Miracle-dz/UniFAR-FTUs huggingface dataset:
THE EFFECTS OF AGGRESSIVE ACTIVATION AND THE NEED TO MERGE ON PATHOLOGICAL THINKING IN SCHIZOPHRENIA

Fifty-two schizophrenics were seen individually for five sessions. In each session a base line assessment first was made of the amount of pathological thinking manifested. Then on different days, in counterbalanced order, the Ss were exposed to the following five conditions: 1) subliminal neutral stimulation; 2) subliminal libidinal stimulation; 3) subliminal merging stimulation: 4) subliminal aggressive stimulation; 5) subliminal aggressive stimulation preceded by manipulations designed to increase self-awareness. Each of these conditions was followed by a “critical” assessment of pathological thinking. The major results were: a) as in previous experiments, subliminal aggressive stimulation intensified pathological thinking; b) however, when this stimulation was preceded by the “self-awareness manipulations,” its pathology-inducing effect was nullified; c) subliminal libidinal stimulation did not affect pathological thinking; d) subliminal merging stimulation (i.e., the exposure of a stimulus depicting two figures as merged) showed a trend toward reducing pathological thinking. Additional analyses of these data plus data from a follow-up study indicated that the merging condition significantly diminished pathological thinking in those schizophrenics who experienced themselves as relatively differentiated to begin with. These findings were discussed with the aim of elucidating the motivational state underlying pathological thinking in schizophrenia.
Reduced Renal Clearance of a Zwitterionic Substrate Cephalexin in Mate1-Deficient Mice

Multidrug and toxin extrusion 1 (MATE1/solute carrier 47A1) mediates the transport of not only organic cations but also zwitterions such as cephalexin. However, the contribution of MATE1 to tubular secretion of cephalexin in vivo has not been elucidated. In the present study, we carried out transport experiments of cephalexin via MATE1 and performed pharmacokinetic analyses of cephalexin in Mate1 knockout [Mate1(−/−)] mice. Cephalexin uptake by human MATE1-expressing human embryonic kidney 293 cells exhibited saturable kinetics (Km = 5.9 ± 0.5 mM) and a bell-shaped pH profile with a maximum at pH 7.0. We confirmed that mouse MATE1 also transported cephalexin. After a single intravenous administration of cephalexin (5 mg/kg), Mate1(−/−) mice showed higher plasma concentrations of cephalexin than wild-type [Mate1(+/+)] mice. The urinary excretion of cephalexin for 60 min was significantly reduced, and the renal concentration was markedly increased in Mate1(−/−) mice compared with Mate1(+/+) mice. The renal clearance of cephalexin in Mate1(−/−) mice was approximately 60% of that in Mate1(+/+) mice and seemed to be near the creatinine clearance. In contrast, there were no significant differences between both mice in the pharmacokinetics of anionic cefazolin, which is not a substrate for MATE1. In this study, we demonstrated that MATE1 is responsible for renal tubular secretion of a zwitterionic substrate cephalexin in vivo.
The T‐TEL Method for Assessing Water, Sediment, and Chemical Connectivity

The concept of connectivity has been the subject of a great deal of recent research and provided new insights and breakthroughs on runoff generation processes and watershed biogeochemistry. However, a consensus definition and cohesive mathematical framework that would permit the consistent quantification of hydrologic connectivity, the examination of the interrelationships between water and material (e.g., sediment and chemicals) connectivity, or rigorous study intercomparison, have not been presented by the water resource community. Building on previous conceptualizations and site‐specific or process‐specific metrics, this paper aimed to review the current state of science on hydrologic connectivity and its role in water‐mediated connectivity of material such as solutes and sediment before introducing a conceptual and a mathematical connectivity assessment framework. These frameworks rely on the quantification of Time scales, Thresholds, Excesses and Losses related to water and water‐mediated material transport dynamics and are referred to as the T‐TEL method. Through a small case study, we show how the T‐TEL method allows a wide range of properties to be quantified, namely the occurrence, frequency, duration, magnitude, and spatial extent of water and water‐mediated material connectivity. We also propose a research agenda to refine the T‐TEL method and ensure its usefulness for facilitating the research and management of connectivity in pristine and human‐impacted landscapes.
Shedding Light on the Spatial Diffusion of Disasters

Climate research suggests that global warming will lead to more frequent and more extreme natural disasters. Most disasters are local events with effects on local economic growth. Hence, assessing their economic impacts with the help of econometric country-level analysis may lead to biased results. Moreover, correct identification is further complicated by the possibility that local shocks shift production and consumption to neighboring locations. In this paper, annual night-time light emission data covering about 24,000 grid cells for the years 1992-2013 are matched to geocoded information on meteorological and geological events. Spatial econometric panel methods are applied to account for interdependencies between locations. Interpreting variation in light emissions as reflecting changes in economic activity, findings convey evidence for pronounced local average treatment effects and strong spatial spillovers, particularly for weather shocks. In particular, results suggest that spatial shifts of economic activity after a natural disaster are a rather local phenomenon, stressing the importance of local adaptation policies. Moreover, substantial heterogeneity across income groups and regions is identified.
CIDR: A Cooperative Integrated Dynamic Reﬁning Method for Minimal Feature Removal Problem

The minimal feature removal problem in the post-hoc explanation area aims to identify the minimal feature set (MFS). Prior studies using the greedy algorithm to calculate the minimal feature set lack the exploration of feature interactions under a monotonic assumption which cannot be satisﬁed in general scenarios. In order to address the above limitations, we propose a C ooperative I ntegrated D ynamic R eﬁning method (CIDR) to efﬁciently discover minimal feature sets. Specifically, we design Cooperative Integrated Gradients (CIG) to detect interactions between features. By incorporating CIG and characteristics of the minimal feature set, we transform the minimal feature removal problem into a knapsack problem. Additionally, we devise an auxiliary Minimal Feature Reﬁnement algorithm to determine the minimal feature set from numerous candidate sets. To the best of our knowledge, our work is the ﬁrst to address the minimal feature removal problem in the ﬁeld of natural language processing. Extensive experiments demonstrate that CIDR is capable of tracing representative minimal feature sets with improved interpretability across various models and datasets.
Special Topic

In the electron-driven fast-ignition (FI) approach to inertial confinement fusion, petawatt laser pulses are required to generate MeV electrons that deposit several tens of kilojoules in the compressed core of an imploded DT shell. We review recent progress in the understanding of intense laser–plasma interactions (LPI) relevant to FI. Increases in computational and modelling capabilities, as well as algorithmic developments have led to enhancement in our ability to perform multi-dimensional particle-in-cell simulations of LPI at relevant scales. We discuss the physics of the interaction in terms of laser absorption fraction, the laser-generated electron spectra, divergence, and their temporal evolution. Scaling with irradiation conditions such as laser intensity are considered, as well as the dependence on plasma parameters. Different numerical modelling approaches and configurations are addressed, providing an overview of the modelling capabilities and limitations. In addition, we discuss the comparison of simulation results with experimental observables. In particular, we address the question of surrogacy of today’s experiments for the full-scale FI problem. (Some figures may appear in colour only in the online journal)
Ergonomic Analysis of Human Lumbar Spine Image Using Canny Edge Detection Algorithm

The largest segment of the movable part is the lumbar vertebrae that are composed of vertebral column, starting at the top from L1 to L5. The spinal column, or the backbone, is primarily made up of vertebrae discs, and the spinal cord. The 24 articulating vertebrae, and nine fused vertebrae in the sacrum and the coccyx will combine to form the vertebral column. The inter vertebral discs are used to separate the vertebral columns that are situated in the dorsal aspect of the torso. The commonly specified word spine or simply backbone is said to be the house that protects the spinal cord in its spinal canal. Signals are transmitted and received through the spinal cord which acts as a communication conduit for the brains. It is otherwise known as vertebral column. It consists of 24 separate bony vertebrae together with 5 fused vertebrae. The disc strength and flexibility required to bear the load of the lumbar spine, is provided by means of the unique interaction between the solid and fluid components. The Segmentation of Spine Image between lumbar spines and CT scan spine disc images are done using Bilateral Filter and Canny Edge Detection Algorithm. It is clear that the canny edge detection provides better result than that of other edge detection algorithm. The most difficult problem is to find the correct boundary in a noisy image of spine disc. A standard result can be used to find out absolute edges from noisy images. An optimal solution is produced by the canny edge detection algorithm as that of the original solution. It works efficiently for all kinds of noisy images
Enabling portable animation browsing by transforming animations into comics

This paper presents a media transformation system that transforms animations into comics. The comic presentation not only enhances the efficiency of animation browsing, but also enables users to browse animations just like reading comic books, which is one of the favorite experiences in many people's childhood. We first select representative keyframes, and then devise an optimization framework based on the genetic algorithm to determine how keyframes are grouped and are arranged into the same comic pages. For keyframes in the same page, shot characteristics and keyframe importance are jointly considered to determine the best presentation layout. Subjective evaluation results demonstrate the attractive comic pages please readers and may facilitate efficient browsing and management for animations.
Trisomy 22 Mosaicism from Prenatal to Postnatal Findings: A Case Series and Systematic Review of the Literature

Background: Among aneuploidies compatible with life, trisomy 22 mosaicism is extremely rare, and only about 25 postnatal and 18 prenatal cases have been described in the literature so far. The condition is mainly characterized by facial and body asymmetry, cardiac heart defects, facial dysmorphisms, growth failure, delayed puberty, and variable degrees of neurodevelopmental delay. Problem: The scattered information regarding the condition and the dearth of data on its natural history and developmental outcomes restrict genetic counseling, particularly in prenatal settings. Moreover, a prompt diagnosis is frequently delayed by the negative selection of trisomic cells in blood, with mosaicism percentage varying among tissues, which often entails the need for further testing. Purpose/topic: The aim of our work is to provide assistance in prenatal and postnatal genetic counseling by systematically delineating the current knowledge of the condition. This entails defining the prenatal and postnatal characteristics of the condition and presenting novel data from three cases, both prenatally and postnatally. Additionally, we report the developmental outcomes observed in two new patients.
ARTHROPOD MANAGEMENT & APPLIED ECOLOGY Efficacy of Bt Toxins and Foliar Insecticides Against Bollworm, Helicoverpa zea (Boddie), in Dried Flower Corollas of Cotton

Foliar insecticides and insecticidal protein from Bacillus thuringiensis (Bt) in transgenic cotton are common tools used for bollworm management in cotton. Efficacy of Bt proteins and foliar insecticides can be dependent upon larval location in the plant canopy and time of year. Floral structures are known to be a common food source for bollworm. Floral components can complicate bollworm control with foliar insecti - cides and transgenic cotton by protecting larvae from contact with formulated insecticides and lower concentrations of Bt proteins. Mortality was measured to evaluate the effects of Bt expres - sion and foliar insecticides in flowers of non-Bt, two-gene Bt, and three-gene Bt cotton varieties. Expression of Bt protein in white flowers provided some efficacy after three days. Bollworm mortal - ity at three
Exercise Prescription in Individuals with Prehypertension and Hypertension: Systematic Review and Meta-Analysis

Background : The prevalence of prehypertension and hypertension has been increasing over the years, and is closely related to cardio-vascular and cerebrovascular diseases. Exercise is an effective method of lifestyle intervention, and it aims to lower blood pressure and control other risks. Studies have shown that different modes of exercise have varying effects on blood pressure, and individuals with prehypertension or hypertension need to carry out this intervention by using personalized modes of exercise. Methods : We conducted a systematic review and meta-analysis to evaluate the effects of different modes of exercise regimens on systolic blood pressure, diastolic blood pressure and heart rate in individuals with high-normal blood pressure and hypertension. We included 27 trials, and 2731 individuals were under 8 exercise regimens. Stata12.0 statistical software was used for statistical analysis. Results : Heat pools significantly reduced systolic blood pressure (SBP) by 15.62 mmHg (95% confidence interval [CI]: –23.83, –7.41), and cycling reduced SBP by 14.76 mmHg (–17.04, –12.48). Two to three types of aerobic exercise performed at the same time also significantly reduced diastolic blood pressure (DBP) by 5.61 mmHg (–7.71, –3.52), and isometric handgrip training exercise reduced DBP by 5.57 mmHg (–7.48, –3.66). Cycling also significantly reduced heart rate (HR) by 9.57 beats/minute (–11.25, –7.90). Conclusions : The existing literature suggests that different types of exercise can effectively reduce the levels of SBP, DBP and HR in individuals with prehypertension or hypertension.
Exact, robust, and e ﬃ cient regularized Booleans on general 3D meshes

Computing Boolean operations (Booleans) of 3D polyhedra / meshes is a basic and essential task in many domains, such as computational geometry, computer-aided design, and constructive solid geometry. Besides their utility and importance, Booleans are challenging to compute when dealing with meshes, because of topological changes, geometric degeneracies, etc. Most prior art techniques either su ﬀ er from robustness issues, deal with a restricted class of input / output meshes, or provide only approximate results. We overcome these limitations and present an exact and robust approach performing on general meshes, required to be only closed and orientable. Our method is based on a few geometric and topological predicates that allow to handle all input / output cases considered as degenerate in existing solutions, such as voids, non-manifold, disconnected, and unbounded meshes, and to robustly deal with special input conﬁgurations. Our experimentation showed that our more general approach is also more robust and more e ﬃ cient than Maya’s implementation ( × 3), CGAL’s robust Nef polyhedra ( × 5), and recent plane-based approaches. Finally, we also present a complete benchmark intended to validate Boolean algorithms under relevant and challenging scenarios, and we successfully ascertain both our algorithm and implementation with it.
Robust face recognition via double low-rank matrix recovery for feature extraction

Feature extraction is one of the most fundamental problems in face recognition tasks. In this paper, motivated by low-rank representation (LRR) model on exploring the multiple subspace structures of observation data, we propose a double low-rank matrix recovery method to learn low-rank subspaces from face images, where it takes into account the recovery of row space and column space information simultaneously. Applying Augmented Lagrangian Multiplier (ALM), the optimization problem on minimization of nuclear norm is resolved efficiently. By evaluating on public face databases, experimental results show that our proposed method works much better than existing face recognition methods based on feature extraction. It is more robust to outliers, varying illumination and occlusion.
PCIT: A Point Cloud Invariance Transformer

Point clouds data is a type of set, which embedded in a continuous space. This makes point clouds structurally different from images and precludes immediate application in deep network designing.We proposes a new framework named PCIT(Point Cloud Invariance Trans-former) for the task of point cloud learning. PCIT is based on transformer, which achieves huge success in natural language processing and displays great potential in image processing. We investigated several improvement directions for the transformer, and made comparative experiments and effect summary. On this basis, we enhanced the ordinary transformer for the point cloud. We used multi-kernel dynamic self attention and kernel weight layer to ensure the order invariance and locality of the point cloud. Extensive experiments demonstrate that PCIT achieves the state-of-the-art performance on shape classification tasks.
Smith ScholarWorks Smith ScholarWorks

—Researchers have studied Internet censorship for nearly as long as attempts to censor contents have taken place. Most studies have however been limited to a short period of time and/or a few countries; the few exceptions have traded off detail for breadth of coverage. Collecting enough data for a comprehensive, global, longitudinal perspective remains challenging. In this work, we present ICLab, an Internet measurement platform specialized for censorship research. It achieves a new balance between breadth of coverage and detail of measurements, by using commercial VPNs as vantage points distributed around the world. ICLab has been operated continuously since late 2016. It can currently detect DNS manipulation and TCP packet injection, and overt “block pages” however they are delivered. ICLab records and archives raw observations in detail, making retrospective analysis with new techniques possible. At every stage of processing, ICLab seeks to minimize false positives and manual validation.Within 53,906,532 measurements of individual web pages, collected by ICLab in 2017 and 2018, we observe blocking of 3,602 unique URLs in 60 countries. Using this data, we compare how different blocking techniques are deployed in different regions and/or against different types of content. Our longitudinal monitoring pinpoints changes in censorship in India and Turkey concurrent with political shifts, and our clustering techniques discover 48 previously unknown block pages. ICLab’s broad and detailed measurements also expose other forms of network interference, such as surveillance and malware injection.
Smith ScholarWorks Smith ScholarWorks

In early-phase requirements engineering, modeling stakeholder goals and intentions helps stakeholders understand the problem context and evaluate tradeoffs, by exploring possible “what if” questions. Prior research allows modelers to make evaluation assignments to desired goals and generate possible selections for task and dependency alternatives, but this treats models as static snapshots, where the evaluation of the fulfillment of an intention remains constant once it has been determined. Using these techniques, stakeholders are unable to reason about possible evolutions, leaving questions about project viability unanswered when the fulfillment of goals or availability of components is not guaranteed in the future. In this article, we formalize the Evolving Intentions framework for specifying, modeling, and reasoning about goals that change over time. Using the Tropos language, we specify a set of functions that define how intentions and relationships evolve, and use path-based analysis for asking a variety of “what if” questions about such changes. We illustrate the framework using the Bike Lanes example and prove correctness of the analysis. Finally, we demonstrate scalability and effectiveness, enabling stakeholders to explore model evolution.
Cooperative dry-electrode sensors for multi-lead biopotential and bioimpedance monitoring

Cooperative sensors is a novel measurement architecture that allows the acquiring of biopotential signals on patients in a comfortable and easy-to-integrate manner. The novel sensors are defined as cooperative in the sense that at least two of them work in concert to measure a target physiological signal, such as a multi-lead electrocardiogram or a thoracic bioimpedance. This paper starts by analysing the state-of-the-art methods to simultaneously measure biopotential and bioimpedance signals, and justifies why currently (1) passive electrodes require the use of shielded or double-shielded cables, and (2) active electrodes require the use of multi-wired cabled technologies, when aiming at high quality physiological measurements. In order to overcome the limitations of the state-of-the-art, a new method for biopotential and bioimpedance measurement using the cooperative sensor is then presented. The novel architecture allows the acquisition of the aforementioned biosignals without the need of shielded or multi-wire cables by splitting the electronics into separate electronic sensors comprising each of two electrodes, one for voltage measurement and one for current injection. The sensors are directly in contact with the skin and connected together by only one unshielded wire. This new configuration requires one power supply per sensor and all sensors need to be synchronized together to allow them to work in concert. After presenting the working principle of the cooperative sensor architecture, this paper reports first experimental results on the use of the technology when applied to measuring multi-lead ECG signals on patients. Measurements performed on a healthy patient demonstrate the feasibility of using this novel cooperative sensor architecture to measure biopotential signals and compliance with common mode rejection specification accordingly to international standard (IEC 60601-2-47) has also been assessed. By reducing the need of using complex wiring setups, and by eliminating the presence of central recording devices (cooperative sensors directly sense and store the measured biosignals on the site), the depicted novel technology is a candidate to a novel generation of highly-integrated, comfortable and reliable technologies that measure physiological signals in real-life scenarios.