Miracle-dz/UniFAR-FTUs huggingface dataset:
Placing Technological Innovation in Globalising China

This study critically examines the relevance of the perceived notions of localised production linkages, knowledge spillover and external technology transfer to the experiences of the growth of the ICT industry in China. The research is based on a major firm-level survey conducted in China’s three most important mega urban regions—Beijing, Shanghai-Suzhou and Shenzhen-Dongguan—where the bulk of the Chinese ICT industry is located. The results of the survey showed a distinct landscape of ICT industrial production in which each of the Chinese regions has functioned as the site of capital investment from different sources for different strategic interests. Despite a marked regional variation in ownership, industrial structure, market orientation and technological investment, firms in all regions have invariably reported internal development as the main source of core technology. A negative relationship existed between the level of technological innovation and external orientation in both capital investment and export production. No evidence has been found to verify the hypothesis that a higher level of technological innovation would co-exist with stronger production linkages and knowledge exchanges with both local firms and foreign-invested enterprises. A further analysis of the firms with different technological performance has highlighted the significance of regional setting, ownership, ability of capital mobilisation and corporate strategy and management in the process of technological innovation.
Complications of First Craniotomy for Intra-Axial Brain Tumour

Abstract: Complications were examined in a single surgeon’s series of 207 consecutive adult patients undergoing first craniotomy for intra-axial brain tumour. The study group consisted of 114 gliomas, 74 metastatic tumours and 19 miscellaneous lesions. There were 25 infratentorial tumours and 182 supratentorial tumours (39 deep and 143 superficial). The total number of patients sustaining complications was 52 for an overall complication rate of 25.1%; the rate was higher for infratentorial tumours (44.0%) than supratentorial tumours (22.8%) regardless of histology (p = 0.012). There were 5 deaths for a mortality rate of 2.4%. Forty-seven patients incurred operative morbidity (22.7%); 7 out of the 47 had multiple complications. Sixteen patients sustained transient worsening due to edema (7.7%) and 6 patients sustained permanent neurological deficit (2.9%). Medical complications were suffered by 17 patients (8.2%). Major complications which significantly altered the quality and/or quantity of survival were suffered by 9 patients overall (4.3%).
Serum lipid profile in patients with severe leptospirosis

Sir, We read with great interest the recently published letter to the editor on acute renal failure in patients with severe leptospirosis (1). The author describes the clinical and laboratory characteristics of 24 patients with Weil's syn- drome (1). He concludes that an increase in triglyceride levels in suspected cases of leptospirosis may be considered as a useful marker, which might be related to the severity of the acute renal failure and hepatitis seen in these patients. In this context, we would like to comment on the abnormalities of the serum lipid profile seen in patients with leptospirosis. The serum lipid parameters of five patients, who were admitted to our clinic during the last 2 years with Weil's syndrome, were studied on admission and 1 month after their recovery and were compared with the serum lipid parameters on admission of 45 patients with acute bacterial infections (20 patients with acute pyelonephritis, 10 patients with pneumonia and 15 patients with acute cholecystitis) and with 116 control subjects (Table 1). In agreement with the results of the above-mentioned study (1), patients with acute leptospirosis exhibited a significant increase in the serum triglyceride level compared to patients with acute bacterial infections and to the control population. Additionally, patients with leptospirosis had significantly lower levels of low-density lipoprotein cholesterol (LDL-C) and lipoprotein (a) (Lp(a)) and higher levels of apolipoproteins (Apo) B and E compared to both the patients with acute bacterial infections and to the control subjects (Table 1). On the other hand, acute leptospirosis patients had significantly lower levels of total cholesterol, high-density lipoprotein cholesterol and ApoAI compared to control subjects, but no differences between patients with severe leptospirosis and
The frequency of occurrence of novae hosting an ONe white dwarf

In this paper, we revisit the problem of the determination of the frequency of occurrence of galactic nova outbursts which involve an oxygen-neon (ONe) white dwarf. The improvement with respect to previous work on the subject derives from the fact that we use the results that our evolutionary calculations provide for the final mass and for the chemical profiles of intermediate-to-massive primary components of close binary systems. In particular, the final evolutionary stages, such as the carbon burning phase, have been carefully followed for the whole range of masses of interest. The chemical profiles obtained with our evolutionary code are of interest in determining the chemical composition of the ejecta after being processed through the thermonuclear runaway, although such other factors as the eciency of the mixing between the accreted material and that of the underlying white dwarf must also be considered. In our calculations of the frequency of occurrence of nova outbursts in- volving an ONe white dwarf, we also take into account the observational selection eects introduced by the dierent recurrence times of the outbursts and by the spatial distribution of novae. In spite of the very dierent evolutionary sequences, we find that approximately 1/3 of the observed nova outbursts should involve an oxygen-neon white dwarf, in agreement with previous theoretical estimates.
Effect of Digital Games on Children's Cognitive Achievement

Technologies’ rapid advance in developing digital media has been extensively applied in contemporary play materials to enrich children’s play, such as electronic or computerized toys, electronic story books, television, personal computers, and game consoles. Recently, studies about digital games in these areas have begun to appear. Some educators have a vision that these games have the potential to become powerful motivating digital environments and they study digital games in order to determine how motivational components of popular digital games might be integrated into instructional design. This study investigated whether digital games facilitate children’s cognitive achievement in comparison to traditional computer-assisted instruction. One hundred and fifteen third-graders from a middle/high socio-economic standard school district in Tainan City, Taiwan participated in the study. Results indicate that digital game playing not only improves participants’ fact/recall processes, but also promotes problem-solving skills by recognizing multiple solutions for problems.
Managing Risk in Software Process Improvement: An Action Research Approach

Many software organizations engage in software process improvement (SPI) initiatives to increase their capability to develop quality solutions at a competitive level. Such efforts, however, are complex and very demanding. A variety of risks makes it difficult to develop and implement new processes. We studied SPI in its organizational context through collaborative practice research (CPR), a particular form of action research. The CPR program involved close collaboration between practitioners and researchers over a three-year period to understand and improve SPI initiatives in four Danish software organizations. The problem of understanding and managing risks in SPI teams emerged in one of the participating organizations and led to this research. We draw upon insights from the literature on SPI and software risk management as well as practical lessons learned from managing SPI risks in the participating software organizations. Our research offers two contributions. First, we contribute to knowledge on SPI by proposing an approach to understand and manage risks in SPI teams. This risk management approach consists of a framework for understanding risk areas and risk resolution strategies within SPI and a related process for managing SPI risks. Second, we contribute to knowledge on risk management within the information systems and software engineering disciplines. We propose an approach to tailor risk management to specific contexts. This approach consists of a framework for understanding and choosing between different forms of risk management and a process to tailor risk management to specific contexts.
Construction and analysis of vector space models for use in aspect mining

A software system is designed so that its concerns are as independent as possible. Concerns upon which other concerns depend are called crosscutting concerns, examples of which are logging, authentication, and session management. Crosscutting concerns in a software system have the potential to increase the number of defects over time as the system is evolved. Aspect-oriented programming provides an additional layer of abstraction to the object-oriented programming paradigm for the purpose of separating concerns. The search for crosscutting concerns is referred to as aspect mining. Previous aspect mining algorithms used aggregated metric values as components in the vector space model. In this paper a new method for constructing vector space models is proposed that attempts to retain the detail present in the relationships between the elements of a software application. This is done through the use of pattern matrices derived from the non-aggregated metrics. The non-aggregated vector space models are then used in a clustering-based aspect mining algorithm and their performance is evaluated. The results show that this new approach to constructing vector space models is a viable one but needs further investigation. Issues with current measures for evaluating clustering-based aspect mining algorithms are highlighted and directions for further research are given.
Comparison of orthogonal and non-orthogonal approaches to future wireless cellular systems

This article provides a comparative study of different multiple access techniques. It is demonstrated that non-orthogonal approaches have a spectral-power efficiency advantage over orthogonal ones for delay-sensitive applications in fading environments, and that this theoretical advantage can be realized in practice by exploiting recent progress in transmission and detection techniques. The practical aspects of these multiple access techniques are also discussed and compared
Relationships Between Ongoing Professional Development and Educators' Beliefs Relative to Response to Intervention

ABSTRACT Questions remain regarding whether professional development focused on response to intervention can be implemented effectively on a large scale. One important goal of professional development involves educators' beliefs regarding foundational response-to-intervention concepts (e.g., data-based decision making, importance of effective instruction). This study examined the relations between professional development focused on response to intervention and educators' beliefs. Participants (N = 3,961) were from 34 pilot and 27 comparison schools in a southeastern state. School leadership teams responsible for facilitating response-to-intervention implementation at pilot schools participated in 13 full-day trainings across 3 years. In addition, coaching support was provided to all pilot school educators including leadership team members. Multilevel modeling indicated that school leadership team membership predicted positive changes in beliefs regarding data-based decision making when compared with the remaining pilot and comparison school staff (π = 0.08; SE = 0.01; t[7,562] = 5.87, p < .0001). Pilot school membership predicted negative changes in beliefs regarding functions of core (Tier I) and supplemental (Tier II) instruction when compared to comparison school staff (β = −0.05; SE = 0.02; t[7,565] = −3.13, p < .01). Implications for research and for practitioners challenged with facilitating response-to-intervention implementation as a large-scale systems change are discussed.
Can neutrophil to lymphocyte ratio predict lamina propria invasion in patients with non muscle invasive bladder cancer?

ABSTRACT Objective Recent studies have demonstrated the role of systemic inflammation in the development and progression of cancer. In this study, we evaluated whether preoperatively measured neutrophil-to-lymphocyte ratio (NLR) can predict lamina propria invasion in patients with non-muscle-invasive bladder cancer (NMIBC). Material and Methods We reviewed the medical records of 304 consecutive and newly diagnosed patients with bladder cancer who had been treated with transurethral resection between January 2008 and June 2014. In total, 271 patients were included in the study and the patients were divided into two groups according to the pathological stage (Group 1: Ta, Group 2: T1). NLR was calculated by dividing the absolute neutrophil count (N) by the absolute lymphocyte count (L). Results In total, 271 patients (27 women and 244 men) were enrolled. Mean age was higher in Group 2 than in Group 1 (67.3±10.8 vs. 62.9±10.8, p<0.001). Furthermore, the presence of high grade tumors and tumors ≥3cm in size was statistically higher in Group 2 than in Group 1 (70.9% vs. 9.9%, p=0.0001; 71.8% vs. 36%, p=0.0001, respectively). While the mean white blood cell (WBC) and N counts were statistically insignificant (7.63±1.87 vs. 7.69±1.93, p=0.780; 4.72±1.54 vs. 4.46±1.38, p=0.140; respectively), L was significantly lower and NLR was significantly higher in Group 2 than in Group 1 (2.07±0.75 vs. 2.4±0.87, p=0.001; 2.62±1.5 vs. 2.19±1.62, p=0.029; respectively). Conclusion Our data indicate that high NLR and low L are statistically associated with T1 stage, whereas low L are able to predict lamina propria invasion in patients with NMIBC. These findings suggest that pretreatment measurement of NLR may provide valuable information for the clinical management of patients with NMIBC. Prospective studies are now required to further validate the role of NLR as a risk factor in NMIBC.
Approach for Energy-Based Voice Detector with Adaptive Scaling Factor

This paper presents an alternative energy-based algorithm to provide speech/silence classification. The algorithm is capable to track non-stationary signals and dynamically calculate instantaneous value for threshold using adaptive scaling parameter. It is based on the observation of a noise power estimation used for computation of the threshold can be obtained using minimum and maximum values of a short-term energy estimate. The paper presents this novel voice activity detection algorithm, its performance, its limitations, and some other techniques which deal with energy estimation as well.
Improving Markov network structure learning using decision trees

Most existing algorithms for learning Markov network structure either are limited to learning interactions among few variables or are very slow, due to the large space of possible structures. In this paper, we propose three new methods for using decision trees to learn Markov network structures. The advantage of using decision trees is that they are very fast to learn and can represent complex interactions among many variables. The first method, DTSL, learns a decision tree to predict each variable and converts each tree into a set of conjunctive features that define the Markov network structure. The second, DT-BLM, builds on DTSL by using it to initialize a search-based Markov network learning algorithm recently proposed by Davis and Domingos (2010). The third, DT+L1, combines the features learned by DTSL with those learned by an L1-regularized logistic regression method (L1) proposed by Ravikumar et al. (2009). In an extensive empirical evaluation on 20 data sets, DTSL is comparable to L1 and significantly faster and more accurate than two other baselines. DT-BLM is slower than DTSL, but obtains slightly higher accuracy. DT+L1 combines the strengths of DTSL and L1 to perform significantly better than either of them with only a modest increase in training time.
MicroRNA-338 Regulates Local Cytochrome c Oxidase IV mRNA Levels and Oxidative Phosphorylation in the Axons of Sympathetic Neurons

MicroRNAs (miRs) are evolutionarily conserved, noncoding RNA molecules of ∼21 nt that regulate the expression of genes that are involved in various biological processes, such as cell proliferation and differentiation. Previously, we reported the presence of a heterogeneous population of mRNAs present in the axons and nerve terminals of primary sympathetic neurons to include the nuclear-encoded mitochondrial mRNA coding for COXIV. Sequence analysis of the 3′UTR of this mRNA revealed the presence of a putative binding site for miR-338, a brain-specific microRNA. Transfection of precursor miR-338 into the axons of primary sympathetic neurons decreases COXIV mRNA and protein levels and results in a decrease in mitochondrial activity, as measured by the reduction of ATP levels. Conversely, the transfection of synthetic anti-miR oligonucleotides that inhibit miR-338 increases COXIV levels, and results in a significant increase in oxidative phosphorylation and also norepinephrine uptake in the axons. Our results point to a molecular mechanism by which this microRNA participates in the regulation of axonal respiration and function by modulating the levels of COXIV, a protein which plays a key role in the assembly of the mitochondrial cytochrome c oxidase complex IV.
Using additional information in DisCSPs search

A method of volunteering information during asynchronous search on DisCSPs is presented. The meeting scheduling problem (MSP) is formulated as a distributed search problem. In order to implement asynchronous backtracking (ABT) for the MSP, a multi-variable version of ABT is described. Agents participate in multiple meetings, where each meeting is represented by a variable that needs to be assigned a time-slot. Assignments are constrained by arrival-time constraints, since meetings take place in different locations. All constraints are local to their agents. Additional information is in the form of Nogoods. During search for a consistent schedule for all meetings, agents can generate and send additional Nogoods to those sent by the ABT algorithm. When additional Nogoods are sent, the efficiency of asynchronous backtracking is enhanced. This effect grows with the number of additional volunteered Nogoods.
Analysis of S. pombe SIN protein association to the SPB reveals two genetically separable states of the SIN

ABSTRACT The Schizosaccharomyces pombe septation initiation network (SIN) regulates cytokinesis, and asymmetric association of SIN proteins with the mitotic spindle pole bodies (SPBs) is important for its regulation. Here, we have used semi-automated image analysis to study SIN proteins in large numbers of wild-type and mutant cells. Our principal conclusions are: first, that the association of Cdc7p with the SPBs in early mitosis is frequently asymmetric, with a bias in favour of the new SPB; second, that the early association of Cdc7p–GFP to the SPB depends on Plo1p but not Spg1p, and is unaffected by mutations that influence its asymmetry in anaphase; third, that Cdc7p asymmetry in anaphase B is delayed by Pom1p and by activation of the spindle assembly checkpoint, and is promoted by Rad24p; and fourth, that the length of the spindle, expressed as a fraction of the length of the cell, at which Cdc7p becomes asymmetric is similar in cells dividing at different sizes. These data reveal that multiple regulatory mechanisms control the SIN in mitosis and lead us to propose a two-state model to describe the SIN.
2016 Ieee International Conference on Big Data (big Data) Interpretable and Effective Opinion Spam Detection via Temporal Patterns Mining across Websites

—Millions of ratings and reviews on online review websites are influential over business revenues and customer experiences. However, spammers are posting fake reviews in order to gain financial benefits, at the cost of harming honest businesses and customers. Such fake reviews can be illegal and it is important to detect spamming attacks to eliminate unjust ratings and reviews. However, most of the current approaches can be incompetent as they can only utilize data from individual websites independently, or fail to detect more subtle attacks even they can fuse data from multiple sources. Further, the revealed evidence fails to explain the more complicated real world spamming attacks, hindering the detection processes that usually have human experts in the loop. We close this gap by introducing a novel framework that can jointly detect and explain the potential attacks. The framework mines both macroscopic level temporal sentimental patterns and microscopic level features from multiple review websites. We construct multiple sentimental time series to detect atomic dynamics, based on which we mine various cross-site sentimental temporal patterns that can explain various attacking scenarios. To further identify individual spams within the attacks with more evidence, we study and identify effective microscopic textual and behavioral features that are indicative of spams. We demonstrate via human annotations, that the simple and effective framework can spot a sizable collection of spams that have bypassed one of the current commercial anti-spam systems. I. INTRODUCTION Online reviews and ratings are influential over customer purchasing decisions and business revenues. For example, business revenues on Yelp are positively correlated with the number of stars in ratings [13]; book sales on Amazon.com and Barnesandnoble.com increase as ratings improve [3]. Thus review websites have become the target of spamming attacks that aim at the unjustly manipulating rating of products and businesses. It is imperative to spot such harmful spamming reviews and ratings. Opinion spams have been intensively studied for over a decade. For example, in [7], [18], [19], textual cues of spam-ming are derived and analyzed. User behaviors, such as the temporal and spatial distributions of ratings and reviews over products are also utilized for suspicious reviewer detection [8], [16], [17], [12], [4], [15]. Graph-based approaches construct graphs consisting of reviews, reviewers and businesses [28], [22], and use various graph characteristics, such as the degree distribution of neighbors as detection signals. Hybrid methods combine features of texts, behaviors and graphs [20] to provide more …