters, the hash table structure is employed to convert each string into corresponding array of integers. By taking the maximum number of characters as the new radix, the Radix sort algorithm is used to implement fast sort of strings in user-defined order. Theory analysis and experiments show that the sort algorithm of this paper can easily achieve Chinese string sort in user-defined order in linear time and space complexity. This sort algorithm has a better time performance than that of Quick Sort algorithm, and it can effortlessly extend to string sort applications of other languages.
Magneto-dielectric characterization of TiO2-CoFe2O4 derived ceramic composites

Dielectric permittivity (ε′), magnetic permeability (μ′) and dielectric and magnetic loss (tan δε and tan δμ, respectively) of magneto-dielectric cobalt ferrite-titania (CFO-TO) ceramic composites are determined from 200 to 300 MHz. The four different combinations of phases that can be produced in the sintered composite, according to the starting CFO/TO molar ratio allow to tune the macroscopic permittivity and permeability. For the first time impedance, miniaturization and magneto-dielectric loss of the four classes of composites are calculated and discussed. The displayed miniaturization factors between 4.4 and 8.2 in the very-high frequency (VHF) range corroborate their potential application as magneto-dielectric substrate materials for antennas. Remarkably, the ceramic composites characterized by 2 vol.% and 3 vol.% of CFO and TO, respectively, dispersed in Fe2CoTi3O10 (FCTO) matrix display a magneto-dielectric loss lower than 0.07 and a miniaturization factor of 4.8.
Multilingual e-mail text processing for speech synthesis

An integrated method of text pre-processing and language identification is introduced to deal with the problem of mixed-language e-mail messages in a speech-enabled e-mail reading system. Our method can confidently distinguish between the supported languages and switch between several TTS engines or languages to read the portions of the text in the appropriate language. This is achieved by making use of the combined information from a text pre-processor and a language identifier that relies on both statistical information and linguistic features indicative of a particular language.
Convergence Rate Analysis for the Alternating Direction Method of Multipliers with a Substitution Procedure for Separable Convex Programming

Recently, in He et al. [He BS, Tao M, Yuan XM (2012) Alternating direction method with Gaussian back substitution for separable convex programming. SIAM J. Optim. 22(2):313–340], we have showed the first possibility of combining the Douglas-Rachford alternating direction method of multipliers (ADMM) with a Gaussian back substitution procedure for solving a convex minimization model with a general separable structure. This paper is a further study on this theme. We first derive a general algorithmic framework to combine ADMM with either a forward or backward substitution procedure. Then, we show that convergence of this framework can be easily proved from the contraction perspective, and its local linear convergence rate is provable if certain error bound condition is assumed. Without such an error bound assumption, we can estimate its worst-case convergence rate measured by the iteration complexity.
A Cortex Segmentation Pipeline for Neurosurgical Intervention Planning

Cortex segmentation is a prerequisite for 3D neurosurgical intervention planning. The visualization of the cortical surface along with target and risk structures enables conservative access planning and gives context information about the patient-specific anatomy. We present a pipeline for the segmentation of the cortical surface in T1-weighted MR images. To segment the cortex, we combine watershed and level set segmentation. The cortex segmentation pipeline (CSP) is semiautomatic and designed to let the surgeon influence the intermediate data at any stage of the segmentation process. To evaluate the CSP we used the Segmentation Validation Engine (SVE) by Shattuck et al. [1] and compared the results to three different popular methods (BET, BSE and HWA).
Development and Characterization of an Inducible Rat Model of Chronic Thromboembolic Pulmonary Hypertension

Chronic thromboembolic pulmonary hypertension (CTEPH) is an entity of PH that not only limits patients quality of life but also causes significant morbidity and mortality. The treatment of choice is pulmonary endarterectomy. However numerous patients do not qualify for pulmonary endarterectomy or present with residual vasculopathy post pulmonary endarterectomy and require specific vasodilator treatment. Currently, there is no available specific small animal model of CTEPH that could serve as tool to identify targetable molecular pathways and to test new treatment options. Thus, we generated and standardized a rat model that not only resembles functional and histological features of CTEPH but also emulates thrombi fibrosis. The pulmonary embolism protocol consisted of 3 sequential tail vein injections of fibrinogen/collagen-covered polystyrene microspheres combined with thrombin and administered to 10-week-old male Wistar rats. After the third embolism, rats developed characteristic features of CTEPH including elevated right ventricular systolic pressure, right ventricular cardiomyocyte hypertrophy, pulmonary artery remodeling, increased serum brain natriuretic peptide levels, thrombi fibrosis, and formation of pulmonary cellular-fibrotic lesions. The current animal model seems suitable for detailed study of CTEPH pathophysiology and permits preclinical testing of new pharmacological therapies against CTEPH.
Efficient OD Trip Matrix Prediction Based on Tensor Decomposition

Origindestination (OD) trip matrices reflect demand patterns of traffic networks and play important roles in traffic engineering. Existing approaches for traffic flow forecast such as ARIMA, SVR, and neural network perform well in modeling and predicting each OD pair separately, but they cause inefficiency when dealing with multidimensional OD demand data. In this paper, to solve the problemgiven OD trip matrices for T moments, how can we predict the overall OD trip matrices at time T+1, T+2, or even T+L, we model temporal vehicle-based OD trip matrix as a four-order tensor consisting of four attributes: origin, destination, vehicle type and time. By resorting to CANDECOMP/PARAFAC (CP) tensor decomposition, we show how a prediction method can be used to forecast future traffic demand in time factor matrix. Experiments based on a real highway tolling dataset demonstrate that our method effectively reduces the time for prediction and meanwhile makes the prediction accuracy competitive with those of other methods.
On the Effectiveness of Information Retrieval Based Bug Localization for C Programs

Localizing bugs is important, difficult, and expensive, especially for large software projects. To address this problem, information retrieval (IR) based bug localization has increasingly been used to suggest potential buggy files given a bug report. To date, researchers have proposed a number of IR techniques for bug localization and empirically evaluated them to understand their effectiveness. However, virtually all of the evaluations have been limited to the projects written in object-oriented programming languages, particularly Java. Therefore, the effectiveness of these techniques for other widely used languages such as C is still unknown. In this paper, we create a benchmark dataset consisting of more than 7,500 bug reports from five popular C projects and rigorously evaluate our recently introduced IR-based bug localization tool using this dataset. Our results indicate that although the IR-relevant properties of C and Java programs are different, IR-based bug localization in C software at the file level is overall as effective as in Java software. However, we also find that the recent advance of using program structure information in performing bug localization gives less of a benefit for C software than for Java software.
Childhood externalizing behavior: theory and implications.

TOPIC Childhood externalizing behavior PURPOSE To analyze the construct of externalizing behavior (aggression, delinquency, and hyperactivity), illustrate the biosocial model of childhood externalizing, and draw clinical implications for nursing research and practice. SOURCES A review of the literature based on psychological, psychiatric, and nursing journals. CONCLUSIONS A better understanding of childhood externalizing behavior problems and the risk factors underlying them are essential to prevent them. The employment of an integrative biosocial perspective is argued to be important in understanding this behavior.
A Geographical Heuristic Routing Protocol for VANETs

Vehicular ad hoc networks (VANETs) leverage the communication system of Intelligent Transportation Systems (ITS). Recently, Delay-Tolerant Network (DTN) routing protocols have increased their popularity among the research community for being used in non-safety VANET applications and services like traffic reporting. Vehicular DTN protocols use geographical and local information to make forwarding decisions. However, current proposals only consider the selection of the best candidate based on a local-search. In this paper, we propose a generic Geographical Heuristic Routing (GHR) protocol that can be applied to any DTN geographical routing protocol that makes forwarding decisions hop by hop. GHR includes in its operation adaptations simulated annealing and Tabu-search meta-heuristics, which have largely been used to improve local-search results in discrete optimization. We include a complete performance evaluation of GHR in a multi-hop VANET simulation scenario for a reporting service. Our study analyzes all of the meaningful configurations of GHR and offers a statistical analysis of our findings by means of MANOVA tests. Our results indicate that the use of a Tabu list contributes to improving the packet delivery ratio by around 5% to 10%. Moreover, if Tabu is used, then the simulated annealing routing strategy gets a better performance than the selection of the best node used with carry and forwarding (default operation).
Preparatory planning framework for Created Out of Mind: Shaping perceptions of dementia through art and science

Created Out of Mind is an interdisciplinary project, comprised of individuals from arts, social sciences, music, biomedical sciences, humanities and operational disciplines. Collaboratively we are working to shape perceptions of dementias through the arts and sciences, from a position within the Wellcome Collection. The Collection is a public building, above objects and archives, with a porous relationship between research, museum artefacts, and the public. This pre-planning framework will act as an introduction to Created Out of Mind. The framework explains the rationale and aims of the project, outlines our focus for the project, and explores a number of challenges we have encountered by virtue of working in this way.
A comment on the cost of capital for investments with non-homogeneous components

In this paper, the expression for the cost of capital is derived when net and replacement investments exhibit differences in their effective prices due to a different fiscal treatment. It is shown that, contrary to previous results in the literature, the cost of capital should be constructed under an opportunity cost criterion rather than a historical one. This result has some important economic consequences, since the optimizing firm will take into account not only the effective price for the new investments but also consider the opportunity cost of replacing them.
Course of the Fatigue Dimension "Activity Level" and the Interference of Fatigue With Daily Living Activities for Patients With Breast Cancer Receiving Adjuvant Chemotherapy

The purpose of this study was to determine the course of the activity level, seen as a dimension of fatigue, as a function of chemotherapy within a breast cancer population receiving adjuvant chemotherapy. The second purpose of this study was to determine the course of the interference of fatigue, in general, with daily activities within a breast cancer population receiving adjuvant chemotherapy. In a prospective cohort study, a sample of 157 patients with breast cancer was interviewed, at the first, third, and fifth cycle of adjuvant chemotherapy as well as 4 and 12 weeks after the last cycle of adjuvant chemotherapy. The chemotherapy was administered with either a doxorubicin-containing schedule or cyclophosphamide, methotrexate, and 5-fluorouracil. These 2 groups were compared. The activity level was measured by the Multidimensional Fatigue Inventory. A linear multilevel model was used to analyze the course. The revised Piper Fatigue Scale was used to examine the behavioral changes in the interference of fatigue with activities of daily living. A logistic multilevel model was used to analyze the course of this interference over time. The activity level seems to be rather stable during the treatment with chemotherapy. After the completion of chemotherapy, an improvement is observed. The activity levels reported at the first and the last measurement do not significantly differ. The course of the activity level is not affected by the type of chemotherapy regimen. Age, having children, and the stage of breast cancer turn out to be important determinants of the course of activity level. At all measurement occasions, women with a mastectomy were significantly more hampered in their activity level than women that had undergone a lumpectomy. The longer the duration of radiotherapy, the less active, and the longer the time interval between the last radiotherapy session and the measurement point, the more active patients were at that measurement point. A phenomenon not easy to explain is that the activity level in women who had received, in total, more chemotherapy treatments was significantly less diminished than those who had received fewer treatments. During the study period, in approximately 15% to 35% of the sample, fatigue interferes considerably with their daily living activities. Furthermore, the interference of fatigue with activities in daily life first increases after the start of chemotherapy and decreases after the completion of chemotherapy. Fatigue definitely affects the daily living activities of patients with breast cancer receiving adjuvant chemotherapy. With this knowledge, healthcare providers can inform patients on what they can expect. Further research should include the trajectory preceding chemotherapy and a healthy control group.
ICTs integration in education: mobile learning and the technology acceptance model (TAM)

The present communication describes the design of a study on the acceptance of mobile technologies among primary education teachers of Castilla y León. The investigation design is based on the Technology Acceptance Model (TAM) conceived by Davis in which the perceived usefulness and the perceived ease of use are the key factors that explain the acceptance of a technological innovation. A series of constructs have been incorporated to Davis' model in order to take into consideration the influence of other factors, both intrinsic and extrinsic. Following this new model, we have drawn up an instrument, which is currently in the validation stage.
Anatomy and Regenerative Biology Faculty Publications Anatomy and Regenerative Biology the Use of Stem Cells in Burn Wound Healing: a Review Recommended Citation the Use of Stem Cells in Burn Wound Healing: a Review

Burn wound healing involves a series of complex processes which are subject to intensive investigations to improve the outcomes, in particular, the healing time and the quality of the scar. Burn injuries, especially severe ones, are proving to have devastating effects on the affected patients. Stem cells have been recently applied in the field to promote superior healing of the wounds. Not only have stem cells been shown to promote better and faster healing of the burn wounds, but also they have decreased the inflammation levels with less scar progression and fibrosis. This review aims to highlight the beneficial therapeutic effect of stem cells in burn wound healing and to discuss the involved pathways and signaling molecules. The review covers various types of burn wound healing like skin and corneal burns, along with the alternative recent therapies being studied in the field of burn wound healing. The current reflection of the attitudes of people regarding the use of stem cells in burn wound healing is also stated.
Memantine, a noncompetitive NMDA receptor antagonist improves hyperammonemia‐induced encephalopathy and acute hepatic encephalopathy in rats

The aim of this study was to investigate the possible role of N‐methyl‐D‐aspartate (NMDA)‐receptor overactivity in two different experimental rat models of encephalopathy: subacute encephalopathy caused by severe hyperammonemia in portacaval‐shunted rats (AI‐PCS rats) and acute hepatic encephalopathy caused by complete liver ischemia (LIS rats). The effect of the noncompetitive NMDA‐receptor antagonist memantine (intraperitoneal [i.p.] 10‐20 mg/kg bw or intravenous [i.v.] 5 mg/kg bw) was studied on the severity of encephalopathy by assessment of clinical grading and electroencephalogram (EEG) spectral analysis, on plasma ammonia concentrations, amino acid concentrations in cerebrospinal fluid (CSF), intracranial pressure (ICP), and brain water content. Both rat models developed encephalopathy within 3 to 6 hours, associated with increased CSF glutamate and aspartate concentrations and increased ICP and brain water content. Memantine administration in AI‐PCS and LIS rats resulted in a significant improvement in clinical grading and less slowing of EEG activity (P < .05), and smaller increases in CSF glutamate (P < .05) concentrations. Moreover, ICP and brain water content were significantly lower in memantine‐treated AI‐PCS rats than in untreated AI‐PCS rats (P < .05). Memantine had no significant effect on ICP and brain water content in LIS rats, and on ammonia concentrations in both models. These results indicate that NMDA‐ receptor activation might be involved in the pathogenesis of hyperammonemia‐induced encephalopathy and of acute hepatic encephalopathy caused by LIS.
On the predictive power of sequence similarity in yeast

Perhaps the most direct way to infer functional linkage of proteins is through structural similarity. However, structure determination lags behind DNA sequencing. Here we show that sequence similarity based on nucleotide sequences alone between ORFs in yeast is indicative of the corresponding genes being of the same functional group, having a similar gene expression pattern or of being involved in a protein-protein interaction. In particular, we compare the nucleotide sequences corresponding to the 6280 yeast ORFs using BLAST, and then cluster them together using a simple neighbor-joining algorithm. This, in effect, gives us hierarchical clustering of 53 levels, where higher levels have bigger clusters. We compare the clustering to large databases that are not based a-priori on sequence information to get a notion of how well our clustering is correlated with this data. For functional annotation we use the SGD database that gives one of 540 annotations for about half the yeast genes. For all pairs that appear within a cluster, we test the hypothesis that almost all genes within the same cluster have the same function. We get very high percentage rates of correct annotation at the lower levels of the hierarchy, which decreases gradually at higher ones. From the results of the large scale gene expression experiments we generate a list of pairs of genes, whose expression is highly correlated (≱0.9). We then go over this list of pairs, and count how many of them are contained within a cluster as opposed to the expected number by a random model. We estimate the significance of our results using simulation, and get for all levels p-value≰≰0.001. The third type of data obtained from the protein-protein interaction database that is given as a list of airs of proteins involved in interaction. As before, we count how many pairs are contained within a cluster, and get much better results than expected by a random model, with p-values≰0.001 for almost all levels. In summary, we show that successful functional predictions and functional annotations can be applied at a genomic scale. This can be achieved by combining a naive hierarchical clustering method that creates sets of clusters at different levels of granularity with statistical validation tools.
Monoclonal antibody production to a B16 melanoma associated antigen

Eight different rat hybridoma cell lines have been produced which secrete MAbs Abbreviations: BSA, bovine serum albumin; ELISA, enzymelinked immunosorbent assay; MSA, murine serum albumin; PBS, phosphate‐buffered saline; MAb, monoclonal antibody; s.c. , subcutaneous. identifying the melanoma‐specific B700 antigen. This antigen has been previously shown to have significant sequence homology to the mammalian serum albumins, but antibodies specifically raised against B700 cross‐react only with murine albumin. Each of these MAbs has been shown by Western immunoblotting to recognize an independent epitope on the B700 protein; it is concluded not only that the B700 protein is a highly immunogenic antigen, but also that the sequence homologies between the B700 antigen and murine albumin must occur extensively throughout the molecule.
Association Between Lamotrigine Concentrations and ABCB1 Polymorphisms in Patients With Epilepsy

Background: Epilepsy is treated with a variety of anticonvulsants that are often used concomitantly. Therefore, therapeutic drug monitoring is often necessary. Along with clinical and environmental factors, genetic predisposition has been recognized to be relevant for interindividual variability in drug response. Polymorphic transporter proteins such as P-glycoprotein significantly influence pharmacokinetics and bioavailability of many structurally unrelated drugs. The aim of the study was to evaluate the impact of polymorphisms in the P-glycoprotein–encoding gene ABCB1 (C1236T, G2677T/A, C3435T) on antiepileptic drug disposition. Methods: We recruited 222 patients with epilepsy who were prescribed lamotrigine in monotherapy or polytherapy. Lamotrigine plasma concentrations were analyzed and compared with ABCB1 gene variants. The ABCB1 genotyping was performed by real-time polymerase chain reaction methods. The therapeutic drug monitoring was performed by high-performance liquid chromatography–diode array detector (DAD) and immunoassay. Results: A significant correlation was confirmed between lamotrigine concentration and additional drugs (P < 0.001). In the whole group, statistical analysis showed correlations between lamotrigine concentrations and ABCB1 C1236T variants: 10.1 and 6.5 &mgr;mol/L for CC versus CT + TT, respectively (P = 0.021), and for dose corrected lamotrigine 0.068 and 0.053 &mgr;mol·L−1·mg−1, for CC versus CT + TT, respectively (P = 0.017). Analysis of a specific haplotype showed that 1236C–2677G–3435C carriers had higher lamotrigine concentrations than 1236T–2677G–3435T carriers (P < 0.001), followed by 1236T–2677T–3435C carriers (P < 0.001). Conclusions: ABCB1 C1236T, G2677T/A, C3435T polymorphisms have an influence on lamotrigine serum concentrations.