Miracle-dz/UniFAR-FTUs huggingface dataset:
A case–control study comparing the incidence of early symptoms in pancreatic and biliary tract cancer

Objectives Pancreatic ductal adenocarcinoma (PDAC) and biliary tract cancers (BTC) are often diagnosed late and at an advanced stage. Population-based screening programmes do not exist and diagnosis is primarily dependent on symptom recognition. Recently symptom-based cancer decision support tools (CDSTs) have been introduced into primary care practices throughout the UK to support general practitioners (GPs) in identifying patients with suspected PDAC. However, future refinement of these tools to improve their diagnostic accuracy is likely to be necessary. Setting The Health Improvement Network (THIN) is a primary care database, which includes more than 11 million electronic patient records, from 562 GP practices in the UK. Participants All patients with a diagnosis of PDAC or BTC between 2000 and 2010 were included in the study along with six matched controls; 2773 patients with PDAC, 848 patients with BTC and 15 395 controls. Primary and secondary outcome measures The primary aim of this study was to determine the early symptom profiles of PDAC and BTC. Secondary aims included comparing early symptom trends between BTC and PDAC, defining symptom onset in PDAC and evaluating trends in routine blood tests nearest to the time of diagnosis. Results In the year prior to diagnosis, patients with PDAC visited their GP on a median of 18 (IQR 11–27) occasions. PDAC was associated with 11 alarm symptoms and BTC with 8. Back pain (OR 1.33 (95% CI 1.18 to 1.49) p<0.001), lethargy (1.42 (95% CI 1.25 to 1.62) p<0.001) and new onset diabetes (OR 2.46 (95% CI 2.16 to 2.80)) were identified as unique features of PDAC. Conclusions PDAC and BTC are associated with numerous early alarm symptoms. CDSTs are therefore likely to be useful in identifying these tumours at an early stage. Inclusion of unique symptoms, symptoms with an early onset and routinely performed blood tests is likely to further improve the sensitivity of these tools.
Neonatal Mortality and the Economy Revisited

The association between economic contraction and neonatal mortality previously reported in this Journal is retested using methods and data that respond to criticisms of aggregate time-series work. Results suggest that the risk of neonatal mortality among birth cohorts of black males in the Los Angeles County and Orange County metropolitan areas is increased by unexpectedly low levels of employment in the second trimester. The argument is made that the strength of the effect is probably not sufficient to make the case for stimulating regional economies more compelling.
Paul's Aegean Network: The Strength of Strong Ties

István Czachesz adapts Mark Granovetter's Social Network Analysis (SNA) view, “the strength of weak ties,” that new, innovative information spreads through a network, not through one's intimate family and friends (“strong ties”), but through more distant, hardly known acquaintances (“weak ties”); Paul, constantly on the move, did not make many strong ties, but spread his message through weak ties. This article appreciates, but counterbalances, Czachesz's thesis with the SNA theory that strong ties are necessary for reinforcing risky behavioral change (complex contagions) and with conclusions about recruitment to, and spread of, new religions. It draws attention to Paul's longer stays as an artisan and the kinds of spaces in which he might have stayed. It also develops matrices and a simple sociogram of Paul's strong tie relationships and exchanges based on Paul's Philemon letter.
BTEX in Ambient Air of a Metropolitan City

The environmental fate, global warming effect and human health risk from mono aromatic VOCs are of major concerns among many consequences of their anthropogenic emission. In more than a yearlong study (November 2003 to February 2005) of the city air in Kolkata, India at different seasons in three different sites, the seasonal mean benzene and toluene concentrations varied between 13.8–72.0 μg/m3 and 21.0–83.2 μg/m3 respectively along all the sites. The environmental distribution and load of BTEX (Benzene, Toluene, Ethylbenzene and isomers of Xylene) in different environmental compartment was estimated using a multimedia mass balance model, TaPL3. The total environmental load of BTEX together was estimated to be 9.7 × 104 kg. Contribution of Kolkata metropolitan city towards global warming due to environmental emission of BTEX has been estimated as 1.9 × 105 tons of carbon dioxide equivalent per year which is about 1.1% of yearly direct CO2 emission the city. The consequence of BTEX emission towards human health has been estimated in terms of non-cancer and cancer risk in population due to their inhalation exposure. The cumulative lifetime cancer risk for benzene and ethylbenzene was found to be higher than the acceptable value and range between 3.0 × 105 and 8.9 × 106 in three sites, although the non-cancer health risk was found to be within acceptable limit.
Recognition System for On-Line Sketched Diagrams

We present our recent model of a diagram recognition engine. It extends our previous work which approaches the structural recognition as an optimization problem of choosing the best subset of symbol candidates. The main improvement is the integration of our own text separator into the pipeline to deal with text blocks occurring in diagrams. Second improvement is splitting the symbol candidates detection into two stages: uniform symbols detection and arrows detection. Text recognition is left for post processing when the diagram structure is already known. Training and testing of the engine was done on a freely available benchmark database of flowcharts. We correctly segmented and recognized 93.0% of the symbols having 55.1% of the diagrams recognized without any error. Considering correct stroke labeling, we achieved the precision of 95.7%. This result is superior to the state-of-the-art method with the precision of 92.4%. Additionally, we demonstrate the generality of the proposed method by adapting the system to finite automata domain and evaluating it on own database of such diagrams.
A Hybrid Approach for Selection of Relevant Features for Microarray Datasets

Developing an accurate classifier for high dimensional microarray datasets is a challenging task due to availability of small sample size. Therefore, it is important to determine a set of relevant genes that classify the data well. Traditionally, gene selection method often selects the top ranked genes according to their discriminatory power. Often these genes are correlated with each other resulting in redundancy. In this paper, we have proposed a hybrid method using feature ranking and wrapper method (Genetic Algorithm with multiclass SVM) to identify a set of relevant genes that classify the data more accurately. A new fitness function for genetic algorithm is defined that focuses on selecting the smallest set of genes that provides maximum accuracy. Experiments have been carried on four well-known datasets. The proposed method provides better results in comparison to the results found in the literature in terms of both classification accuracy and number of genes selected. Keywords—Gene Selection, Genetic Algorithm, Microarray datasets, Multi-class SVM.
CUSUM quality control chart for monitoring energy use performance

This paper builds on measuring and evaluating energy use performance of a process using statistical process control charts. This paper discusses the application of the latest SPC tool named cumulative SUM of difference (CUSUM) to monitor energy use data so that abnormal changes can be detected in a timely manner. The application case study to highlight the benefits of CUSUM charts for monitoring energy use performance is presented and performance of these charts is compared to the traditional control chart.
A 4.6Tbits/s 3.6GHz single-cycle NoC router with a novel switch allocator in 65nm CMOS

As chip multiprocessors (CMPs) become the only viable way to scale up and utilize the abundant transistors made available in current microprocessors, the design of on-chip networks is becoming critically important. These networks face unique design constraints and are required to provide extremely fast and high bandwidth communication, yet meet tight power and area budgets. In this paper, we present a detailed design of our on-chip network router targeted at a 36-core shared-memory CMP system in 65nm technology. Our design targets an aggressive clock frequency of 3.6GHz, thus posing tough design challenges that led to several unique circuit and microarchitectural innovations and design choices, including a novel high throughput and low latency switch allocation mechanism, a non-speculative single-cycle router pipeline which uses advanced bundles to remove control setup overhead, a low-complexity virtual channel allocator and a dynamically-managed shared buffer design which uses prefetching to minimize critical path delay. Our router takes up 1.19 mm area and expends 551 mW power at 10% activity, delivering a single-cycle no-load latency at 3.6GHz clock frequency while achieving a peak switching data rate in excess of 4.6Tbits/s per router node.
Cultural and Text Variables in Processing Personal Experiences While Reading Literature

The present study investigated the influence of reader and text variables on personal resonance while reading literature. As the reader variable, the distance between readers' cultural background and the thematic content of the text was studied. A Hungarian short story dealing with themes that are central to the cultural and historical past of that country was presented to Hungarian (culturally proximate) and Danish (culturally distant) readers. As the text style variable, narrative point of view (POV) was manipulated by changing some inside POV passages to outside POV. The findings indicate that cultural proximity did result in the generation of a larger proportion of personally experienced, contextually rich, and vividly remembered events. The occasional use of inside, psychological POV in the story enhanced this effect in the Hungarian (culturally proximate) group, but not in the Danish group. However, the phenomenal quality of remindings elicited locally by reading the inside POV text passages differed from those of the same passages written from the outside POV, irrespective of readers' cultural background. This suggests that compositional text devices, as narrative POV, may have universal effects on literary reading.
Self-efficacy in Internet-based Learning Environments: A Literature Review

This paper reviews 46 papers from 1999 to 2009 regarding self-efficacy in Internet-based learning environments, and discusses three major categories of research: (1) learners’ Internet self-efficacy, assessing learners’ confidence in their skills or knowledge of operating general Internet functions or applications in Internet-based learning; (2) the interplay between learners’ general academic self-efficacy and their Internetbased learning, and (3) learners’ self-efficacy, particularly in terms of Internet-based learning. In general, students’ self-efficacy plays a positive role in their attitude towards and their processes and outcomes derived from Internet-based learning. It was found that for the reviewed studies, a significant amount of research has adopted search tasks to predict students’ learning outcomes in Internet-based settings, implying that search tasks may still be considered as the most commonly implemented Internet-based learning activities. All of the studies utilized questionnaires or surveys for assessing students’ self-efficacy, and mostly selected students in higher education institutes as their samples. It was also found that relatively few empirical studies were conducted from the theoretical perspectives of the initially proposed concept of self-efficacy.
Managerial Turnover in a Changing World

We develop a dynamic theory of managerial turnover in a world in which the quality of the match between a firm and its managers changes stochastically over time. Shocks to managerial productivity are anticipated at the time of contracting but privately observed by the managers. Our key positive result shows that the firm’s optimal retention decisions become more permissive with time. Our key normative result shows that, compared to what is efficient, the firm’s contract induces either excessive retention at all tenure levels or excessive firing at the early stages of the relationship, followed by excessive retention after sufficiently long tenure.
Outcomes of Endoscopically Harvested Saphenous Vein for Lower Extremity Bypass

Abstract Objectives: The purpose of this study was to evaluate the outcomes of endoscopically harvested saphenous vein (EHSV) for lower extremity bypass (LEB) surgery. Methods: Data from 91 consecutive patients who underwent LEB using EHSV between February 2003 and November 2012 were analyzed. Outcomes of interest were wound infection, patency, re-intervention and limb loss. Results: Fifty-eight (64%) and 33 (36%) patients underwent femoropopliteal (FP) and femorotibial (FT) bypass using EHSV. Three (3%) patients had superficial and 1 (1%) deep wound infection. Primary and primary assisted patency at 5 years was 68% and 71% in the FP group and 56% and 65% in the FT group. Six (6%) patients underwent major amputation. No predicting factors for wound infection or graft patency were found. Conclusion: EHSV carries a low incidence of perioperative wound complication and has a reasonable mid-to-long-term patency regardless of the length of vein harvested.
OFDM schemes with non-overlapping time waveforms

For orthogonal frequency division multiplexing (OFDM) schemes, the time waveform plays a major role not only in shaping the spectrum of the transmitted signal but also in separating the signal subcarriers at the receiver. The selection of such waveform is then very important and can make a big difference in spectrum utilization and system performance. The difficulty in using pulse shaping with OFDM appears in the detector design since smooth time waveforms destroy the orthogonality between subcarriers and introduce inter-channel interference (ICI). This paper investigates the use of non-overlapping signal waveforms for OFDM schemes. It is shown that pulse shaping for such schemes can be equivalently achieved using a discrete shaping matrix. Such a shaping structure is very suitable for digital implementation and can be combined with OFDM schemes without affecting their IDFT/DFT operators. It therefore makes the use of guard time interval (cyclic prefix) for OFDM schemes possible with any kind of non-overlapping shaping waveform.
Activation of PPARγ by pioglitazone potentiates the effects of naltrexone on alcohol drinking and relapse in msP rats.

BACKGROUND Pioglitazone is a selective peroxisome proliferator-activated receptor γ (PPARγ) agonist used for the treatment of insulin resistance and type 2 diabetes. Previous studies conducted in our laboratory showed that activation of PPARγ by pioglitazone reduces alcohol drinking, stress-induced relapse, and alcohol withdrawal syndrome in rats. Pioglitazone was not able to prevent relapse elicited by alcohol cues. Conversely, the nonselective opioid antagonist naltrexone has been shown to reduce alcohol drinking and cue- but not stress-induced relapse in rodents. METHODS Based on these findings, this study was sought to determine the efficacy of pioglitazone and naltrexone combination on alcohol intake and relapse behavior. Genetically selected alcohol-preferring Marchigian Sardinian (msP) rats were used for the study. RESULTS Pioglitazone (10 and 30 mg/kg) and naltrexone (0.25 and 1.0 mg/kg) each individually reduced alcohol drinking in msP rats. The combination of the 2 drugs resulted in a more potent alcohol drinking reduction than single agents. Confirming previous studies, pioglitazone (10 and 30 mg/kg) significantly reduced relapse induced by the pharmacological stressor yohimbine (1.25 mg/kg) but not by cues predictive of alcohol availability. Conversely, naltrexone reduced reinstatement of drug seeking elicited by alcohol cues but not by yohimbine. CONCLUSIONS The drug combination was effective in reducing both relapse behaviors. These findings open new vistas in the use pioglitazone in combination with naltrexone for the treatment of alcoholism.
A Survey On: Secure Data Deduplication on Hybrid Cloud Storage Architecture

Data deduplication is one of the most important Data compression techniques used for to removing the duplicate copies of repeating data and it is widely used in the cloud storage for the purpose of reduce the storage space and save bandwidth. To keep the confidentiality of sensitive data while supporting the deduplication, to encrypt the data before outsourcing convergent encryption technique has been proposed . To better protect data security, this project makes the first attempt to formally address the problem of authorized data deduplication . Different from the traditional deduplication system, differential benefits of the user are further considered the duplicate check besides the data itself. Hybrid cloud architecture contains several new deduplication constructions supporting authorized duplicate check. The proposed security models contain the demonstration of security analysis scheme. As a proof of concept, contains the implementation framework of proposed authorized duplicate check scheme and conduct testbed experiments using these prototype. In proposed system contain authorized duplicate check scheme incurs minimal overhead compared to normal operations. General Terms Convergent Encryption, Baseline Algorithm, Dekey Algorithm.
The Mathematics of Statistical Machine Translation: Parameter Estimation

We describe a series of five statistical models of the translation process and give algorithms for estimating the parameters of these models given a set of pairs of sentences that are translations of one another. We define a concept of word-by-word alignment between such pairs of sentences. For any given pair of such sentences each of our models assigns a probability to each of the possible word-by-word alignments. We give an algorithm for seeking the most probable of these alignments. Although the algorithm is suboptimal, the alignment thus obtained accounts well for the word-by-word relationships in the pair of sentences. We have a great deal of data in French and English from the proceedings of the Canadian Parliament. Accordingly, we have restricted our work to these two languages; but we feel that because our algorithms have minimal linguistic content they would work well on other pairs of languages. We also feel, again because of the minimal linguistic content of our algorithms, that it is reasonable to argue that word-by-word alignments are inherent in any sufficiently large bilingual corpus.
Self-Esteem and Religiosity: An Analysis of Catholic Adolescents from Five Cultures

On the basis of a social contextual model this paper hypothesizes: first, a positive relationship between adolescent self-esteem and religiosity across twelve purposive, middle-class, Catholic, samples from cities in five cultures: New York and St. Paul; Merida, Yucatan; San Juan, Puerto Rico; Seville, Spain; and Bonn, West Germany; and second, on the basis of traditional sex-role theory, a stronger relationship between the two variables is hypothesized for females than for males. The findings yield consistent support for the first hypothesis, and mild support for the second in the Latin samples only. The cross-cultural support for the first is underscored and speculation concerning the apparent contradictory evidence for sex-role theories is offered. The emergence of a Latin/non-Latin dichotomy is discussed. Suggested expansions of the topic include motivational and church-sect issues.
The Theoretical Maximum Throughput Calculation for the IEEE802.11g Standard

††† Summary Estimating the throughput of a WiFi connection can be quite complex, even when considering simple scenarios. Indeed, the varying number of parameters specified in the standards makes it hard to understand their impact in terms of delay and throughput. The main contribution of this work is to present a scheme to compute the exact maximum throughput for an IEEE802.11g network. The proposed scheme incorporates all the timings and settings, which allow one to calculate the throughput for different channel spacing and modulation techniques specified in the standard. Experimental and simulated results show the accuracy of the proposed scheme.
Functional connectivity estimation over large networks at cellular resolution based on electrophysiological recordings and structural prior

Despite many structural and functional aspects of the brain organization have been extensively studied in neuroscience, we are still far from a clear understanding of the intricate structure-function interactions occurring in the multi-layered brain architecture, where billions of different neurons are involved. Although structure and function can individually convey a large amount of information, only a combined study of these two aspects can probably shade light on how brain circuits develop and operate at the cellular scale. Here, we propose a novel approach for refining functional connectivity estimates within neuronal networks using the structural connectivity as prior. This is done at the mesoscale, dealing with thousands of neurons while reaching, at the microscale, an unprecedented cellular resolution. The High-Density Micro Electrode Array (HD-MEA) technology, combined with fluorescence microscopy, offers the unique opportunity to acquire structural and functional data from large neuronal cultures approaching the granularity of the single cell. In this work, an advanced method based on probabilistic directional features and heat propagation is introduced to estimate the structural connectivity from the fluorescence image while functional connectivity graphs are obtained from the cross-correlation analysis of the spiking activity. Structural and functional information are then integrated by reweighting the functional connectivity graph based on the structural prior. Results show that the resulting functional connectivity estimates are more coherent with the network topology, as compared to standard measures purely based on cross-correlations and spatio-temporal filters. We finally use the obtained results to gain some insights on which features of the functional activity are more relevant to characterize actual neuronal interactions.
AIDE: An Automatic User Navigation System for Interactive Data Exploration

Data analysts often engage in data exploration tasks to discover interesting data patterns, without knowing exactly what they are looking for. Such exploration tasks can be very labor-intensive because they often require the user to review many results of ad-hoc queries and adjust the predicates of subsequent queries to balance the tradeoff between collecting all interesting information and reducing the size of returned data. In this demonstration we introduce AIDE, a system that automates these exploration tasks. AIDE steers the user towards interesting data areas based on her relevance feedback on database samples, aiming to achieve the goal of identifying all database objects that match the user interest with high efficiency. In our demonstration, conference attendees will see AIDE in action for a variety of exploration tasks on real-world datasets.