Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Control Theory to Explore the Bullwhip Effect in the Supply Chain for a Deteriorating

The bullwhip effect phenomena in supply chain management were discussed a lot in the literatures. Most of them provided empirical evidences or analytical formulas to demonstrate the existence of the bullwhip effect in a simple two or more echelons supply chain. This paper will explore the phenomena in a quite different situation: a supply chain with deteriorating products. Unlike the conventional statistical or time series approaches, the control theory methodology was used to investigate the bullwhip effect of deteriorating products. It shows that the bullwhip effect was demonstrated effectively by using the control theory approach. The bullwhip effect could be reduced if the deterioration rate is high.
Early Percutaneous Cholecystostomy in Severe Acute Cholecystitis Reduces the Complication Rate and Duration of Hospital Stay

AbstractThe optimal timing of percutaneous cholecystostomy for severe acute cholecystitis is unclear. The aim of this study was to investigate the timing of percutaneous cholecystostomy and its relationship to clinical outcomes in patients with inoperable acute severe cholecystitis.From 2008 to 2010, 209 consecutive patients who were admitted to our hospital due to acute cholecystitis and were treated by percutaneous cholecystostomy were retrospectively reviewed. The time periods from symptom onset to when percutaneous cholecystostomy was performed and when patients were discharged were recorded.In the 209 patients, the median time period between symptom onset and percutaneous cholecystostomy was 23 hours (range, 3–95 hours). The early intervention group (⩽24 hours, n = 109) had a significantly lower procedure-related bleeding rate (0.0% vs 5.0%, P = 0.018) and shorter hospital stay (15.8 ± 12.9 vs 21.0 ± 17.5 days) as compared with the late intervention group (>24 hours, n = 100). Delayed percutaneous cholecystostomy was a significant independent factor for a longer hospital stay (odds ratio 3.03, P = 0.001). In inoperable patients with acute severe cholecystitis, early percutaneous cholecystostomy reduced hospital stay and procedure-related bleeding without increasing the mortality rate.
Platelet Orthomode Transducer for  $Q$-Band Correlation Polarimeter Clusters

This paper presents a Q-band orthomode transducer (OMT) that has been designed according to the mechanical constraints of the platelet (multi-layer) manufacturing strategy. It is composed of a twofold symmetric coupling section with two electrically identical recombination networks. The two OMT outputs lay on the same plane to provide a suitable interface to the correlation unit. The two channels are equalized in both magnitude and phase according to the correlation polarimeter requirements. They also exhibit a very low cross-coupling (-50 dB) and good reflection levels (-28 dB) in the 21% bandwidth.
Simulative scenario analysis of the impact of different green timeshares on urban speed-volume relationship

Travel demand models use speed-flow equations to accurately predict the speed of traffic on urban roads. However, in urban networks, the correlations can be quite complex because they are affected by rather short road segments and signalized intersections resulting in interrupted traffic flows. In this context, the green timeshare of a traffic signal influences the capacity of a corresponding road segment significantly. This paper investigates the impacts of different green timeshares on the speed-volume relationship using a simulative approach. The impacts of both reductions and extensions of green timeshares with respect to statistically significant changes in speed values in undersaturated and saturated traffic conditions are presented.
Adaptive Quantization for Matching Pursuit

We propose an adaptive quantization scheme for matching pursuit. Different quantizers are used in different matching pursuit (MP) stages based on the probability distribution of MP coefficients. The quantizers are optimized for a given rate budget constraint. Additionally, our proposed adaptive quantization scheme finds the optimal quantizers for each stage based on the information known to both encoder and decoder. Our quantization scheme outperforms existing MP encoders
CD44variant exon 9 plays an important role in colon cancer initiating cells

Cancer stem cells(cancer initiating cells) have become increasingly important in the treatment of malignant tumors. CD44 in particular has been identified as a marker for stem cells in colon cancer, which is a high-morbidity tumor. However, many details remain unknown, including identification of the relevant exon. The elucidation of these details could lead to the development of new therapies and improvements in prognosis. We report our findings on the importance of CD44 variant exon 9(v9) of stem cells in colon cancer. Using the anti-CD44 standard form(s) antibody, as well as antibodies for each of the CD44 variant exons, we studied colon cancer cell lines by examining stained images of stem cells in the crypt of normal colon mucosa. Using the anti-CD44v9 antibody that fits the normal colon mucosa stem cells, we screened cells using flow cytometry to examine colony formation, resistance to anticancer drugs, and tumor mass formation after subcutaneous implantation in mice. The stem cell–containing region in the crypt of normal colon mucosa was negative for anti-Ki67 antibody staining; only the anti-CD44 v9 antibody stain was expressed. As for colony formation, resistance to anticancer drugs, and tumor mass formation, cells positive both for anti-CD44s and anti-CD44v9 antibody stains was significantly more frequent than those positive for anti-CD44s antibody stain and negative for anti-CD44v9 antibody stain and those negative both for anti-CD44s and anti-CD44v9 antibody stains. CD44 variant exon 9 plays an important role in colon cancer stem cells.
eflection coefficients in attenuative anisotropic media

Such reservoir rocks as tar sands are characterized by significant attenuation and, in some cases, attenuation anisotropy. Most existing attenuation studies are focused on plane-wave attenuation coefficients, which determine the amplitude decay along the raypath of seismic waves. Here we study the influence of attenuation on PPand PS-wave reflection coefficients for anisotropic media with the main emphasis on transversely isotropic models with a vertical symmetry axis VTI . Concise analytic solutions obtained by linearizing the exact plane-wave reflection coefficients are verified by numerical modeling. To make a substantial contribution to reflection coefficients, attenuation must be strong, with the quality factor Q not exceeding 10. For such highly attenuative media, it is also necessary to take attenuation anisotropy into account if the magnitude of the Thomsen-style
Technical Compatibility and the Mode of Foreign Entry With Network Externalities

We examine the preferences of a foreign firm and a local government over two modes of foreign direct investment: de novo entry and acquisition of the domestic incumbent. Two crucial features of the model are network externalities and partial incompatibility between the domestic and the foreign technology. The relative welfare impact of the two entry modes depends on the degree of market competition and the strength of the network externality. The clash between the foreign firm's choice and the local government's ranking of the two entry modes can motivate limits on the degree of foreign ownership of the local firm.
Research on Incremental Learning Method Based on Support VectorMachine Method

An incremental learning algorithm based on support vector machine was proposed to process large-scale data or data generated in batches. Initial goal concept learnt by standard support vector machine algorithm was updated by an updating model. Compared with the existing incremental learning algorithms, this algorithm can achieve the incremental inverse process and the training time is in inverse proportion. Results show that the algorithm satisfies the three criteria of stability, improvement and recoverability. The main target of this thesis is to find a new SVM learning algorithm based on weighted incremental method above the current SVM algorithms, and this new algorithm will have a better classification performance in large-scale data situation.
Greedy Perimeter Stateless Routing In Vehicular Ad-Hoc Networks

Greedy Perimeter Stateless Routing (GPSR) is a Posi tion-Based Routing Protocol for Wireless Networks t hat uses the Position of routers. GPSR makes greedy for warding decision by using closest neighbor’s information of destination. In GPSR each node has the knowledge of its current physical position and also the neighbo r node, this knowledge about node provides better routing. When a packet reaches a region where there is no closest node to the destination then greedy forwarding is impossible, t he algorithm recover by using perimeter forwarding. By Studying GPSR, we find that Greedy part of GPSR is not alway s finding the most optimized route. In this paper we investigated about different forwarding method of GPSR in wireless network and also find out the problems and their solutions. The main aim of our study was to identify which routing method has better performance in highly mobile env ironment of VANET. Keywords— GPSR; Greedy Forwarding; Perimeter Forwarding; VANET.
An Integrated Model of Knowledge Acquisition: Empirical Evidences in China

This study combines trust, learning and knowledge management theory to develop an integrated model of knowledge acquisition in transition China. We analyze the model using a structural equation model approach, and 218 manufacturing and service firms in China are selected as the samples of this study. The results conclude that: (1) the trust is positively relative commitment to learning; (2) trust is a function of its knowledge interpretation; (3) trust will significantly impact on knowledge acquisition; (4) commitment to learning is a function of its knowledge interpretation; (5) commitment to learning will significantly impact on knowledge acquisition; (6) knowledge interpretation is a function of its knowledge acquisition; (7) knowledge acquisition will significantly impact on performance. Finally, implications for researchers and practitioners are presented.
Evaluation of an intervention program for the reduction of bullying and victimization in schools

The present study evaluates the effect of an intervention program on the reduction of bullying and victimization in schools with a sample of 239 students aged 10-16 years old in Rome, Italy. The program deals with bullying and violence. It consists of three videos and a booklet that help students to develop the social cognitive competence skills to understand the negative consequences of aggressive behavior. The intervention was evaluated using an experimental design with pre-test and post-test analyses. Students were randomly allocated to experimental or control classes. Students completed a self-report questionnaire in which they were asked to indicate on a 5-point scale how often they were victimized or bullied others. Victimization and bullying were assessed by using questions about specific types of actions, a composite measure of victimization and bullying, and a single question about victimization and bullying in general. Results showed that the program worked best for older students, but not for younger ones who in some cases reported an increased level of victimization after the intervention. For older students there was a decrease in victimization according to the sum of types of behavior for the experimental group, but an increase for the control group. The same result was found for direct victimization, having belongings stolen, and being called nasty names. Therefore, the program seemed to be beneficial for older students but possibly damaging for younger students. It is suggested that the program could have worked better with older students because of the cognitive skills it required. Younger students could have reported higher levels of bullying after the intervention because they became more sensitized to the topic of bullying.
A Novel Method to Extract Comparison of Products Using Comparative Questions

Comparing one thing with another is a typical part of human decision making process, especially during an online purchase scheme. To assist decision making it is useful to compare entities that share common utility but have distinguishing peripheral features. Without comparing it is not fair to purchase a product, since it would not give an ideal performance. To get rid of this difficulty, my paper presents an ideal way for automatically mine comparable entities from comparative questions that users posted online. It gives an opportunity to improve the search experience by automatically offering comparisons to user. A weekly supervised bootstrapping algorithm is employed here for comparative question identification and comparable entity extraction by collecting a large online question archive. This is done by detecting whether a given question is comparative or not. A sequential pattern is generated and is called an indicative extraction pattern (IEP) if it can be used to identify comparative questions and extract comparator pairs with high reliability. The results will be very useful in helping users’ exploration of alternative choices by suggesting comparable entities based on other users’ prior requests. Abstract—This electronic document is a “live” template. The various components of your paper [title, text, heads, etc.] are already defined on the style sheet, as illustrated by the portions given in this document. (Abstract) Keywords— Comparative question, Bootstrap algorithm, Comparable entity mining, Indicative Extraction Pattern, Sequential pattern mining.
Using energy difference for speech separation of dual-microphone close-talk system

Using the computational auditory scene analysis (CASA) as a framework, a novel speech separation approach based on dual-microphone energy difference (DMED) is proposed for close-talk system. The energy levels of the two microphones are calculated in time-frequency (T-F) units. The DMEDs are calculated as the energy level ratio between the two microphones, and used as a cue to estimate the signal to noise ratio (SNR) and ideal binary mask (IBM) for mix-acoustic of the close-to-mouth microphone. The binary masked units are grouped to generate the target speech. Test with speeches and different noises show that the algorithm is more than 95 % accurate. As the T-F units’ length increase, the accuracy increase as well. Using automatic speech recognition (ASR) analysis, we show that the proposed algorithm improves speech quality in actual close talk system. Copyright © 2013 IFSA.
Identity, food and landscape character in the urban context

Abstract Urban landscape character has been influenced by the evolving interactions between people and their lifestyles, food and city form. Concerns of urban populations about food production and consumption issues have led to a greater awareness of our links with food and how our food choices influence lifestyles. Consumer literature commonly categorises consumer types or identities, while the landscape literature similarly categorises landscapes through the production of typologies and character areas. In an examination of concept, this paper identifies and examines urban ‘foodscape’ character typologies where the interaction between people and food has a strong influence on the form, function and character of the present landscape. It draws on literature across a range of disciplines and uses an examination of the city of Newcastle upon Tyne, UK to suggest a typology which reveals seven foodscape character types which are described and discussed.
Minimizing Commit Latency of Transactions in Geo-Replicated Data Stores

Cross datacenter replication is increasingly being deployed to bring data closer to the user and to overcome datacenter outages. The extent of the influence of wide-area communication on serializable transactions is not yet clear. In this work, we derive a lower-bound on commit latency. The sum of the commit latency of any two datacenters is at least the Round-Trip Time (RTT) between them. We use the insights and lessons learned while deriving the lower-bound to develop a commit protocol, called Helios, that achieves low commit latencies. Helios actively exchanges transaction logs (history) between datacenters. The received logs are used to decide whether a transaction can commit or not. The earliest point in the received logs that is needed to commit a transaction is decided by Helios to ensure a low commit latency. As we show in the paper, Helios is theoretically able to achieve the lower-bound commit latency. Also, in a real-world deployment on five datacenters, Helios has a commit latency that is close to the optimal.
Peripheral parenteral nutrition: an option for patients with an indication for short-term parenteral nutrition.

OBJECTIVE The aim of this study was to examine and describe our experience with the use of peripheral parenteral nutrition (PPN). METHODS Patients with an indication for parenteral nutrition for less than 15 days received it via a peripheral vein via a short, 20 or 22 gauge French polyurethane catheter. Parenteral nutrition had a final osmolality of 993 mOsm/l and was administered by infusion pump. The nutritional status of patients was assessed by the Subjective Global Assessment (SGA) technique. Patients were followed by a trained nutritional team and the access site was changed if problems developed. RESULTS Fifty-three patients were followed with a mean age of 59.5 +/- 17.5 years. There were 36 males (69.2%). Nutritional requirements were reached in 67.6% of the patients within 2.9 +/- 0.7 days. The mean time on parenteral nutrition was 7.2 +/- 6.6 days. In 74.3% of the cases parenteral nutrition was offered until the end of the planned treatment. Pain at the venipuncture site occurred in 17.1% of the cases, pain and fever in 20% and pain, hyperthermia and edema in 2.8%. No patient developed an abscess. CONCLUSIONS PPN can benefit a great number of patients without the risks linked to a venous central catheter. Complications associated with PPN are low especially when the care and follow-up are provided by a nutritional support team.
Data Transform for Dance Motion Capture Based on Kinect

This paper presents a data conversion method between Kinect raw motion data and standard BVH format file. To verify the feasibility of conversion and correctness of data, the motion data in BVH format is imported into Motion Builder, 3D animation software, forming a demo animation. The results show that data conversion is workable and data are correct.
Trail-directed Java Program Verification

This paper introduces the application of trail-based heuristics for software verification. Trail-directed program verification serves the purpose of shortening an error trail, so that it will be more comprehensible for the user. We explain the concept of two heuristics that are based on the Hammingand FSM-distance between states of a Java program. We then utilize the Java software verifier JPF to implement and test the new heuristics and to compare them to the heuristics that are already provided by this tool.
Support Vector Machines Applied to the Classification of Semantic Relations in Nominalized Noun Phrases

The discovery of semantic relations in text plays an important role in many NLP applications. This paper presents a method for the automatic classification of semantic relations in nominalized noun phrases. Nominalizations represent a subclass of NP constructions in which either the head or the modifier noun is derived from a verb while the other noun is an argument of this verb. Especially designed features are extracted automatically and used in a Support Vector Machine learning model. The paper presents preliminary results for the semantic classification of the most representative NP patterns using four distinct learning models.
The Building of a CBD-Based Domain Ontology in Chinese

This paper describes a method of building a medical ontology prototype in Chinese. During the procedure, we explored the following questions, which are crucial for the task of ontology engineering: (1) are there some more computer-understandable knowledge description models? We proposed a structural and fine-grained knowledge description model called concept-based description model (CBD) to describe the rich knowledge in the ontology. That is, to use other concept or the combination of the related concepts to represent the targeted concept, which is supposed to be more computer-understandable; (2) during large scale ontology engineering, how to use NLP technologies to reduce domain expertspsila work to the minimal? In our work, we used some NLP technologies to try to reduce domain expertspsila work to the minimal as possible as it can. The experiments show the significance of our method.
Supervised Competitive Learning with Backpropagation Network and Fuzzy Logic

SCL assembles a set of learning modules into a supervised learning system to address the stability-plasticity dilemma. Each learning module acts as a similarity detector for a prototype, and includes prototype resetting (akin to that of ART) to respond to new prototypes. Here (Part I) we report SCL results using backpropagation networks as the learning modules. We used two feature extractors: about 30 energy-based features, and a combination of energy-based and graphical features (about 60). ACL recognized 96% (energy) and 99% (energy/graphical) of test digits, and 91% (energy) and 96% (energy/graphical) of test letters. In the accompanying paper (Part II), we report the results of SCL using fuzzy sets as learning moduels for recognizing handwritten digits.
Notes on the S-matrix of bosonic and topological non-critical strings

We show that the equivalence between the c = 1 non-critical bosonic string and the = 2 topologically twisted coset SL(2)/U(1) at level one can be checked very naturally on the level of tree-level scattering amplitudes with the use of the Stoyanovsky-Ribault-Teschner map, which recasts H3+ correlation functions in terms of Liouville field theory amplitudes. This observation can be applied equally well to the topologically twisted SL(2)n/U(1) coset with n > 1, which has been argued recently to be equivalent with a c < 1 non-critical bosonic string whose matter part is defined by a time-like linear dilaton CFT.
Palmprint recognition using Fisher-Gabor feature extraction

This paper presents a new approach for palmprint recognition using a combined Fisher linear discriminant (FLD) and Gabor Wavelet responses. Gabor wavelets have properties of being more robust to image illuminations, small translations, limited rotations and having a superior feature representation in both spatial and frequency domains. On the other hand, FLD seeks those projections that are efficient for data discrimination and produces well separated classes in low-dimensional subspaces. The new combined method involves convolving a palmprint image with a series of Gabor wavelets at different scales and rotations before extracting features from the resulting Gabor filtered images. Linear discriminant analysis is then applied to the feature vectors for dimension reduction as well as class separability. Experiments show that the proposed method yields a high classification rate even when using a simple classifier when compared with other popular approaches reported in the literature.
Lost in Familiar Places: Creating New Connections between the Individual and Society

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