Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Learning Analysis of Upright-Supine High-Efficiency SPECT Myocardial Perfusion Imaging for Prediction of Obstructive Coronary Artery Disease: A Multicenter Study

Combined analysis of SPECT myocardial perfusion imaging (MPI) performed with a solid-state camera on patients in 2 positions (semiupright, supine) is routinely used to mitigate attenuation artifacts. We evaluated the prediction of obstructive disease from combined analysis of semiupright and supine stress MPI by deep learning (DL) as compared with standard combined total perfusion deficit (TPD). Methods: 1,160 patients without known coronary artery disease (64% male) were studied. Patients underwent stress 99mTc-sestamibi MPI with new-generation solid-state SPECT scanners in 4 different centers. All patients had on-site clinical reads and invasive coronary angiography correlations within 6 mo of MPI. Obstructive disease was defined as at least 70% narrowing of the 3 major coronary arteries and at least 50% for the left main coronary artery. Images were quantified at Cedars-Sinai. The left ventricular myocardium was segmented using standard clinical nuclear cardiology software. The contour placement was verified by an experienced technologist. Combined stress TPD was computed using sex- and camera-specific normal limits. DL was trained using polar distributions of normalized radiotracer counts, hypoperfusion defects, and hypoperfusion severities and was evaluated for prediction of obstructive disease in a novel leave-one-center-out cross-validation procedure equivalent to external validation. During the validation procedure, 4 DL models were trained using data from 3 centers and then evaluated on the 1 center left aside. Predictions for each center were merged to have an overall estimation of the multicenter performance. Results: 718 (62%) patients and 1,272 of 3,480 (37%) arteries had obstructive disease. The area under the receiver operating characteristics curve for prediction of disease on a per-patient and per-vessel basis by DL was higher than for combined TPD (per-patient, 0.81 vs. 0.78; per-vessel, 0.77 vs. 0.73; P < 0.001). With the DL cutoff set to exhibit the same specificity as the standard cutoff for combined TPD, per-patient sensitivity improved from 61.8% (TPD) to 65.6% (DL) (P < 0.05), and per-vessel sensitivity improved from 54.6% (TPD) to 59.1% (DL) (P < 0.01). With the threshold matched to the specificity of a normal clinical read (56.3%), DL had a sensitivity of 84.8%, versus 82.6% for an on-site clinical read (P = 0.3). Conclusion: DL improves automatic interpretation of MPI as compared with current quantitative methods.
Histone Deacetylases Enhance Ca2+-Activated K+ Channel KCa3.1 Expression in Murine Inflammatory CD4+ T Cells

The up-regulated expression of the Ca2+-activated K+ channel KCa3.1 in inflammatory CD4+ T cells has been implicated in the pathogenesis of inflammatory bowel disease (IBD) through the enhanced production of inflammatory cytokines, such as interferon-γ (IFN-γ). However, the underlying mechanisms have not yet been elucidated. The objective of the present study is to clarify the involvement of histone deacetylases (HDACs) in the up-regulation of KCa3.1 in the CD4+ T cells of IBD model mice. The expression levels of KCa3.1 and its regulators, such as function-modifying molecules and transcription factors, were quantitated using a real-time polymerase chain reaction (PCR) assay, Western blotting, and depolarization responses, which were induced by the selective KCa3.1 blocker TRAM-34 (1 μM) and were measured using a voltage-sensitive fluorescent dye imaging system. The treatment with 1 μM vorinostat, a pan-HDAC inhibitor, for 24 h repressed the transcriptional expression of KCa3.1 in the splenic CD4+ T cells of IBD model mice. Accordingly, TRAM-34-induced depolarization responses were significantly reduced. HDAC2 and HDAC3 were significantly up-regulated in the CD4+ T cells of IBD model mice. The down-regulated expression of KCa3.1 was observed following treatments with the selective inhibitors of HDAC2 and HDAC3. The KCa3.1 K+ channel regulates inflammatory cytokine production in CD4+ T cells, mediating epigenetic modifications by HDAC2 and HDAC3.
Pupillary contagion is independent of the emotional expression of the face.

The concept of pupillary contagion refers to the automatic imitation of observed pupil size and reflects shared autonomic arousal. Previous studies have linked the experience of sadness to changes in pupil size. Accordingly, in a 2006 Social Cognitive and Affective Neuroscience article, Harrison, Singer, Rotshtein, Dolan, and Critchley found evidence for pupillary contagion when the observed face expressed sadness but not when it showed a neutral, happy, or angry expression. However, differences in eye movements might have influenced these results. Furthermore, the relatively small sample size of the study merits additional replication. In the current study, we modified the experimental design of Harrison et al. by requiring high attention toward the eye region of the face, which minimized differences in eye movements between facial expressions. In doing so, we demonstrate that the degree of pupillary contagion is independent of the observed emotional expression. Instead, pupil size and emotional expression of the shown face independently contribute to the observer's pupil size. The role of pupillary contagion for social communication is discussed. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
The Impact of Renal Tissue Procurement at Bedside on Specimen Adequacy and Best Practices

Objectives Renal biopsy is the gold standard for the diagnosis of both native and allograft renal diseases. We studied the impact of tissue procurement at bedside (TPB) omission on the adequacy of renal biopsies. Methods We compared 120 renal biopsies collected during 2015 using TPB with 111 renal biopsies collected during 2016 when TPB was discontinued. Adequacy criteria were applied as follows: by light microscopy, 10 glomeruli and two arteries for allograft biopsies and seven glomeruli for native biopsies. At least one glomerulus was considered adequate for immunofluorescence and electron microscopy in both groups. Results The rate of inadequacies in allograft biopsies increased significantly, from 12.50% to 21.61% (P < .05), when TPB was discontinued. Conclusions Elimination of TPB service had a negative impact on allograft specimen adequacy. Repeat biopsies add cost and delay patient care. Institutions should take this into consideration when considering omission of TPB.
Conditional WaveGAN

Generative models are successfully used for image synthesis in the recent years. But when it comes to other modalities like audio, text etc little progress has been made. Recent works focus on generating audio from a generative model in an unsupervised setting. We explore the possibility of using generative models conditioned on class labels. Concatenation based conditioning and conditional scaling were explored in this work with various hyper-parameter tuning methods. In this paper we introduce Conditional WaveGANs (cWaveGAN). Find our implementation at https://github.com/acheketa/cwavegan
KADIN VE ERKEKLERDE SOSYAL SERMAYE VE BENLİK KURGULARI ARASINDAKİ İLİŞKİLER

Bireylerin kendilerini ozerk ya da iliskisel hissetmesi, benlik kurgulariyla ilgilidir. Sosyal sermaye, guvene dayali insan iliskilerinin urunudur ve maddi olmayan bir sermaye turudur. Sosyal sermaye; guven, ortak degerler ve iletisim aglari ile birbirine baglanmayi iceren grup aidiyeti duygusundan olusur. Baska insanlari taniyor olmak ve o insanlar ile iletisim halinde olmak, bir yerde, sosyal sermayenin olusmasi icin yeterli degildir. Bu insanlara guvenmek, kendinizi tanidiginiz insanlardan olusan bir gruba ait hissetmek ve iletisim kurdugunuz kisilerle bazi ortak degerleri tasidiginiza inanmak gerekir. Bu arastirmanin amaci, kadin ve erkeklerde iliskisel ve ozerk benlik kurgularini stratejik guven, genellestirilmis guven, kurumsal guven ve ortak degerlerin yordayip yordamadigini ortaya koymaktir. Arastirma grubu 236 universite ogrencisinden olusmaktadir (%66.7 kadin, %33.3 erkek). Verilerin analizinde Pearson Korelasyon katsayisi ve regresyon modeli kullanilmistir. Genel olarak stratejik guven, genellestirilmis guven, kurumsal guven ve ortak degerler ozerk ve iliskisel benligi yordamistir.
Surgical Lip Remodeling After Injection of Permanent Filler

BACKGROUND A major concern regarding permanent lip fillers is difficulty with revision should this be required. Currently, the only way to treat lip sequelae is by surgical remodeling. OBJECTIVES Based on the senior author's 6-year experience, the authors collectively suggest a surgical method to correct lip deformity in such situations. METHODS The records of 38 patients with lip deformity who underwent surgery between 2011 and 2017 after receiving permanent filler injections were analyzed retrospectively. A total of 38 consecutive patients (69 lips) with an average age of 38.8 years (range, 28-52 years) were treated surgically. RESULTS All patients experienced postoperative swelling (average duration, 15 days), and no infections were recorded. In 3 cases, a 1-cm dehiscence was documented, which healed by secondary intention. In 1 case, a hematoma noted several days after surgery resolved spontaneously within 3 weeks. In 2 upper lips, a minor touchup procedure (with the patient under local anesthesia) was performed 9 months after the initial surgery. Overall, patients noted that it took at least 6 to 9 months to achieve natural lip movement. The average time until softening of the lip tissue was 4 months. CONCLUSIONS This study emphasizes the importance of informing patients that complete removal of permanent filler is not always possible. However, most of the authors' patients were pleased with the results. This study also highlights the importance of paying strict attention when approaching the area adjacent to the oral commissures in order to avoid potential reductions in mouth opening that can occur from postoperative scarring. LEVEL OF EVIDENCE: 4
Thread-assisted mucosal defect closure using the locking-clip technique after gastric endoscopic submucosal dissection

Methods of closing mucosal defects after gastric endoscopic submucosal dissection (ESD) have been reported [1–3]. However, closing large mucosal defects in the stomach is considered difficult compared with other parts of the intestinal tract because the submucosal layer is thick [4]. We designed the threadassisted closure method using a lockingclip technique (LCT) for closing mucosal defects. Thread-assisted closure using LCT uses clips and a thread (commercially available dental floss). After setting the clip, the thread is fixed on the proximal side of the clip’s tooth (▶Fig. 1). LCT involves the clip and thread becoming strongly fixed when fully opened. First, a threaded clip is attached to the marginal defect edge followed by the mucosal defect margin on the contralateral side. Next, LCT is performed by pulling the thread and bringing the mucosal defect margins close to each other (▶Video1). The mucosal defect margins are fixed, and the defect base is completely closed by repeating the technique. We closed a mucosal defect of approximately 50mm in size after gastric ESD using thread-assisted closure via LCT. First, the endoscope was pulled out from the stomach, a clip fixed with the thread was attached, and the scope was reinserted. The first clip was attached to the marginal part of the defect on the anal side. Subsequently the second clip was attached to the mucosal defect margin. Finally, LCT was used to completely fix the margins (▶Fig. 2,▶Video1). Repeated LCT helped perform thread-assisted closure multiple times to completely close the defect. The patient was discharged uneventfully. Thread-assisted closure and line-assisted complete closure are effective methods for closing mucosal defects. By using LCT, it was possible to perform threadassisted closure several times with a single thread and bring rigid mucosal defect margins together. Thread-assisted closure using LCT is a safe and effective mucosal defect closure method. Endoscopy_UCTN_Code_TTT_1AO_2AG E-Videos
Source Cell-Phone Identification in the Presence of Additive Noise from CQT Domain

With the widespread availability of cell-phone recording devices, source cell-phone identification has become a hot topic in multimedia forensics. At present, the research on the source cell-phone identification in clean conditions has achieved good results, but that in noisy environments is not ideal. This paper proposes a novel source cell-phone identification system suitable for both clean and noisy environments using spectral distribution features of constant Q transform (CQT) domain and multi-scene training method. Based on the analysis, it is found that the identification difficulty lies in different models of cell-phones of the same brand, and their tiny differences are mainly in the middle and low frequency bands. Therefore, this paper extracts spectral distribution features from the CQT domain, which has a higher frequency resolution in the mid-low frequency. To evaluate the effectiveness of the proposed feature, four classification techniques of Support Vector Machine (SVM), Random Forest (RF), Convolutional Neural Network (CNN) and Recurrent Neuron Network-Long Short-Term Memory Neural Network (RNN-BLSTM) are used to identify the source recording device. Experimental results show that the features proposed in this paper have superior performance. Compared with Mel frequency cepstral coefficient (MFCC) and linear frequency cepstral coefficient (LFCC), it enhances the accuracy of cell-phones within the same brand, whether the speech to be tested comprises clean speech files or noisy speech files. In addition, the CNN classification effect is outstanding. In terms of models, the model is established by the multi-scene training method, which improves the distinguishing ability of the model in the noisy environment than single-scenario training method. The average accuracy rate in CNN for clean speech files on the CKC speech database (CKC-SD) and TIMIT Recaptured Database (TIMIT-RD) databases increased from 95.47% and 97.89% to 97.08% and 99.29%, respectively. For noisy speech files with seen noisy types and unseen noisy types, the performance was greatly improved, and most of the recognition rates exceeded 90%. Therefore, the source identification system in this paper is robust to noise.
Computational design of transformables

We present a computational approach to designing transformables, physical characters that can shape‐shift to take on vastly different forms. The design process begins with a morphological description of an input character and a target object that it should transform into. Guided by a set of objectives that model the core attributes of desirable transformable designs, optimized embeddings are interactively generated. Intuitively, embeddings represent tightly folded character configurations that fit within the target object. From any feasible embedding, skin meshes are then generated for each body part of the character. The process for generating these 3D models is based on a segmentation of the target object, which is achieved through a growth‐based model applied to a multiple level set representation of the transformable. A set of transformation‐aware post‐processing algorithms ensure the feasibility of the final designs. Building on this technical core, our computational design system provides many opportunities for users to inject their intuition and personal preferences into the process of creating transformables, while shielding them from tasks that are challenging and tedious. As a result, they can intuitively explore the vast space of design possibilities. We demonstrated the effectiveness of our computational approach by creating a variety of transformable designs, three of which we fabricate.
Kernel based low-rank sparse model for single image super-resolution

Self-similarity learning has been recognized as a promising method for single image super-resolution (SR) to produce high-resolution (HR) image in recent years. The performance of learning based SR reconstruction, however, highly depends on learned representation coeffcients. Due to the degradation of input image, conventional sparse coding is prone to produce unfaithful representation coeffcients. To this end, we propose a novel kernel based low-rank sparse model with self-similarity learning for single image SR which incorporates nonlocalsimilarity prior to enforce similar patches having similar representation weights. We perform a gradual magnification scheme, using self-examples extracted from the degraded input image and up-scaled versions. To exploit nonlocal-similarity, we concatenate the vectorized input patch and its nonlocal neighbors at different locations into a data matrix which consists of similar components. Then we map the nonlocal data matrix into a high-dimensional feature space by kernel method to capture their nonlinear structures. Under the assumption that the sparse coeffcients for the nonlocal data in the kernel space should be low-rank, we impose low-rank constraint on sparse coding to share similarities among representation coeffcients and remove outliers in order that stable weights for SR reconstruction can be obtained. Experimental results demonstrate the advantage of our proposed method in both visual quality and reconstruction error.
Technical Note - The Competitive Facility Location Problem in a Duopoly: Advances Beyond Trees

We consider a competitive facility location problem on a network where consumers located on vertices wish to connect to the nearest facility. Knowing this, each competitor locates a facility on a vertex, trying to maximize market share. We focus on the two-player case and study conditions that guarantee the existence of a pure-strategy Nash equilibrium for progressively more complicated classes of networks. For general graphs, we show that attention can be restricted to a subset of vertices referred to as the central block. By constructing trees of maximal bi-connected components, we obtain sufficient conditions for equilibrium existence. Moreover, when the central block is a vertex or a cycle (for example, in cactus graphs), this provides a complete and efficient characterization of equilibria. In that case, we show that both competitors locate their facilities in a solution to the 1-median problem, generalizing a well-known insight arising from Hotelling’s model. We further show that an equilibrium must.
More Compact Orthogonal Drawings by Allowing Additional Bends †

Compacting orthogonal drawings is a challenging task. Usually, algorithms try to compute drawings with small area or total edge length while preserving the underlying orthogonal shape. We suggest a moderate relaxation of the orthogonal compaction problem, namely the one-dimensional monotone flexible edge compaction problem with fixed vertex star geometry. We further show that this problem can be solved in polynomial time using a network flow model. An experimental evaluation shows that by allowing additional bends could reduce the total edge length and the drawing area.
Zebrafish Recoverin Isoforms Display Differences in Calcium Switch Mechanisms

Primary steps in vertebrate vision occur in rod and cone cells of the retina and require precise molecular switches in excitation, recovery, and adaptation. In particular, recovery of the photoresponse and light adaptation processes are under control of neuronal Ca2+ sensor (NCS) proteins. Among them, the Ca2+ sensor recoverin undergoes a pronounced Ca2+-dependent conformational change, a prototypical so-called Ca2+-myristoyl switch, which allows selective targeting of G protein-coupled receptor kinase. Zebrafish (Danio rerio) has gained attention as a model organism in vision research. It expresses four different recoverin isoforms (zRec1a, zRec1b, zRec2a, and zRec2b) that are orthologs to the one known mammalian variant. The expression pattern of the four isoforms cover both rod and cone cells, but the differential distribution in cones points to versatile functions of recoverin in these cell types. Initial functional studies on zebrafish larvae indicate different Ca2+-sensitive working modes for zebrafish recoverins, but experimental evidence is lacking so far. The aims of the present study are (1) to measure specific Ca2+-sensing properties of the different recoverin isoforms, (2) to ask whether switch mechanisms triggered by Ca2+ resemble that one observed with mammalian recoverin, and (3) to investigate a possible impact of an attached myristoyl moiety. For addressing these questions, we employ fluorescence spectroscopy, surface plasmon resonance (SPR), dynamic light scattering, and equilibrium centrifugation. Exposure of hydrophobic amino acids, due to the myristoyl switch, differed among isoforms and depended also on the myristoylation state of the particular recoverin. Ca2+-induced rearrangement of the protein-water shell was for all variants less pronounced than for the bovine ortholog indicating either a modified Ca2+-myristoyl switch or no switch. Our results have implications for a step-by-step response of recoverin isoforms to changing intracellular Ca2+ during illumination.
Nitrogen Metabolism and Biomass Production in Forest Trees

Low nitrogen (N) availability is a major limiting factor for tree growth and development. N uptake, assimilation, storage and remobilization are key processes in the economy of this essential nutrient, and its efficient metabolic use largely determines vascular development, tree productivity and biomass production. Recently, advances have been made that improve our knowledge about the molecular regulation of acquisition, assimilation and internal recycling of N in forest trees. In poplar, a model tree widely used for molecular and functional studies, the biosynthesis of glutamine plays a central role in N metabolism, influencing multiple pathways both in primary and secondary metabolism. Moreover, the molecular regulation of glutamine biosynthesis is particularly relevant for accumulation of N reserves during dormancy and in N remobilization that takes place at the onset of the next growing season. The characterization of transgenic poplars overexpressing structural and regulatory genes involved in glutamine biosynthesis has provided insights into how glutamine metabolism may influence the N economy and biomass production in forest trees. Here, a general overview of this research topic is outlined, recent progress are analyzed and challenges for future research are discussed.
An Improved Architecture of a Hardware Accelerator for Factoring Integers with Elliptic Curve Method

Elliptic Curve Method (ECM) is a well-known method for factoring integers, which is usually used in the Number Field Sieve algorithm as a subroutine for factoring smaller integers than the targeted one. ECM is called many times and can be executed in parallel for different inputs. This method mainly consist of simple operations on elliptic curves. Thus, ECM is suitable for hardware implementations that can efficiently reduce computational time. This work describes a new, improved FPGA-based hardware accelerator for ECM, designed for large scale computations. Our accelerator can operate with an on board ARM processor or with an external host computer. This design can factor several numbers at once and can be easily ported to various FPGA boards. Different methods for improving results (e.g. the use of DSP blocks, cache-registers, reorganizing instruction order) are described and their performance is analyzed. As a result, one of the fastest hardware ECM units is achieved.