Miracle-dz/UniFAR-FTUs huggingface dataset:
Preserved Object Weight Processing after Bilateral Lateral Occipital Complex Lesions

Object interaction requires knowledge of the weight of an object, as well as its shape. The lateral occipital complex (LOC), an area within the ventral visual pathway, is well known to be critically involved in processing visual shape information. Recently, however, LOC has also been implicated in coding object weight before grasping—a result that is surprising because weight is a nonvisual object property that is more relevant for motor interaction than visual perception. Here, we examined the causal role of LOC in perceiving heaviness and in determining appropriate fingertip forces during object lifting. We studied perceptions of heaviness and lifting behavior in a neuropsychological patient (M.C.) who has large bilateral occipitotemporal lesions that include LOC. We compared the patient's performance to a group of 18 neurologically healthy age-matched controls. Participants were asked to lift and report the perceived heaviness of a set of equally weighted spherical objects of various sizes—stimuli which typically induce the size–weight illusion, in which the smaller objects feel heavier than the larger objects despite having identical mass. Despite her ventral stream lesions, M.C. experienced a robust size–weight illusion induced by visual cues to object volume, and the magnitude of the illusion in M.C. was comparable to age-matched controls. Similarly, M.C. evinced predictive fingertip force scaling to visual size cues during her initial lifts of the objects that were well within the normal range. These single-case neuropsychological findings suggest that LOC is unlikely to play a causal role in computing object weight.
Selection Processing in Noun and Verb Production in Left- and Right-Sided Parkinson's Disease Patients

Verbs are more difficult to produce than nouns. Thus, if executive resources are reduced as in Parkinson's disease (PD), verbs are penalized compared to nouns. However, in an experimental condition in which it is the noun that must be selected from a larger number of alternatives compared to the verb, it is the noun production that becomes slower and more prone to errors. Indeed, patients are slower and less accurate than normal subjects when required to produce nouns from verbs (VN) in a morphology derivation tasks (e.g., “osservazione” from “osservare”) [“observation” from “observe”] than verbs from nouns in a morphology generation task, in which only a verb can be generated from the noun (NV) (e.g., “fallire” from “fallimento”) [“to fail” from “failure”]. In the Italian language morphology, in fact, generation and derivation tasks differ in the number of lexical entries among which the response must be selected. The left Inferior Frontal Gyrus (IFG) has been demonstrated to be involved in selection processes. In the present study, we explored if the ability to select words is related to the cortical thickness of the left IFG. Twelve right-sided PD with nigrostriatal hypofunctionality in the left hemisphere (RPD-LH), 9 left-sided PD with nigrostriatal hypofunctionality in the right hemisphere (LPD-RH) and 19 healthy controls (HC) took part in the study. NV and VN production tasks were administered; accuracy and reaction times (RTs) were collected. All 40 subjects received a structural MRI examination. Cortical thickness of the IFG and volumetric measurements for subcortical regions, thought to support selection processes, were computed using FreeSurfer. In VN derivation tasks RPD-LH patients were less accurate than LPD-RH patients (accuracy: 66% vs. 77%). No difference emerged among the three groups in RTs. Task accuracy/RTs and IFG thickness showed a significant correlation only in RPD-LH. Not only nouns (as expected) but also verbs were correlated with cortical thickness. This suggests that the linguistic nature of the stimuli along with executive resources are both relevant during word selection processes. Our data confirm that executive resources and language interact in the left IFG in word production tasks.
In vivo tracking and quantification of inhaled aerosol using magnetic particle imaging towards inhaled therapeutic monitoring

Pulmonary delivery of therapeutics is attractive due to rapid absorption and non-invasiveness but it is challenging to monitor and quantify the delivered aerosol or powder. Currently, single-photon emission computed tomography (SPECT) is used but requires inhalation of radioactive labels that typically have to be synthesized and attached by hot chemistry techniques just prior to every scan. Methods: In this work, we demonstrate that superparamagnetic iron oxide nanoparticles (SPIONs) can be used to label and track aerosols in vivo with high sensitivity using an emerging medical imaging technique known as magnetic particle imaging (MPI). We perform proof-of-concept experiments with SPIONs for various lung applications such as evaluation of efficiency and uniformity of aerosol delivery, tracking of the initial aerosolized therapeutic deposition in vivo, and finally, sensitive visualization of the entire mucociliary clearance pathway from the lung up to the epiglottis and down the gastrointestinal tract to be excreted. Results: Imaging of SPIONs in the lung has previously been limited by difficulty of lung imaging with magnetic resonance imaging (MRI). In our results, MPI enabled SPION lung imaging with high sensitivity, and a key implication is the potential combination with magnetic actuation or hyperthermia for MPI-guided therapy in the lung with SPIONs. Conclusion: This work shows how magnetic particle imaging can be enabling for new imaging and therapeutic applications of SPIONs in the lung.
Risk Factors for Sepsis Based on Sepsis-3 Criteria after Orthotopic Liver Transplantation

Sepsis is a common complication of solid organ transplant procedures and, in particular, can affect the prognosis of orthotopic liver transplantation (OLT). This retrospective study determined the pre-, peri-, and postoperative risk factors for sepsis after OLT, using as reference the 2016 Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). Pre-, peri-, and postoperative clinical data of the sepsis-positive (n = 85) and sepsis-negative (n = 41) groups were analyzed for potential risk factors of OLT-related sepsis. The sepsis-positive patients had a significantly higher rate of dialysis (49.4%), longer time under mechanical ventilation (1.5 d), higher hospitalization costs (0.41 million RMB), and worse survival rate (68.5%), compared with the sepsis-negative patients (4.8%, 1 d, 0.30 million RMB, and 73.1%, resp.). The multivariate logistic analysis identified the following as risk factors for OLT-related sepsis: preoperative Child-Pugh grade C (OR 10.43; 95% CI 2.081–52.292; P = 0.004), preoperative hypercalcemia (OR 6.372; 95% CI 1.693–23.98; P = 0.006), and perioperative acidosis (OR 6.364; 95% CI 1.196–33.869; P = 0.030). Patients with preoperative Child-Pugh grade C, preoperative hypercalcemia, or perioperative acidosis are at higher risk for developing sepsis after OLT. When any of these problems occur, timely sepsis management should be planned.
A Hand-Held Multimedia Translation and Interpretation System with Application to Diet Management

We propose a network independent, hand-held system to translate and disambiguate foreign restaurant menu items in real-time. The system is based on the use of a portable multimedia device, such as a smartphones or a PDA. An accurate and fast translation is obtained using a Machine Translation engine and a context-specific corpora to which we apply two pre-processing steps, called translation standardization and $n$-gram consolidation. The phrase-table generated is orders of magnitude lighter than the ones commonly used in market applications, thus making translations computationally less expensive, and decreasing the battery usage. Translation ambiguities are mitigated using multimedia information including images of dishes and ingredients, along with ingredient lists. We implemented a prototype of our system on an iPod Touch Second Generation for English speakers traveling in Spain. Our tests indicate that our translation method yields higher accuracy than translation engines such as Google Translate, and does so almost instantaneously. The memory requirements of the application, including the database of images, are also well within the limits of the device. By combining it with a database of nutritional information, our proposed system can be used to help individuals who follow a medical diet maintain this diet while traveling.
Heterogeneous Responses of Ovarian Cancer Cells to Silver Nanoparticles as a Single Agent and in Combination with Cisplatin

We investigated the effects of silver nanoparticle (AgNP) exposure in three ovarian cancer cell lines (A2780, SKOV3, and OVCAR3). We found that AgNPs were highly cytotoxic toward A2780 and SKOV3 cells but OVCAR3 cells were less sensitive to AgNPs. In agreement with the cytotoxicity data, AgNPs caused DNA damage in A2780 and SKOV3 cells, but not in OVCAR3 cells. A2780 and SKOV3 showed higher levels of basal reactive oxygen species (ROS) relative to OVCAR3 cells. AgNP exposure increased ROS levels in both A2780 and SKOV3 cells, but not in OVCAR3 cells. We found that the heterogeneous cytotoxicity was specific to the uptake of intact particles and was not due to differences in sensitivity to silver ions. Furthermore, the combination of AgNPs and standard-of-care platinum therapy, cisplatin (cis-diamminedichloroplatinum(II), CDDP), was synergistic for treatment of A2780 andOVCAR3 cells and the combination of AgNPs and CDDP showed a favorable dose reduction in all cell lines tested. These results provide insight into potential applications of AgNPs for treatment of ovarian cancer.
TE Connectivity：创意连接 无线未来

制造业的需求早已今非昔比：更可靠、自动化程度更高、更灵活、扩展性更强、更分散化的生产流程已成为主流发展趋势。 当然,还需要更出色的连接。 生产力和成产效率与连接密不可分,这也是TE Connectivity（以下简称：TE）在过去六十年里始终与制造和流程自动化领军企业保持密切合作的原因,TE始终致力于帮助工业合作伙伴解决连接方面的难题。
Decreased Expression of Sulfatase 2 in the Brains of Alzheimer’s Disease Patients: Implications for Regulation of Neuronal Cell Signaling

Background: The human sulfatase 1 (SULF1) and sulfatase 2 (SULF2) genes modulate cell signaling and homeostasis in many tissues. Gene expression analyses have implicated SULF2 in disease pathogenesis, including Alzheimer’s disease (AD), but changes in brain SULF2 expression have not been directly established. Objective: To investigate the expression of SULF1 and SULF2 in brain tissues from AD cases and cognitively normal controls. Methods: Autopsy tissue from AD cases (n = 20) and age-and gender-matched cognitively normal controls (n = 20) were identified from the Mayo Clinic Alzheimer’s Disease Patient Registry neuropathology database. Tissue slides were stained for SULF1 and SULF2 protein expression in the hippocampus and frontal lobe and an expression score computed from the proportion of cells stained and the intensity of staining (range 0 [no expression] to 9 [marked expression]). Results: SULF2 expression was reduced in AD cases. Compared to cognitively normal controls, SULF2 expression in AD cases was significantly decreased in the hippocampal Cornu Ammonis (CA) (mean score of 6.5 in cases versus 8.3 in controls; p = 0.003), in the gray matter of the parahippocampal gyrus (5.6 in cases versus 7.6 in controls; p = 0.003), and in the frontal lobe gray matter (5.4 in cases versus 7.4 in controls; p = 0.002). There was no difference in SULF1 expression in the hippocampus or frontal lobe of AD cases and controls. As expected there were no differences in SULF1 or SULF2 expression in white matter in AD cases compared to cognitively normal controls. Conclusion: Decreased SULF2 in specific regions of the brain occurs in AD.
ISIC 2018-A Method for Lesion Segmentation

Our team participate in the challenge of Task 1: Lesion Boundary Segmentation , and use a combined network, one of which is designed by ourselves named updcnn net and another is an improved VGG 16-layer net. Updcnn net uses reduced size images for training, and VGG 16-layer net utilizes large size images. Image enhancement is used to get a richer data set. We use boxes in the VGG 16-layer net network for local attention regularization to fine-tune the loss function, which can increase the number of training data, and also make the model more robust. In the test, the model is used for joint testing and achieves good results.
Diversity from genes to ecosystems: A unifying framework to study variation across biological metrics and scales

Biological diversity is a key concept in the life sciences and plays a fundamental role in many ecological and evolutionary processes. Although biodiversity is inherently a hierarchical concept covering different levels of organization (genes, population, species, ecological communities and ecosystems), a diversity index that behaves consistently across these different levels has so far been lacking, hindering the development of truly integrative biodiversity studies. To fill this important knowledge gap, we present a unifying framework for the measurement of biodiversity across hierarchical levels of organization. Our weighted, information‐based decomposition framework is based on a Hill number of order q = 1, which weights all elements in proportion to their frequency and leads to diversity measures based on Shannon's entropy. We investigated the numerical behaviour of our approach with simulations and showed that it can accurately describe complex spatial hierarchical structures. To demonstrate the intuitive and straightforward interpretation of our diversity measures in terms of effective number of components (alleles, species, etc.), we applied the framework to a real data set on coral reef biodiversity. We expect our framework will have multiple applications covering the fields of conservation biology, community genetics and eco‐evolutionary dynamics.
Morphological and Mechanical Properties of the Human Patella Tendon in Adult Males With Achondroplasia

Achondroplasia is a genetic mutation of fibroblast growth factor receptor resulting in impaired growth plate development in long bones due to lower collagen turnover. Despite the characteristic shorter stature and lower strength in Achondroplasic groups, little is known of the tendon mechanical properties under loading. The aim of this study was therefore to conduct a between measure design of patella tendon (PT) mechanical properties (stress, strain, stiffness and Young's Modulus) in 10 men with Achondroplasia (22 ± 3 years) and 17 male controls (22 ± 2 years). PT mechanical properties were measured during isometric maximal voluntary contraction (iMVC) of the knee extensors using ultrasonography. The Achondroplasic group produced 54% less stress at iMVC than controls (29.4 ± 8.0 v 64.5 ± 14.0 MPa, P < 0.001, d = 3.12). Maximal excursion of the Achondroplasic PT was 22% less than controls at iMVC (7.4 ± 2.1 v 5.5 ± 1.7 mm, P < 0.001, d = 0.99), but there was no difference in strain between groups (13 ± 4 v 13 ± 3%, P > 0.05). Achondroplasic PT were 47% less stiff (748 ± 93 v 1418 ± 101 N·mm−1, P < 0.001, d = 6.89) and had a 51% lower Young's modulus (0.39 ± 0.09 v 0.77 ± 0.14 GPa, P < 0.001, d = 3.46) than controls at iMVC. Achondroplasic PT are indeed more compliant than controls which may contribute to lower relative force production. The causes of higher Achondroplasic PT compliance are unclear but are likely due to the collagen related genetic mutation which causes Achondroplasia.
Generative Adversarial Networks for MR-CT Deformable Image Registration

Deformable Image Registration (DIR) of MR and CT images is one of the most challenging registration task, due to the inherent structural differences of the modalities and the missing dense ground truth. Recently cycle Generative Adversarial Networks (cycle-GANs) have been used to learn the intensity relationship between these 2 modalities for unpaired brain data. Yet its usefulness for DIR was not assessed. In this study we evaluate the DIR performance for thoracic and abdominal organs after synthesis by cycle-GAN. We show that geometric changes, which differentiate the two populations (e.g. inhale vs. exhale), are readily synthesized as well. This causes substantial problems for any application which relies on spatial correspondences being preserved between the real and the synthesized image (e.g. plan, segmentation, landmark propagation). To alleviate this problem, we investigated reducing the spatial information provided to the discriminator by decreasing the size of its receptive fields. Image synthesis was learned from 17 unpaired subjects per modality. Registration performance was evaluated with respect to manual segmentations of 11 structures for 3 subjects from the VISERAL challenge. State-of-the-art DIR methods based on Normalized Mutual Information (NMI), Modality Independent Neighborhood Descriptor (MIND) and their novel combination achieved a mean segmentation overlap ratio of 76.7, 67.7, 76.9%, respectively. This dropped to 69.1% or less when registering images synthesized by cycle-GAN based on local correlation, due to the poor performance on the thoracic region, where large lung volume changes were synthesized. Performance for the abdominal region was similar to that of CT-MRI NMI registration (77.4 vs. 78.8%) when using 3D synthesizing MRIs (12 slices) and medium sized receptive fields for the discriminator.
Marker-Assisted Improvement of the Elite Maintainer Line of Rice, IR 58025B for Wide Compatibility (S5n) Gene

The degree of heterosis in different hybrid rice varieties is reported to be at the highest in indica/japonica cross combination, however, there is a problem of sterility and semi-sterility in such inter sub specific hybrids. To overcome this problem, it is essential to develop parental lines having wide compatibility (S5n) gene. In this study, a functional marker S5-InDel was used for marker-assisted backcrossing (MABB) to introgress S5n gene from Dular into the genetic background of a widely grown recurrent parent IR 58025B, a maintainer line of wild-abortive (WA) cytoplasmic male sterile line, IR 58025A. Further, a closely linked marker nksbadh2 was used for the identification of plants devoid of aroma in backcross population to develop hybrids with no aroma. The stringent phenotypic selection followed by background selection of BC3F4 identified plants with 94.51–98.90% of the recurrent parent genome recovery of lines carrying S5n gene. Subsequently, at 10 promising BC3F5 lines possessing S5n gene with high yielding and long-slender grain type were validated for their maintainer behavior through test crosses with IR 58025A. Also the improved lines showed significantly improved spikelet fertility performance while crossed with japonica and javanica testers in comparison to the original recurrent parent. The improved lines developed in the present study, are being converted to CMS lines through marker-assisted backcross breeding to facilitate precise and improved hybrid breeding program in rice.
Guess who? Multilingual Approach For The Automated Generation Of Author-Stylized Poetry

This paper addresses the problem of stylized text generation in a multilingual setup. A version of a language model based on a long short-term memory (LSTM) artificial neural network with extended phonetic and semantic embeddings is used for stylized poetry generation. The quality of the resulting poems generated by the network is estimated through bilingual evaluation understudy (BLEU), a survey and a new cross-entropy based metric that is suggested for the problems of such type. The experiments show that the proposed model consistently outperforms random sample and vanilla-LSTM baselines, humans also tend to associate machine generated texts with the target author.
Transgenic Mouse Models in Cancer Research

The use of existing mouse models in cancer research is of utmost importance as they aim to explore the casual link between candidate cancer genes and carcinogenesis as well as to provide models to develop and test new therapies. However, faster progress in translating mouse cancer model research into the clinic has been hampered due to the limitations of these models to better reflect the complexities of human tumors. Traditionally, immunocompetent and immunodeficient mice with syngeneic and xenografted tumors transplanted subcutaneously or orthotopically have been used. These models are still being widely employed for many different types of studies, in part due to their widespread availability and low cost. Other types of mouse models used in cancer research comprise transgenic mice in which oncogenes can be constitutively or conditionally expressed and tumor-suppressor genes silenced using conventional methods, such as retroviral infection, microinjection of DNA constructs, and the so-called “gene-targeted transgene” approach. These traditional transgenic models have been very important in studies of carcinogenesis and tumor pathogenesis, as well as in studies evaluating the development of resistance to therapy. Recently, the clustered regularly interspaced short palindromic repeats (CRISPR)-based genome editing approach has revolutionized the field of mouse cancer models and has had a profound and rapid impact on the development of more effective systems to study human cancers. The CRISPR/Cas9-based transgenic models have the capacity to engineer a wide spectrum of mutations found in human cancers and provide solutions to problems that were previously unsolvable. Recently, humanized mouse xenograft models that accept patient-derived xenografts and CD34+ cells were developed to better mimic tumor heterogeneity, the tumor microenvironment, and cross-talk between the tumor and stromal/immune cells. These features make them extremely valuable models for the evaluation of investigational cancer therapies, specifically new immunotherapies. Taken together, improvements in both the CRISPR/Cas9 system producing more valid mouse models and in the humanized mouse xenograft models resembling complex interactions between the tumor and its environment might represent one of the successful pathways to precise individualized cancer therapy, leading to improved cancer patient survival and quality of life.
Audio-to-Score Alignment using Transposition-invariant Features

Audio-to-score alignment is an important pre-processing step for in-depth analysis of classical music. In this paper, we apply novel transposition-invariant audio features to this task. These low-dimensional features represent local pitch intervals and are learned in an unsupervised fashion by a gated autoencoder. Our results show that the proposed features are indeed fully transposition-invariant and enable accurate alignments between transposed scores and performances. Furthermore, they can even outperform widely used features for audio-to-score alignment on `untransposed data', and thus are a viable and more flexible alternative to well-established features for music alignment and matching.
Transfer Learning for Action Unit Recognition

This paper presents a classifier ensemble for Facial Expression Recognition (FER) based on models derived from transfer learning. The main experimentation work is conducted for facial action unit detection using feature extraction and fine-tuning convolutional neural networks (CNNs). Several classifiers for extracted CNN codes such as Linear Discriminant Analysis (LDA), Support Vector Machines (SVMs) and Long Short-Term Memory (LSTM) are compared and evaluated. Multi-model ensembles are also used to further improve the performance. We have found that VGG-Face and ResNet are the relatively optimal pre-trained models for action unit recognition using feature extraction and the ensemble of VGG-Net variants and ResNet achieves the best result.