Miracle-dz/UniFAR-FTUs huggingface dataset:
Geometry Helps to Compare Persistence Diagrams

Exploiting geometric structure to improve the asymptotic complexity of discrete assignment problems is a well-studied subject. In contrast, the practical advantages of using geometry for such problems have not been explored. We implement geometric variants of the Hopcroft-Karp algorithm for bottleneck matching (based on previous work by Efrat el al.) and of the auction algorithm by Bertsekas for Wasserstein distance computation. Both implementations use k-d trees to replace a linear scan with a geometric proximity query. Our interest in this problem stems from the desire to compute distances between persistence diagrams, a problem that comes up frequently in topological data analysis. We show that our geometric matching algorithms lead to a substantial performance gain, both in running time and in memory consumption, over their purely combinatorial counterparts. Moreover, our implementation significantly outperforms the only other implementation available for comparing persistence diagrams.
Engaging student teachers in reflection through micro teaching and interaction

This article describes and evaluates a microteaching and stimulated recall activity designed to engage novice teachers with reflection. We use data extracts from tutor/student discussions and student assignments to analyse moments of reflection. We look at what aspects of the microteaching lessons caused reflection and how students reflected. Analysis shows that microteaching produced authentic classroom problems or puzzles that stimulated reflection and that a mirror teacher system gave students valuable opportunities for comparison and reflection. Analysis also reveals that interaction in tutor-student discussions also helped student teachers reflect.
A value chain perspective to the control of avian influenza in the Western Java poultry sector

HPAI H5N1 is considered endemic in Indonesian poultry and poses a major challenge to animal and human health authorities. The complex structure of the Indonesian poultry meat value chain is an important reason for the limited efficacy of HPAI control in Indonesia so far. The overall objective of this research is to improve our understanding of how to implement a push-and-pull strategy in the poultry supply chain to control HPAI infection in Western Java. More specifically, this study investigates the poultry value chain in Western Java in relation to consumers’ behavior and governance of the value chain. Poultry production in Western Java is organized in a highly complex structure. The co-existence of four different poultry value chains in West Java can be distinguished by the level of coordination: the integrator chain, the semi- automated slaughterhouse chain, the controlled slaughter-point chain, and the private slaughter- point chain. In more integrated chains, slaughterhouses held considerable market power, while in more informal value chains, market power was in the hands of traders. Implementation of biosecurity and HPAI control measures was strongly related to the governance structure of the chain, with interactions that accentuating the risk of HPAI. This complex structure is responsible for the existence of a market for sick poultry that has a very negative influence on HPAI control. A combination of a value chain analysis with expertise-based estimates for HPAI introduction and transmission did identify critical actors in the epidemiology of HPAI. Critical actors were all farming sectors, private collecting farms, traditional outlets, and semi-automated slaughterhouses. The poultry business types play a significant role in biosecurity practices; a makloon farm (farming for fee) tends to have a lower adoption than other business types due to lack of incentives. While, the main reason for consumers in Western Java to have a preference for the less safe, wet poultry markets, is their perception of freshness. Consumers had a preference for warm poultry meat, government certification, and product information label. In conclusion, a push strategy, as an incentive mechanism, should be designed in such a way that it pays attention to the interactions between actors in a value chain and their impact on introduction and transmission of disease. Moreover, a pull strategy as an incentive mechanism for consumers forcing producers to improve their production environment into higher levels of biosecurity is expected to be less effective than a push strategy targeting producers.
Supply Chain Optimization, Management and Integration: Emerging Applications

Our rapidly changing world has forced business practitioners, in corporation with academic researchers, to respond quickly and develop effective solution methodologies and techniques to handle new challenges in supply chain systems. Supply Chain Optimization, Management and Integration: Emerging Applications presents readers with a rich collection of ideas from researchers who are bridging the gap between the latest in information technology and supply chain management. This book includes theoretical, analytical, and empirical research, comprehensive reviews of relevant research, and case studies of effective applications in the field of SCM. The use of new technologies, methods, and techniques are emphasized by those who have worked with supply chain management across the world for those in the field of information systems.
Analysis of Short-Term and Long-Term Variability in Measures of Physical Function

Maintaining functional independence is crucial for older adults to have a high quality of life, as well as to reduce the risk of frailty, disability, placement into nursing homes, and debilitating diseases. It is well established that level of physical function declines with age in older adults. Hence, gerontologists have developed measurement tools to assess physical function and to monitor the changes with age. Previous investigators have conducted analysis to evaluate the sensitivity and reliability of shortand long-term measurements of the Short Physical Performance Battery (SPPB), a widely used measure of physical function. Researchers have also investigated the short-term variability of walking speed by accessing the “internal memory” between consecutive measurements. To our knowledge, no one has modeled how the correlation between measurements of physical function decays as a function of sampling time interval. Here we develop robust regression models to examine the temporal correlation of SPPB and walking speed, across large time scales, by combining shortand long-term measurements. Specifically, we developed weighted linear quantile regression models, which capture the decline in temporal correlation for the physical
Time-varying risk behavior and prior investment outcomes: Evidence from Italy

Risk behavior can be capricious and may vary from month to month. We study 62 clients of a private bank in Northern Italy. The individuals are of special interest for several reasons. As active traders, they manage the value-at-risk (VaR) of a portion of their wealth portfolios. In addition, they act alone, i.e., without input from a financial adviser. Based on VaR-statistics, we find that, in general, the subjects become more risk-averse after suffering losses and more risk-seeking after experiencing gains. The monthly gains and losses that alter investor risk behavior represent true changes in wealth but are “on paper” only, i.e., not immediately realized. Our results allow several interpretations, but they are not at odds with a house money effect, or the possibility that overconfident investors trade on illusions. Rapidly shifting risk behavior in fast response to unstable circumstances weakens individual risk tolerance as a deep parameter and key construct of finance theory.
Global controlled consensus of Multi-Agent Systems with different agent dynamics

This paper investigates the global bounded consensus problem of networked Multi-Agent Systems (MAS) exhibiting nonlinear, non-identical agent dynamics with communication time-delays. Globally bounded controlled consensus conditions based on pinning control method and adaptive pinning control method are derived. The proposed consensus criteria ensures that all agents eventually move along desired trajectories in terms of boundedness. The proposed controlled consensus criteria generalizes the case of identical agent dynamics to the case of non-identical agent dynamics, and many related results of other researches in this area can be viewed as special cases of the above results. We finally demonstrate the effectiveness of the theoretical results by means of a numerical simulation.
NMOS symmetric load ring VCOs modeling for submicron technologies

Voltage Controlled Oscillators (VCOs) are a key element in PLL design. The simulation of VCOs is a time consuming process because transient circuit simulations must run long enough that the steady state is attained. Furthermore, the robustness of design against operating and technological conditions must also be tested by simulating the circuits at several corners, thus making the design methodology based in iterative simulation rather prohibitive for this class of circuits. The development of efficient and reliable VCO models is therefore a very important task, not only for the automation of the circuit design, but for design space exploration as well. Besides accuracy and simplicity, models must easily adapt to the rapid technology evolution. In order to grant such robustness, we must develop models based on transistor level technological parameters. This paper presents an accurate model for submicron Voltage Controlled Oscillators (VCOs). The model obtained is based on the Npower MOS model, yielding quite accurate results for sub micron technologies. An example considering a 1.2V TSMC013 VCO is presented, where the accuracy of the results obtained against Hspice simulation is shown. Results obtained in about 2 seconds have 4% average error, compared to simulations taking over 15 minutes.
Design and analysis of new multilevel inverter topology with induction motor load

Multilevel inverter technology has emerged recently as a very important in the area of high-power medium-voltage energy control, with the added advantages of lower THD, lower electromagnetic interference (EMI) and lower dv/dt stresses in output. A new topology of a cascaded multilevel inverter is proposed in this paper that utilizes only eight but the conventional topology has twelve switches for the same seven level output. Because of less number of switches in the circuit, there results in less switching losses, converter cost and installation cost. If the number of the levels is increased then we obtain the perfect sinusoidal output waveform but harmonic is increased. A seven level multilevel inverter is simulated with the induction motor load and its effect on the harmonics spectrum is analyzed. The system will be modelled with the help of MATLAB/SIMULINK.
Impact of elevated CO 2 on shellfish calcification

[1] Ocean acidification resulting from human emissions of carbon dioxide has already lowered and will further lower surface ocean pH. The consequent decrease in calcium carbonate saturation potentially threatens calcareous marine organisms. Here, we demonstrate that the calcification rates of the edible mussel (Mytilus edulis) and Pacific oyster (Crassostrea gigas) decline linearly with increasing pCO2. Mussel and oyster calcification may decrease by 25 and 10%, respectively, by the end of the century, following the IPCC IS92a scenario ( 740 ppmv in 2100). Moreover, mussels dissolve at pCO2 values exceeding a threshold value of 1800 ppmv. As these two species are important ecosystem engineers in coastal ecosystems and represent a large part of worldwide aquaculture production, the predicted decrease of calcification in response to ocean acidification will probably have an impact on coastal biodiversity and ecosystem functioning as well as potential ly lead to signif icant economic loss. Citation: Gazeau, F. , C. Quiblier, J. M. Jansen, J.-P. Gattuso, J. J. Middelburg, and C. H. R. Heip (2007), Impact of elevated CO2 on shellfish calcification, Geophys. Res. Lett. , 34, L07603, doi:10.1029/2006GL028554.
Microanalysis of Multimodal Communication in Therapy: A Case of Relational Trauma in Parent-Infant Psychoanalytic Psychotherapy

ABSTRACT This article explains the role of multimodal, microanalytic examinations of the therapeutic process in parent-infant psychotherapy. The work described involves the adaptation of the microanalytic approach that has been applied to exploring the dyad and the rich interactional sequences of behaviors that constitute the parent-infant relationship. The approach in this article widens the focus to include the therapist’s interactions with parent and infant in considering how parent-infant psychotherapy works. Using a clinical case study, several perspectives of the therapeutic processes, including transcripts from videoed sessions, microanalysis of a brief five-second event; clinical session notes, and the therapist’s own narrative, are drawn upon to follow the therapeutic encounter and to consider how the micro-interventions on the part of the therapist, often in the form of subtle embodied communications, interact with the evolving interactional behaviors of the dyad to bring about change in the parent-infant relationship.
Using Convolutional Neural Networks to Discover Cogntively Validated Features for Gender Classification

The human visual cortex is extremely adept at distinguishing between male and female faces, or performing "Gender Classification". While the subject of face detection and recognition has received a lot of focus, research into the features or cognitive processes that are useful for identifying gender have received relatively little attention. Researchers have attempted to extract hand crafted features like wavelet coefficients, histograms etc. on the basis of which to generate a model to classify the male and female faces. However, these models tend to compress the image into a vector and disregard the two dimensional spatial correlations between the pixels in an image. Additionally, these features have to hand crafted and may or may not be ideal for the classification at hand. Ideally, the system should be able to generate specific features from the input face image which would help in classification of male faces from female faces. In this paper and a Deep Convolution Neural Network (CNN) model is presented for gender classification. The features generated by the CNN appear to agree with known results from the cognitive science community indicating that these models may be closer to biological neuronal processes governing gender classification. The classification results are compared with different regularization techniques and other standard classifiers, and the CNN models yield higher accuracy than both svms and random forest classifiers.
The Role of Pre-Existing Diabetes Mellitus on Hepatocellular Carcinoma Occurrence and Prognosis: A Meta-Analysis of Prospective Cohort Studies

Background The impact of pre-existing diabetes mellitus (DM) on hepatocellular carcinoma (HCC) occurrence and prognosis is complex and unclear. The aim of this meta-analysis is to evaluate the association between pre-existing diabetes mellitus and hepatocellular carcinoma occurrence and prognosis. Methods We searched PubMed, Embase and the Cochrane Library from their inception to January, 2011 for prospective epidemiological studies assessing the effect of pre-existing diabetes mellitus on hepatocellular carcinoma occurrence, mortality outcomes, cancer recurrence, and treatment-related complications. Study-specific risk estimates were combined by using fixed effect or random effect models. Results The database search generated a total of 28 prospective studies that met the inclusion criteria. Among these studies, 14 reported the risk of HCC incidence and 6 studies reported risk of HCC specific mortality. Six studies provided a total of 8 results for all-cause mortality in HCC patients. Four studies documented HCC recurrence risks and 2 studies reported risks for hepatic decomposition occurrence in HCC patients. Meta-analysis indicated that pre-existing diabetes mellitus (DM) was significantly associated with increased risk of HCC incidence [meta-relative risk (RR) = 1.87, 95% confidence interval (CI): 1.15–2.27] and HCC-specific mortality (meta-RR = 1.88, 95%CI: 1.39–2.55) compared with their non-DM counterparts. HCC patients with pre-existing DM had a 38% increased (95% CI: 1.13–1.48) risk of death from all-causes and 91% increased (95%CI: 1.41–2.57) risk of hepatic decomposition occurrence compared to those without DM. In DM patients, the meta-RR for HCC recurrence-free survival was 1.93(95%CI: 1.12–3.33) compared with non-diabetic patients. Conclusion The findings from the current meta-analysis suggest that DM may be both associated with elevated risks of both HCC incidence and mortality. Furthermore, HCC patients with pre-existing diabetes have a poorer prognosis relative to their non-diabetic counterparts.
Dual Role of cAMP in the Transcriptional Regulation of Multidrug Resistance-Associated Protein 4 (MRP4) in Pancreatic Adenocarcinoma Cell Lines

Cyclic AMP represents one of the most studied signaling molecules and its role in proliferation and differentiation processes has been well established. Intracellular cAMP levels are tightly regulated where the MRP4 transporter plays a major role. In the present study, we sought to establish whether cAMP modulated MRP4 expression in pancreatic adenocarcinoma cell lines. Quantitative PCR and western blot studies showed that cAMP-increasing agents enhanced MRP4 transcripts and protein levels in PANC-1 cells. Reporter luciferase experiments carried out in pancreatic AR42J cells showed that intracellular cAMP up-regulates MRP4 through an Epac2- and Rap1- mediated mechanism whereas extracellular cAMP reduced MRP4 promoter activity by a MEK/ERK-mediated pathway. Present results show that cAMP regulates MRP4 promoter activity, and further indicate that the balance between intracellular and extracellular cAMP levels determines MRP4 expression.
Migration and global environmental change: methodological lessons from mountain areas of the global South

Abstract. The relationship between migration and environmental and climatic changes is a crucial yet understudied factor influencing mountain livelihoods in the global South. These livelihoods are often characterized by high prevalence of family farming, widespread dependence on natural resources, and high sensitivity to climatic changes. Except for a limited number of empirical case studies, the literature on migration and global environmental change has not yet moved beyond case study results to address and explain global patterns and specificities of migration in mountain areas of the global South. After an introduction to the topic, the authors present a new synthesis of three field studies combining household surveys, participatory research approach (PRA) tools and key informant interviews in Pakistan, Peru, and Tanzania. This article suggests that the systematic use of transdisciplinary approaches, with a combination of quantitative and qualitative empirical methods, is the key to understanding global migration patterns in rural mountain areas of the global South. The results of our synthesis suggests that survey data should be triangulated with PRA results as well as secondary data in order to build household profiles connecting vulnerability (measured through a multidimensional index) with human mobility patterns. Such profiles can be conducive to better understand the feedback processes between livelihoods and mobility patterns both within each case study and across case studies, helping researchers to draw general lessons.
High Performance Lossless Multimedia Data Compression through Improved Dictionary

The advent of modern electronic world has opened up various fronts in multimedia interaction. They are used in various fields for various purposes of education, entertainment, research and many more. This has led to storage and retrieval of multimedia content regularly. But due to limitations of current technology the disk space and the transmission bandwidth fall behind in the race with the requirement of multimedia content. This imposes a need to compress multimedia content so that they can be easily stored requiring lesser space and easily transferred from one point to another. Some online dictionary based compression technique can be applied to reduce the data packet size. When the repetition rate of the same symbols within the data are high the compression techniques works very well. During the process of encoding and decoding, the building of online dictionary in the primary memory ensures the single pass over the data, and the dictionary need not to be transmitted over the network. Our proposed Improved Dictionary technique scans the data byte-wise, so that the chances of repetition of individual symbols are higher for text messages. Fixed length coding transmits fixed length codes for all dictionary entries. For bigger messages better optimization in terms of size reduction can be achieved through variable length coding with L-Z technique, where transmitted code length corresponding to individual dictionary entries will vary according to the requirement dynamically.
A New Rate 3/4 Transmit Diversity for Five and Six Transmit Antennas with Phase Feedback

We present a rate 3/4 transmit diversity scheme for five or six transmit antennas. The new code provides a diversity order 4 and the same rate as quasi-orthogonal space-time block code (QOSTBC) which has a diversity order 3. Based on the perfect channel phase feedback (CPF) from the receiver to the transmitter, a precoding is employed at the transmitter to assure the acquirement of the full diversity. We also derive the closed-form expression for phase feedback, which is only the function of the channel gains known to the receiver. Moreover, decoding complexity is reduced by the partial linear and symbol-pair maximum likelihood (ML) decoding. Analyzing and simulation results confirm that the proposed transmit diversity scheme outperforms QOSTBC
Characterization of GlnK1 from Methanosarcina mazei Strain Gö1: Complementation of an Escherichia coli glnK Mutant Strain by GlnK1

ABSTRACT Trimeric PII-like signal proteins are known to be involved in bacterial regulation of ammonium assimilation and nitrogen fixation. We report here the first biochemical characterization of an archaeal GlnK protein from the diazotrophic methanogenic archaeon Methanosarcina mazei strain Gö1 and show that M. mazei GlnK1 is able to functionally complement an Escherichia coli glnK mutant for growth on arginine. This indicates that the archaeal GlnK protein substitutes for the regulatory function of E. coli GlnK. M. mazei GlnK1 is encoded in the glnK1-amtB1 operon, which is transcriptionally regulated by the availability of combined nitrogen and is only transcribed in the absence of ammonium. The deduced amino acid sequence of the archaeal glnK1 shows 44% identity to the E. coli GlnK and contains the conserved tyrosine residue (Tyr-51) in the T-loop structure. M. mazei glnK1 was cloned and overexpressed in E. coli, and GlnK1 was purified to apparent homogeneity. A molecular mass of 42 kDa was observed under native conditions, indicating that its native form is a trimer. GlnK1-specific antibodies were raised and used to confirm the in vivo trimeric form by Western analysis. In vivo ammonium upshift experiments and analysis of purified GlnK1 indicated significant differences compared to E. coli GlnK. First, GlnK1 from M. mazei is not covalently modified by uridylylation under nitrogen limitation. Second, heterotrimers between M. mazei GlnK1 and Klebsiella pneumoniae GlnK are not formed. Because M. mazei GlnK1 was able to complement growth of an E. coli glnK mutant with arginine as the sole nitrogen source, it is likely that uridylylation is not required for its regulatory function.