Miracle-dz/UniFAR-FTUs huggingface dataset:
The assignment heuristic for crossing reduction

Several applications use algorithms for drawing k-layered networks and, in particular, 2-layered networks (i.e. bipartite graphs). Bipartite graphs are commonly drawn in the plane so that all vertices lie on two parallel vertical lines, and an important requirement in drawing such graphs is to minimize edge crossings. Such a problem is NP-complete even when the position of the vertices on one layer is held fixed. This paper presents a heuristic, called the assignment heuristic, for edge crossing minimization in bipartite graphs, which works by reducing the problem to an assignment problem. The main idea of the assignment heuristic is to position simultaneously all the vertices of one layer, so that the mutual interaction of the position of all the vertices can be taken into account. We also show that the idea underlying the assignment heuristic can be effectively applied in other cases requiring edge crossing minimization. >
Optogenetic control of cell function using engineered photoreceptors

Over the past decades, there has been growing recognition that light can provide a powerful stimulus for biological interrogation. Light‐actuated tools allow manipulation of molecular events with ultra‐fine spatial and fast temporal resolution, as light can be rapidly delivered and focused with sub‐micrometre precision within cells. While light‐actuated chemicals such as photolabile ‘caged’ compounds have been in existence for decades, the use of genetically encoded natural photoreceptors for optical control of biological processes has recently emerged as a powerful new approach with several advantages over traditional methods. Here, we review recent advances using light to control basic cellular functions and discuss the engineering challenges that lie ahead for improving and expanding the ever‐growing optogenetic toolkit.
Gated-diode Sense Amplifier for Robust Differential sensing in 6 T SRAM

The reliable operation of SRAM in presence of process variation in sub-100nm devices is largely influenced by periphery circuits, like sense amplifiers, demanding more robust solutions. A new differential sense amplifier for use in standard 6-T SRAM based on gated-diode is proposed and designed. For comparison, three other latch-based sense amplifiers are also designed in 45nm technology. The brief description of each sense amplifier is presented with HSPICE simulation results. With sense amplifier model and reasonable assumption, the deep analysis of effects from process variation proves that gated-diode sense amplifier is the most robust. Index terms – Clamped bit-line sense amplifier (CBLSA), Conventional sense amplifier (CSA), Gateddiode sense amplifier (GDSA), Transconductance sense amplifier or Matsui sense amplifier (TSA),
Does Singing Facilitate Social Bonding

Psychobiological effects of amateur choral singing were studied in a naturalistic controlled within-subjects trial. A mixed group of novice and experienced singers (N = 21) filled out brief ad hoc questionnaires of psychological wellbeing and gave samples of saliva for measuring levels of salivary oxytocin, cortisol, and dehydroepiandrosteron (DHEA) at the beginning of 2 rehearsal sessions and 30 minutes later. The singing condition included warm-up vocal exercises and repertoire pieces. In the chatting condition, dyads of participants talked to each other about recent positive life experiences. Within-subjects, repeated measures analysis of variance (ANOVA) on self-reported and physiological measures revealed significant Time X Condition interactions for psychological wellbeing and oxytocin. Comparisons of mean scores showed patterns of changes favouring singing over chatting. There were no significant interactions for cortisol, DHEA as well as for the cortisol-DHEA-ratio. These results suggest that singing enhances individual psychological wellbeing as well as induces a socio-biological bonding response.
Computed tomographic colonography without cathartic preparation for the detection of colorectal polyps.

BACKGROUND AND AIMS We prospectively compared the performance of low-dose multidetector computed tomographic colonography (CTC) without cathartic preparation with that of colonoscopy for the detection of colorectal polyps. METHODS A total of 203 patients underwent low-dose CTC without cathartic preparation followed by colonoscopy. Before CTC, fecal tagging was achieved by adding diatrizoate meglumine and diatrizoate sodium to regular meals. No subtraction of tagged feces was performed. Colonoscopy was performed 3-7 days after CTC. Three readers interpreted the CTC examinations separately and independently using a primary 2-dimensional approach using multiplanar reconstructions and 3-dimensional images for further characterization. Colonoscopy with segmental unblinding was used as reference standard. The sensitivity of CTC was calculated both on a per-polyp and a per-patient basis. For the latter, specificity, positive predictive values, and negative predictive values were also calculated. RESULTS CTC had an average sensitivity of 95.5% (95% confidence interval [CI], 92.1%-99%) for the identification of colorectal polyps > or =8 mm. With regard to per-patient analysis, CTC yielded an average sensitivity of 89.9% (95% CI, 86%-93.7%), an average specificity of 92.2% (95% CI, 89.5%-94.9%), an average positive predictive value of 88% (95% CI, 83.3%-91.5%), and an average negative predictive value of 93.5% (95% CI, 90.9%-96%). Interobserver agreement was high on a per-polyp basis (kappa statistic range, .61-.74) and high to excellent on a per-patient basis (kappa statistic range, .79-.91). CONCLUSIONS Low-dose multidetector CTC without cathartic preparation compares favorably with colonoscopy for the detection of colorectal polyps.
The symbolic meaning of artifacts for the workplace identity of women in academia

Purpose – The aim of this paper is to investigate the symbolic meaning attributed by women in academia to workplace artifacts. Design/methodology/approach – The research approach is that of auto-ethnography, whereby the authors, as researchers and participants, explore symbolic meaning from artifacts in their working environment. Findings – Three themes emerged on the symbolic meaning from artifacts for women in academia. The theme of “affect” revealed women as uncomfortable in their surroundings; “representation”, renders women invisible within the institution; and women felt themselves to be under “surveillance”. Research limitations/implications – The investigation is limited to one university, which limits generalizability. The implication is to replicate this auto-ethnographical study in other institutions of higher education. Practical implications – This paper implies that architectural, institutional and personal artifacts play an important role in defining women’s workplace identity. Social impli.
Application of entropy of centrality measures to routing in tactical wireless networks

Various Centrality measures such as Degree, Closeness, and Betweenness were introduced in order to analyze networks and understand both the global dynamics of the networks and the roles played by individual nodes. It will be worthwhile to rank the centrality measures of each node and an index of the distribution of centrality measures in the entire network. In this paper, we define the notion of entropy of centrality measures, which extends the concept of centrality to the whole network. We show that this measure has wide range of applications, in network design, from designing maximally efficient networks to identifying dominance of one node or link in the context of entire network. In particular, we present an application to tactical wireless networks.
Survey of Memory Optimization Techniques for Embedded Systems

Memory systems have been pointed out as a main source to the performance and power consumption of embedded software. Embedded systems require low-power consumption, so becomes interesting investigate memory optimization techniques for these systems. There are many techniques in the literature to reduce power/energy consumption and execution time of embedded systems. This work revises and discusses these techniques focusing on hardware and software optimizations.
Extraovarian Primary Peritoneal Carcinomatosis: A Case Report

Patient: Female, 66 Final Diagnosis: Extraovarian primary peritoneal carcinomatosis Symptoms: Abdominal distension with constipation of 3 days, while still passing flatus. She further complained of mild postprandial epigastric pain, but denied nausea or vomiting as well as fever Medication: — Clinical Procedure: — Specialty: Surgery Objective: Rare disease Background: Extraovarian primary peritoneal carcinoma (EOPPC) is a rare malignant epithelial tumor with an age-adjusted incidence rate of 6.78 per million, which arises from the peritoneal lining with minimal or no ovarian involvement. EOPPC is a diagnosis of exclusion with the absence of other identifiable primary sites and after surgical assessment and consideration of the histological report to evaluate the extent of ovarian invasion. Case Report: A 66-year-old woman complained of mild postprandial epigastric pain. Physical exam revealed positive bowel sounds over all 4 quadrants, with a soft, non-tender abdomen. Distension and dullness to percussion were noted. A CT scan revealed peritoneal fluid, and evaluation of the peritoneal fluid showed an elevated white blood cell count, while fulfilling criteria for exudate. There was no bacterial growth from the peritoneal fluid. Serum tumor markers CEA were significantly elevated, suggestive of an underlying malignancy. An exploratory laparoscopy confirmed diffuse carcinomatosis in the omentum, the coloparietal region bilaterally, as well as surrounding small bowel loops, the transverse and sigmoid colon, and the rectum. A bilateral oophorectomy was performed and 2 biopsies from the thickened peritoneum were taken. The histomorphological features from the pathology examination concluded the patient had peritoneal serous carcinoma with uninvolved ovaries. Conclusions: EOPPC may be misdiagnosed as epithelial ovarian cancer, and should be considered in patients with peritoneal carcinomatosis, normal-sized ovaries, and no identifiable primary lesion. Since the common therapeutic strategies achieve comparable survival rates, failed recognition may be without consequences. However, to further improve survival, optimal cytoreductive surgery is essential and should be made a priority in disease management.
Strategies for Dealing with Missing Data in Clinical Trials: From Design to Analysis

Randomized clinical trials are the gold standard for evaluating interventions as randomized assignment equalizes known and unknown characteristics between intervention groups. However, when participants miss visits, the ability to conduct an intent-to-treat analysis and draw conclusions about a causal link is compromised. As guidance to those performing clinical trials, this review is a non-technical overview of the consequences of missing data and a prescription for its treatment beyond the typical analytic approaches to the entire research process. Examples of bias from incorrect analysis with missing data and discussion of the advantages/disadvantages of analytic methods are given. As no single analysis is definitive when missing data occurs, strategies for its prevention throughout the course of a trial are presented. We aim to convey an appreciation for how missing data influences results and an understanding of the need for careful consideration of missing data during the design, planning, conduct, and analytic stages.
Recurrent alterations of TNFAIP3 (A20) in T‐cell large granular lymphocytic leukemia

The pathogenesis of T‐cell large granular lymphocytic leukemia (T‐LGL) is poorly understood, as STAT3 mutations are the only known frequent genetic lesions. Here, we identified non‐synonymous alterations in the TNFAIP3 tumor suppressor gene in 3 of 39 T‐LGL. In two cases these were somatic mutations, in one case the somatic origin was likely. A further case harbored a SNP that is a known risk allele for autoimmune diseases and B cell lymphomas. Thus, TNFAIP3 mutations represent recurrent genetic lesions in T‐LGL that affect about 8% of cases, likely contributing to deregulated NF‐κB activity in this leukemia.
Absence of Msx2 Does Not Affect Cardiac Conduction or Rescue Conduction Defects Associated with Nkx2‐5 Mutation

Introduction: The transcription factors governing embryonic development of the AV conduction system are largely unknown. Heterozygous mutations of the cardiac transcription factor Nkx2‐5 cause AV conduction defects, which are associated with anatomic hypoplasia of the conduction system. In situ expression patterns of Msx2 in the mouse and chick embryonic heart have suggested a developmental function for this transcription factor. Homozygous Nkx2‐5 knockout mouse embryos express Msx2 ectopically throughout the myocardium, suggesting Msx2 affects conduction system development through a transcriptional cascade starting with Nkx2‐5. Several observations support a model in which Msx2 negatively regulates formation of the conduction system and inappropriate Msx2 up‐regulation causes the conduction defects associated with Nkx2‐5 mutation.
A non-linear gray-level appearance model improves active shape model segmentation

Active Shape Models (ASMs), a knowledge-based segmentation algorithm developed by Cootes and Taylor [1995, 1999], have become a standard and popular method for detecting structures in medical images. In ASMs-and various comparable approaches-the model of the object's shape and of its gray-level variations is based the assumption of linear distributions. In this work, we explore a new way to model the gray-level appearance of the objects, using a k-nearest-neighbors (kNN) classifier and a set of selected features for each location and resolution of the Active Shape Model. The construction of the kNN classifier and the selection of features from training images is fully automatic. We compare our approach with the standard ASMs on synthetic data and in four medical segmentation tasks. In all cases, the new method produces significantly better results (p<0.001).
Rheological study of selected pharmaceutical semisolids.

Rheograms were obtained with a Ferranti-Shirley cone and plate viscometer at 20, 2 5, 30, and 35° for 13 pharmaceutical semisolids. As the temperature was raised, all the products studied showed a decrease in viscosity, thixotropy, and yield value. For many of the semisolids there appears to be a straight line relationship between thixotropic area and temperature. For ointments whose base is predominatety white ointment, the viscosity is reduced by a factor of 0.5 for every 5° rise in temperature. At 35° many of the products studied showed similar values for thixotropy and viscosity.
Multicenter Analysis of Long-Term Oncologic Impact of Anastomotic Leakage After Laparoscopic Total Mesorectal Excision

Abstract This study aims to validate the oncologic outcomes of anastomotic leakage (AL) after laparoscopic total mesorectal excision (TME) in a large multicenter cohort. The impact of AL after laparoscopic TME for rectal cancer surgery has not yet been clearly described. This was a multicenter retrospective study of 1083 patients who underwent laparoscopic TME for nonmetastatic rectal cancer (stage 0–III). AL was defined as an anastomotic complication within 30 days of surgery irrespective of requiring a reoperation or interventional radiology. Estimated local recurrence (LR), disease-free survival (DFS), and overall survival (OS) were compared between the leakage group and the no leakage group using the log-rank method. Multivariate Cox-regression analysis was used to adjust confounding for survival. The incidence of AL was 6.4%. Mortality within 30 days of surgery occurred in 1 patient (1.4%) in the leakage group and 2 patients (0.2%) in the no leakage group. The leakage group showed a higher LR rate (6.4% vs 1.8%, P = 0.011). Five-year DFS and OS were significantly lower in the leakage group than the no leakage group (DFS 71.7% vs 82.1%, P = 0.016, OS 81.8% vs 93.5%, P = 0.007). Multivariate analysis showed that AL was an independent poor prognostic factor for DFS and OS (hazard ratio [HR] = 1.6; 95% confidence intervals [CI]: 1.0–2.6; P = 0.042, HR = 2.1; 95% CI: 1.0–4.2; P = 0.028, respectively). AL after laparoscopic TME was significantly associated with an increased rate of LR, systemic recurrence and poor OS.
When Things Matter: A Data-Centric View of the Internet of Things

With the recent advances in radio-frequency identification (RFID), low-cost wireless sensor devices, and Web technologies, the Internet of Things (IoT) approach has gained momentum in connecting everyday objects to the Internet and facilitating machine-to-human and machine-to-machine communication with the physical world. While IoT offers the capability to connect and integrate both digital and physical entities, enabling a whole new class of applications and services, several significant challenges need to be addressed before these applications and services can be fully realized. A fundamental challenge centers around managing IoT data, typically produced in dynamic and volatile environments, which is not only extremely large in scale and volume, but also noisy, and continuous. This article surveys the main techniques and state-of-the-art research efforts in IoT from data-centric perspectives, including data stream processing, data storage models, complex event processing, and searching in IoT. Open research issues for IoT data management are also discussed.
Educating Children in Conflict Zones: Research, Policy, and Practice for Systemic Change---A Tribute to Jackie Kirk

Inspired by the work of the late Dr. Jacqueline Kirk, this book takes a penetrating look at the challenges of delivering quality education to the approximately 39 million out-of-school children around the world who live in situations affected by violent conflict. With chapters by leading researchers on education in war and other conflict zones, the volume provides a comprehensive and critical overview of the links between conflict and children's access to education, as well as a review of the policies and approaches taken by those offering international assistance in this area. Empirical case studies drawn from diverse contextsAfghanistan, Sierra Leone, Rwanda, and Uganda (among others)offer readers a deeper understanding of the educational needs of these children and the practical challenges to meeting these needs.
Variable Binding through Assemblies in Spiking Neural Networks

We propose a model for the binding of variables to concrete fillers in the human brain. The model is based on recent experimental data about corresponding neural processes in humans. First, electrode recordings from the human brain suggest that concepts are represented in the medial temporal lobe (MTL) through sparse sets of neurons (assemblies). Second, fMRI recordings from the human brain suggest that specific subregions of the temporal cortex are dedicated to the representation of specific roles (e.g., subject or object) of concepts in a sentence or visually presented episode. We propose that quickly recruited assemblies of neurons in these subregions act as pointers to previously created assemblies that represent concepts. As a proof of principle, we performed computer simulations of a spiking neural network model that implemented the proposed paradigm for binding through assembly pointers. We show that the model supports basic operations of brain computations, such as structured recall and copying of information.
Automatic Feature Learning for Spatio-Spectral Image Classification With Sparse SVM

Including spatial information is a key step for successful remote sensing image classification. In particular, when dealing with high spatial resolution, if local variability is strongly reduced by spatial filtering, the classification performance results are boosted. In this paper, we consider the triple objective of designing a spatial/spectral classifier, which is compact (uses as few features as possible), discriminative (enhances class separation), and robust (works well in small sample situations). We achieve this triple objective by discovering the relevant features in the (possibly infinite) space of spatial filters by optimizing a margin-maximization criterion. Instead of imposing a filter bank with predefined filter types and parameters, we let the model figure out which set of filters is optimal for class separation. To do so, we randomly generate spatial filter banks and use an active-set criterion to rank the candidate features according to their benefits to margin maximization (and, thus, to generalization) if added to the model. Experiments on multispectral very high spatial resolution (VHR) and hyperspectral VHR data show that the proposed algorithm, which is sparse and linear, finds discriminative features and achieves at least the same performances as models using a large filter bank defined in advance by prior knowledge.
Lysogenic Streptococcus suis Isolate SS2-4 Containing Prophage SMP Showed Increased Mortality in Zebra Fish Compared to the Wild-Type Isolate

Streptococcus suis (S. suis) infection is considered to be a major problem in the swine industry worldwide. Based on the capsular type, 33 serotypes of S. suis have been described, with serotype 2 (SS2) being the most frequently isolated from diseased piglets. Little is known, however, about the pathogenesis and virulence factors of S. suis. Research on bacteriophages highlights a new area in S. suis research. A S. suis serotype 2 bacteriophage, designated SMP, has been previously isolated in our laboratory. Here, we selected a lysogenic isolate in which the SMP phage was integrated into the chromosome of strain SS2-4. Compared to the wild-type isolate, the lysogenic strain showed increased mortality in zebra fish. Moreover the sensitivity of the lysogenic strain to lysozyme was seven times higher than that of the wild-type.
Plasma levels of tumour necrosis factor‐α in patients with chronic periodontitis and type 2 diabetes

Objectives: Studies suggest that elevated circulating tumour necrosis factor-a (TNF-a) may contribute to insulin resistance in patients with type 2 diabetes. The source of plasma TNF has been thought to be adipocytes associated with obesity, but inflammation and infection result in TNF-a production as well. Methods: We studied 46 patients with type 2 diabetes and chronic periodontitis to determine the relationship between plasma TNF-a levels and clinical measures of periodontitis, gingival crevicular fluid (GCF) interleukin-1β (IL-1β), plasma endotoxin, serum glucose, and glycated haemoglobin (HbAlc). TNF-a levels were measured using a high sensitivity enzyme-linked immunosorbent assay. Results: TNF-a showed a significant positive correlation with attachment loss (r = 0.40, p = 0.009), plasma endotoxin (r = 0.33, p = 0.03), and GCF IL-1β (r = 0.33, p = 0.035), but not probing depth (r = 0.28, p = 0.07), bleeding on probing (r = 0.30, p = 0.053), plaque index (r = 0.22, p = 0.17), serum glucose, HbAlc (r = 0.10, p = 0.50), or body mass index (r = 0.077, p = 0.62). A dose-response relationship was observed between periodontitis severity and TNF-a (p = 0.012). Conclusion: The finding that chronic periodontitis is associated with plasma TNF-a levels in subjects with type 2 diabetes supports the hypothesis that periodontal infection and inflammation may contribute to insulin resistance.