Miracle-dz/UniFAR-FTUs huggingface dataset:
Laparoscopic Gastric Wedge Resection for Dieulafoy's Disease Following Preoperative Endoscopic Localization With India Ink and Endoscopic Clips

Background: Dieulafoy's lesion is a vascular malformation, usually of the stomach but occasionally of the small or large bowel. It is an uncommon, but clinically significant, source of upper gastrointestinal hemorrhage. Three cases have been reported in the literature of laparoscopic gastric wedge resection of these lesions by using intraoperative endoscopic localization. We present the only reported case of preoperative endoscopic localization of a Dieulafoy's lesion with India ink and an endoscopic clip before laparoscopic resection. Case Report: We present an 82-year-old female patient who presented to the emergency department with 3 episodes of hematemesis. Esophagogastroduodenoscopy revealed an actively bleeding Dieulafoy's lesion in the fundus of the stomach along the greater curvature, which was controlled endoscopically. However, the patient had a recurrent episode of bleeding. Repeat endoscopy was performed and the lesion was tagged with 2 endoscopic clips and marked with India ink. A laparoscopic wedge resection was performed after the India ink was identified in the fundus. The patient did well postoperatively. Conclusion: Preoperative localization of a Dieulafoy's lesion with India ink and endoscopic clips before laparoscopic wedge resection is a feasible procedure. Therefore, no need exists for intraoperative endoscopy to aid in the localization, as previously reported.
Zero-Shot Voice Conversion Based on Speaker Embedding Domain Generalization

In this paper, a zero-shot voice conversion frame-work is constructed by effectively decoupling the semantic and speaker features in speech. The proposed method is based on the pre-trained wav2vec 2.0 model to extract semantic features from source speakers and a WavLM model to extract speaker features from target speakers. We propose the Robust-MAML model to map the speaker feature of the target speaker into a domain generalization space, making it directly applicable to any unregistered speaker domain. Finally, through transfer learning, the speech synthesis model FastSpeech2 integrates the semantic feature and domain-generalized speaker features to synthesize the target speaker's voice. Experimental results show that the proposed method outperforms the common baseline systems in both naturalness and speaker similarity.
Forecasting and Analyzing the Disease Burden of Aged Population in China, Based on the 2010 Global Burden of Disease Study

Background: Forecasting the disease burden of the elderly will contribute to make a comprehensive assessment about physical and mental status of the elderly in China and provide a basis for reducing the negative consequences of aging society to a minimum. Methods: This study collected data from a public database online provided by Global Burden of Disease Study 2010. Grey model GM (1, 1) was used to forecast all-cause and disease-specific rates of disability adjusted life years (DALYs) in 2015 and 2020. Results: After cross-sectional and longitudinal analysis, we found that non-communicable diseases (NCDs) were still the greatest threats in the elderly, followed by injuries. As for 136 predicted causes, more than half of NCDs increased obviously with age, less than a quarter of communicable, material, neonatal, and nutritional disorders or injuries had uptrend. Conclusions: The findings display the health condition of the Chinese elderly in the future, which will provide critical information for scientific and sociological researches on preventing and reducing the risks of aging society.
Accuracy of p53 Codon 72 Polymorphism Status Determined by Multiple Laboratory Methods: A Latent Class Model Analysis

Introduction Studies on the association of a polymorphism in codon 72 of the p53 tumour suppressor gene (rs1042522) with cervical neoplasia have inconsistent results. While several methods for genotyping p53 exist, they vary in accuracy and are often discrepant. Methods We used latent class models (LCM) to examine the accuracy of six methods for p53 determination, all conducted by the same laboratory. We also examined the association of p53 with cytological cervical abnormalities, recognising potential test inaccuracy. Results Pairwise disagreement between laboratory methods occurred approximately 10% of the time. Given the estimated true p53 status of each woman, we found that each laboratory method is most likely to classify a woman to her correct status. Arg/Arg women had the highest risk of squamous intraepithelial lesions (SIL). Test accuracy was independent of cytology. There was no strong evidence for correlations of test errors. Discussion Empirical analyses ignore possible laboratory errors, and so are inherently biased, but test accuracy estimated by the LCM approach is unbiased when model assumptions are met. LCM analysis avoids ambiguities arising from empirical test discrepancies, obviating the need to regard any of the methods as a “gold” standard measurement. The methods we presented here to analyse the p53 data can be applied in many other situations where multiple tests exist, but where none of them is a gold standard.
Apply Combined Model Between VGG16 and LightGBM on Weather Image Recognition

This research implements hybrid deep learning network models for weather image classification. The study proposes to apply a combined model, namely VGG16-LightGBM. In its architecture model, a pre-train convolutional neural network (CNN) name as VGG16 is employed for feature extraction of images and the LightGBM algorithm is used to make classification. The results on accuracy of proposed models were compared with four other models, namely Xception, Inception V3,Vgg19, Vgg16 which are all implemented by transfer learning mechanism on the same dataset. The experimental results proved that the VGG16-LightGBM gives the best performance with the highest accuracy of 81,28%, outperforms the transfer learning technique of other 4 pre-train models in the problem of weather image classification.
A Zero-Shot Deep Learning Approach for Unknown IoT Botnet Attack Detection

In recent years, as digitalization greatly advances, many homes and organizations have adopted Internet of Things (IoTs) networks to manage and regulate different devices in their infrastructure. This presents a vulnerability when a device is attacked by a Botnet as the whole network can be compromised. In such cases, one Botnet can have different behaviors when deployed in another device's environment or multiple Botnet families altogether can target different devices on the network. This poses a challenge in IoT Botnet detection for unseen Botnet families on unknown devices, as the data is unfamiliar. Machine learning (ML) algorithms and more specifically deep learning (DL) methods have proven to be effective in addressing the traditional detection approach where training data includes all samples of the attacking Botnet. However, with new attack data, it is still a remaining problem to accurately discern malicious flows from benign traffic. In this paper, we propose a zero-shot DL approach to detect Botnet samples from both seen and unseen families on unknown devices. Specifically, we propose a Deep Sparse Contrastive Auto-Encoder (DSCAE) model for Botnet detection by boosting performance with the meaningful latent representation of features. We also tested our approach against classical ML methods as well as simple Auto-Encoder. The results demonstrate that our proposed model is able to improve results in most cases and often achieves the highest metric values.
The influence of extraversion on preferences and engagement in pleasant activities in patients with substance use disorders: one size fits all?

A hallmark of the Community Reinforcement Approach (CRA) is its emphasis on getting individuals to increase their engagement in healthy old and new rewarding activities that can compete with substance use. The personality dimension extraversion seems to be an important mechanism underlying activity engagement. A median split classified 265 patients with substance use disorders as high or low on NEO-FFI extraversion scores. Group comparisons indicated that patients with low NEO-FFI extraversion scores reported lower pleasant activity levels in general, and lower intensity of social interactions in particular. The disparity between conditions as far as what they valued was relative, since both groups pinpointed a wealth of potentially pleasant activities that could play a role in achieving non-substance related positive reinforcement for sobriety.
Biomedical Document Triage: Automatic Classification Exploiting Category Specific Knowledge

—We approached the problem of categorizing papers for the 2005 TREC Genomics Track Categorization task in three different ways. In the ﬁrst, we used a machine learning based approach. We used the MeSH ontology and other specialized ontologies from MGI to identify the set of features to be used in the classiﬁcation. In the second, for each of the categories, we identiﬁed a set of terms to use for ﬁltering the articles. In the third, combined approach, we used the machine learning based approach on the ﬁltered set of articles. In all three approaches we incorporate biological knowledge about the classes into the classiﬁcation system to achieve improved utility.
An Ontogenetic Model of Perceptual Organization for a developmental Robot

This paper presents an ontogenetic model of self-organization for robotic intermediary vision. Two mechanisms are under concern. First, the development of low-level local feature detectors that perform a piecewise categorization of the sensory signal. Second, the hierarchical grouping of these local features in a holistic perception. While the grouping mechanism is expressed as a classical agglomerative clustering, underlying similarity measures are not pre-given but developed from the signal statistics.
Expressions of nitrotyrosine and TUNEL immunoreactivities in cultured rat spinal cord neurons after exposure to glutamate, nitric oxide, or peroxynitrite

Although excitotoxic and oxidative stress play important roles in spinal neuron death, the exact mechanism is not fully understood. We examined cell damage of primary culture of 11‐day‐old rat spinal cord by addition of glutamate, nitric oxide (NO) or peroxynitrite (PN) with detection of nitrotyrosine (NT) or terminal deoxynucleotidyl transferase‐mediated dUTP‐biotin in situ nick end labeling (TUNEL). With addition of glutamate, NOC18 (a slow NO releaser) or PN, immunoreactivity for NT became stronger in the cytoplasm of large motor neurons in the ventral horn at 6 to 48 hr and positive in the axons of the ventral horn at 24 to 48 hr. TUNEL positive nuclei were found in spinal large motor neurons from 24 hr, and the positive cell number greatly increased at 48 hr in contrast to the vehicle. Pretreatment of cultures with α‐amino‐3‐hydroxy‐5‐methyl‐4‐isoxazole propionic acid (AMPA)/kainate receptor antagonist, NO‐suppressing agent, and antioxidant protected the immunoreactivity for NT or TUNEL. The present results suggest that both excitotoxic and oxidative stress play an important role in the upregulation of NT nitration and the apoptotic pathway in cultured rat spinal neurons. J. Neurosci. Res. 65:371–377, 2001. © 2001 Wiley‐Liss, Inc.
Design of dual-passband cross-coupled filter using stub-loaded open-loop resonators

Compact open-loop resonators loaded by open stubs are used to design cross-coupled filters with a dual-passband response of chebyshev function. The second passband of the proposed filter is obtained by tuning higher resonant modes of the open-loop resonator by changing the stub length and position. Proper couplings required for the two desired/designed frequencies are obtained by tuning the relative open position of open-loop resonator and the distance between the resonators. Required external coupling is obtained by adjusting the tapping position and dual-frequencies transformer. The S-parameter of the dua-passband filter has been measured. The results show good agreement with the simulation ones. Furthermore, the proposed filter has two transmission zeros and exhibits high skirt selectivity.
Final version of the American Joint Committee on Cancer staging system for cutaneous melanoma.

PURPOSE To revise the staging system for cutaneous melanoma under the auspices of the American Joint Committee on Cancer (AJCC). MATERIALS AND METHODS The prognostic factors analysis described in the companion publication (this issue), as well as evidence from the published literature, was used to assemble the tumor-node-metastasis criteria and stage grouping for the melanoma staging system. RESULTS Major changes include (1) melanoma thickness and ulceration but not level of invasion to be used in the T category (except for T1 melanomas); (2) the number of metastatic lymph nodes rather than their gross dimensions and the delineation of clinically occult (ie, microscopic) versus clinically apparent (ie, macroscopic) nodal metastases to be used in the N category; (3) the site of distant metastases and the presence of elevated serum lactic dehydrogenase to be used in the M category; (4) an upstaging of all patients with stage I, II, and III disease when a primary melanoma is ulcerated; (5) a merging of satellite metastases around a primary melanoma and in-transit metastases into a single staging entity that is grouped into stage III disease; and (6) a new convention for defining clinical and pathologic staging so as to take into account the staging information gained from intraoperative lymphatic mapping and sentinel node biopsy. CONCLUSION This revision will become official with publication of the sixth edition of the AJCC Cancer Staging Manual in the year 2002.
Void Avoidance in Mobile Underwater Sensor Networks

Mobile underwater sensor networks are featured with three-dimensional topology, high node mobility and long propagation delay. Geographic routing has been shown to be very suitable for such networks. However, routing voids pose great challenges on the greedy policy used in most geographic routing protocols. This is especially true for the underwater sensor networks because of node mobility and three-dimensional topology. In this paper, we propose a void avoidance protocol, called Vector-Based Void Avoidance (VBVA), to address the void problem in mobile underwater sensor networks. VBVA adopts two mechanisms, vector-shift and back-pressure, to handle voids. Vector-shift mechanism is used to route data packets along the boundary of the void. Back-pressure mechanism routes data packets backward to bypass a concave void. VBVA handles the void problem on demand and thus does not need to know network topology and void information in advance. Therefore, it is very robust to cope with mobile voids in mobile networks. To the best of our knowledge, VBVA is the first void avoidance protocol to address the three-dimensional and mobile void problems in underwater sensor networks. Our simulation results show that VBVA works effectively and efficiently in mobile underwater sensor networks.
Chippewa Spearfishing, Lake Property Owner/Anglers, and Tourism—A Case Study of Environmental Social Conflict

This article explores ethnic relations surrounding an environmental issue by focusing on Chippewa spearfishing in northern Wisconsin and its impact on local lake property owner/anglers, merchants, fishing guides, and Department of Natural Resources representatives. Tourism has suffered since court rulings have legalized off-reservation spearfishing. These court rulings recognize Chippewa treaty rights going back to 1837. The walleye, a prized fish in this region, has become increasingly scarce and is the focus in this environmentally based social conflict. Using a social constructionist perspective and interviews with 55 persons involved in this controversy, the main features of the conflict are isolated and interpreted, and suggestions are offered for its amelioration. The various stakeholders involved in the dispute have framed the decline in walleye catch in different ways and have made claims that each of their views is valid. For the Chippewa, walleye depletion is an angler problem, and their spearing is claimed to be a sacred entitlement; for the non-Native people, spearfishing is claimed to be an unfair Chippewa privilege that contributes to the decline in walleye catch. These divergent sentiments and interests are shown to be mired in cultural misunderstandings, physical separation between the Chippewa and the non-Native people, and a history of poor social relations.
Setuid Demystified

Access control in Unix systems is mainly based on user IDs, yet the system calls that modify user IDs (uid-setting system calls), such as setuid, are poorly designed, insufficiently documented, and widely misunderstood and misused. This has caused many security vulnerabilities in application programs. We propose to make progress on the setuid mystery through two approaches. First, we study kernel sources and compare the semantics of the uid-setting system calls in three major Unix systems: Linux, Solaris, and FreeBSD. Second, we develop a formal model of user IDs as a Finite State Automaton (FSA) and develop new techniques for automatic construction of such models. We use the resulting FSA to uncover pitfalls in the Unix API of the uid-setting system calls, to identify differences in the semantics of these calls among various Unix systems, to detect inconsistency in the handling of user IDs within an OS kernel, and to check the proper usage of these calls in programs automatically. Finally, we provide general guidelines on the proper usage of the uid-setting system calls, and we propose a high-level API that is more comprehensible, usable, and portable than the usual Unix API.
The hidden effect of hearing acuity on speech recall, and compensatory effects of self-paced listening

Abstract Objective: The purpose of this research was to determine whether negative effects of hearing loss on recall accuracy for spoken narratives can be mitigated by allowing listeners to control the rate of speech input. Design: Paragraph-length narratives were presented for recall under two listening conditions in a within-participants design: presentation without interruption (continuous) at an average speech-rate of 150 words per minute; and presentation interrupted at periodic intervals at which participants were allowed to pause before initiating the next segment (self-paced). Study sample: Participants were 24 adults ranging from 21 to 33 years of age. Half had age-normal hearing acuity and half had mild- to-moderate hearing loss. The two groups were comparable for age, years of formal education, and vocabulary. Results: When narrative passages were presented continuously, without interruption, participants with hearing loss recalled significantly fewer story elements, both main ideas and narrative details, than those with age-normal hearing. The recall difference was eliminated when the two groups were allowed to self-pace the speech input. Conclusion: Results support the hypothesis that the listening effort associated with reduced hearing acuity can slow processing operations and increase demands on working memory, with consequent negative effects on accuracy of narrative recall.
Voice building from insufficient data - classroom experiences with web-based language development tools

To make the goal of building voices in new languages easier and more accessible to non-experts, the combined tasks of phoneme set definition, text selection, prompt recording, lexicon building, and voice creation in Festival are now integrated behind a web-based development environment. This environment has been exercised in a semester-long laboratory course taught at Carnegie Mellon University. Here we report on the students' efforts in building voices for the languages of Bulgarian, English, German, Hindi, Konkani, Mandarin, and Vietnamese. In some cases intelligible synthesizers were built from as little as ten minutes of recorded speech.
Leadership for a Better World: Understanding the Social Change Model of Leadership Development

Preface. About the Authors and Editors. PART 1: SOCIAL CHANGE AND THE SOCIAL CHANGE MODEL OF LEADERSHIP DEVELOPMENT. 1. What Is Social Change (Wendy Wagner)? 2. An Overview of the Social Change Model of Leadership Development (Kristan Cilente). 3. Applying the Social Change Model: A Case Study Approach Jose-Luis Riera). 4. Change (Nurredina Workman). PART 2: SOCIETAL/COMMUNITY VALUES. 5. Citizenship (Jennifer Bonnet). PART 3: GROUP VALUES. 6. Collaboration (Jordan England). 7. Common Purpose (Alex Teh). 8. Controversy with Civility (Cecilio Alvarez). PART 4: INDIVIDUAL VALUES. 9. Consciousness of Self (Justin Fincher). 10. Congruence (Tricia Shalka). 11. Commitment (Ashlee M. Kerkhoff and Daniel T. Ostick). PART 5: CHANGE AGENTS. 12. Becoming a Change Agent (Marybeth J. Drechsler and William A. Jones). Epilogue. Susan R. Komives and Wendy Wagner. Further Readings. Index.
Aircraft noise prediction via aeroacoustic hybrid methods - development and application of onera tools over the last decade : some examples.

This article focuses on advanced noise prediction methodologies, in regard to aircraft noise mitigation. More precisely, the so-called aeroacoustic hybrid methodology is first recalled here, before illustrating its potentialities through several examples of application to realistic aircraft noise problems. Among other things, this paper highlights how Onera has contributed to the development of reliable computational methodologies over the last decade, which can now help in solving aircraft noise issues.
Forelimb preferences in human beings and other species: multiple models for testing hypotheses on lateralization

Functional preferences in the use of right/left forelimbs are not exclusively present in humans but have been widely documented in a variety of vertebrate and invertebrate species. A matter of debate is whether non-human species exhibit a degree and consistency of functional forelimb asymmetries comparable to human handedness. The comparison is made difficult by the variability in hand use in humans and the few comparable studies conducted on other species. In spite of this, interesting continuities appear in functions such as feeding, object manipulation and communicative gestures. Studies on invertebrates show how widespread forelimb preferences are among animals, and the importance of experience for the development of forelimb asymmetries. Vertebrate species have been extensively investigated to clarify the origins of forelimb functional asymmetries: comparative evidence shows that selective pressures for different functions have likely driven the evolution of human handedness. Evidence of a complex genetic architecture of human handedness is in line with the idea of multiple evolutionary origins of this trait.
N-GRAM-BASED AUTHOR PROFILES FOR

We present a novel method for computer-assisted authorship attribution based on characterlevel n-gram author profiles, which is motivated by an almost-forgotten, pioneering method in 1976. The existing approaches to automated authorship attribution implicitly build author profiles as vectors of feature weights, as language models, or similar. Our approach is based on byte-level n-grams, it is language independent, and the generated author profiles are limited in size. The effectiveness of the approach and language independence are demonstrated in experiments performed on English, Greek, and Chinese data. The accuracy of the results is at the level of the current state of the art approaches or higher in some cases.