Miracle-dz/UniFAR-FTUs huggingface dataset:
The Nerd Factor: The Potential of S&P Adepts to Serve as a Social Resource in the User's Quest for More Secure and Privacy-Preserving Behavior

There are several ways to inform individuals about secure and privacy-preserving behavior in private social environments. Experts who are versed in security and privacy (S&P), who might be social peers, such as family members or friends, can provide advice or give recommendations. In this paper, we specifically investigate how S&P adepts inform peers in their private social environment about security and privacy. For this, we first conducted thirteen in-depth interviews with S&P adepts, revealing 1) their own S&P behavior and strategies in their personal lives, 2) obstacles in S&P conversations with peers, 3) situations in which S&P adepts intervene in the behavior of others, and 4) the perception of S&P adepts and stereotypes. Based on the interview results, we conducted three co-design workshop sessions with S&P adepts to explore options to better support S&P adepts informing their peers about secure and privacy-preserving behavior.
Comparison Of K- Means And Fuzzy C- Means Algorithms

Clustering is the process of grouping feature vectors into classes in the self-organizing mode. Choosing cluster centers is crucial to the clustering. In this paper we compared two fuzzy algorithms: fuzzy c-means algorithm and fuzzy k means algorithm. Fuzzy c-means algorithm uses the reciprocal of distances to decide the cluster centers. The representation reflects the distance of a feature vector from the cluster center but does not differentiate the distribution of the clusters [1, 10, and 11]. The fuzzy k means algorithm in data mining, is a method of cluster analysis which aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean[10,11].
COVID‑19‑associated coagulopathy and disseminated intravascular coagulation Advances in diagnosis and treatment of disseminated intravascular coagulation

The pathology of coronavirus disease 2019 (COVID-19) is exacerbated by the progression of thrombosis, and disseminated intravascular coagulation (DIC), and cytokine storms. The most frequently reported coagulation/fibrinolytic abnormality in COVID-19 is the increase in d -dimer, and its relationship with prognosis has been discussed. However, limits exist to the utility of evaluation by d -dimer alone. In addition, since the coagulation/fibrinolytic condition sometimes fluctuates within a short period of time, regular examinations in recognition of the significance of the examination are desirable. The pathophysiology of disseminated intravascular coagulation (DIC) associated with COVID-19 is very different from that of septic DIC, and both thrombotic and hemorrhagic pathologies should be noted. COVID-19 thrombosis includes macro- and microthrombosis, with diagnosis of the latter depending on markers of coagulation and fibrinolysis. Treatment of COVID19 is classified into antiviral treatment, cytokine storm treatment, and thrombosis treatment. Rather than providing uniform treatment, the treatment method most suitable for the severity and stage should be selected. Combination therapy with heparin and nafamostat is expected to develop in the future. Fibrinolytic therapy and adsorption therapy require further study
Open Research Online Structuring visual exploratory analysis of skill demand

The analysis of increasingly large and diverse data for meaningful interpretation and question answering is handicapped by human cognitive limitations. Consequently, semi-automatic abstraction of complex data within structured information spaces becomes increasingly important, if its knowledge content is to support intuitive, exploratory discovery. Exploration of skill demand is an area where regularly updated, multi-dimensional data may be exploited to assess capability within the workforce to manage the demands of the modern, technology- and data-driven economy. The knowledge derived may be employedbyskilledpractitionersindefiningcareerpathways,toidentifywhere,whenandhowtoupdate their skillsets in line with advancing technology and changing work demands. This same knowledge may also be used to identify the combination of skills essential in recruiting for new roles. To address the challenges inherent in exploring the complex, heterogeneous, dynamic data that feeds into such applications, we investigate the use of an ontology to guide structuring of the information space, to allow individuals and institutions to interactively explore and interpret the dynamic skill demand landscape for their specific needs. As a test case we consider the relatively new and highly dynamic field of Data Science , where insightful, exploratory data analysis and knowledge discovery are critical. We employ context-driven and task-centred scenarios to explore our research questions and guide iterative design, development and formative evaluation of our ontology-driven, visual exploratory discovery and analysis approach, to measure where it adds value to users’ analytical activity. Our findings reinforce the potential in our approach, and point us to future paths to build on.
E MPIRICAL C HALLENGES TO THE E VIDENTIAL P ROBLEM OF E VIL

The problem of evil is broadly considered to be one of the greatest intellectual threats to traditional brands of theism.1 And William Rowe’s 1979 formulation of the problem in “The Problem of Evil and Some Varieties of Atheism” is the most cited formulation in the contemporary philosophical literature. In this paper, we explore how the tools and resources of experimental philosophy might be brought to bear on Rowe’s seminal formulation, arguing that our empirical findings raise significant questions regarding the ultimate success of Rowe’s argument. Such a result would be quite notable within philosophy of religion, since this is considered one of the most formidable arguments against theism. However, further testing is needed before any firm conclusions can be drawn. In section 1, we elucidate Rowe’s formulation of the problem of evil and the intuitions that seem to underwrite it. In section 2, we explore how the tools and resources of experimental philosophy might be brought to bear on Rowe’s formulation, outlining our hypotheses and our methods for testing them before showcasing our results. In section 3, we discuss the philosophical import of our results–arguing that our results, when taken together, pose an initial challenge to Rowe’s seminal argument.
GeoMorph: Geometric Deep Learning for Cortical Surface Registration

We present GeoMorph, a geometric deep learning image registration framework that takes two cortical surfaces on the spherical space and learns a smooth displacement ﬁeld that aligns the features on the moving surface to those on the target. GeoMorph starts with feature extraction: independently extracting low-dimensional feature representations for each input surface using graph convolutions. These learned features are then registered in a deep-discrete manner by learning the optimal displacement for a set of control points that optimizes the overlap between features across the two surfaces. To ensure a smooth deformation, we propose a regularization network that considers the input sphere structure based on a deep conditional random ﬁeld (CRF), implemented using a recurrent neural network (RNN). Results show that GeoMorph improves over existing deep learning methods by improving alignment whilst generating smoother and more biologically plausible deformations. Performance is competitive with classical frameworks, generalizing well even for subjects with atypical folding patterns.
TAGPRIME: A Unified Framework for Relational Structure Extraction

Many tasks in natural language processing require the extraction of relationship information for a given condition, such as event argument extraction, relation extraction, and task-oriented semantic parsing. Recent works usually propose sophisticated models for each of the tasks independently and pay less attention to the commonality of these tasks and to have a unified framework for all the tasks. In this work, we propose to take a unified view of all these tasks and introduce TAGPRIME to address relational structure extraction problems. TAGPRIME is a sequence tagging model that appends priming words about the information of the given condition (such as an event trigger) to the input text. With the self-attention mechanism in pre-trained language models, the priming words make the output contextualized representations contain more information about the given condition, and hence become more suitable for extracting specific relationships for the condition. Extensive experiments and analyses on three different tasks that cover ten datasets across five different languages demonstrate the generality and effectiveness of TAGPRIME.
Stability of perturbed geodesics in nD axisymmetric spacetimes

The effect of self-gravity of a disk matter is evaluated by the simplest modes of oscillation frequencies for perturbed circular geodesics. We plotted the radial profiles of free oscillations of an equatorial circular geodesic perturbed within the orbital plane or in the vertical direction. The calculation is carried out to geodesics of an axisymmetric n-dimensional spacetime. The profiles are computed by examples of disks embeded in five-dimensional or six-dimensional spacetime, where we studied the motion of free test particles for three axisymmetric cases: (i) the Newtonian limit of a general proposed 5D and 6D axisymmetric spacetime; (ii) a simple Randall–Sundrum (RS) 5D spacetime; (iii) general 5D and 6D RS spacetime. The equation of motion of such particles is derived and the stability study is computed for both horizontal and vertical directions, to see how extra dimensions could affect the system. In particular, we investigate a disk constructed from Miyamoto–Nagai and Chazy–Curzon with a cut parameter to generate a disk potential. Those solutions have a simple extension for extra dimensions in case (i), and by solving vacuum Einstein field equations for a kind of RS–Weyl metric in cases (ii) and (iii). We find that it is possible to compute a range of possible solutions where such perturbed geodesics are stable. Basically, the stable solutions appear, for the radial direction, in special cases when the system has 5D and in all cases when the system has 6D and, for the axial direction, in all cases when the system has both 5D or 6D.
Open Research Online Iron Mobility during Diagenesis at Vera Rubin ridge, Gale Crater, Mars

The Curiosity rover investigated a topographic structure known as Vera Rubin ridge, associated with a hematite signature in orbital spectra. There, Curiosity encountered mudstones interpreted as lacustrine deposits, conformably overlying the 300 m-thick underlying sedimentary rocks of the Murray formation at the base of Mount Sharp. While the presence of hematite (α-Fe 2 O 3 ) was confirmed in-situ by both Mastcam and ChemCam spectral observations and by the CheMin instrument, neither ChemCam nor APXS observed any significant increase in FeO T (total iron oxide) abundances compared to the rest of the Murray formation. Instead, Curiosity discovered dark-toned diagenetic features displaying anomalously high FeO T abundances, commonly observed in association with light-toned Ca-sulfate veins but also as crystal pseudomorphs in the host rock. These iron-rich diagenetic features are predominantly observed in “grey” outcrops on the upper part of the ridge, which lack the telltale ferric signature of other Vera Rubin ridge outcrops. Their composition is consistent with anhydrous Fe-oxide, as the enrichment in iron is not associated with enrichment in any other elements, nor with detections of volatiles. The lack of ferric absorption features in the ChemCam reflectance spectra and the hexagonal crystalline structure associated with dark-toned crystals points toward coarse “grey” hematite. In addition, the host rock adjacent to these features appears bleached and show low-FeO T content as well as depletion in Mn, indicating mobilization of these redox-sensitive elements during diagenesis. Thus, groundwater fluid circulations could account for the remobilization of iron and recrystallization as crystalline hematite during diagenesis on Vera Rubin ridge. of the sediments and up to their transformation into rocks. On the surface, the rover did not observe significant differences between the ridge and the terrains encountered before it, except for small, dark geologic features that formed during diagenesis. Their analysis by the ChemCam instrument revealed that these features are composed of hematite—the same iron-oxide mineral that was observed from orbit—and interestingly, that the iron required to form them was removed from the adjacent rocks by groundwaters. Thus, it appears that groundwaters played an important role in shaping Vera Rubin ridge, and thus partially obscure interpretations on the environmental conditions that existed on the surface of Mars at the time of sedimentation. this issue) showing that VRR is composed of the Pettegrove Point and Jura members, and that it is part of the Murray formation. Mastcam mosaics illustrating the lateral red and grey color variations in the bedrock on Vera Rubin ridge observed from a distance during the rover approach on the north flank of the ridge (mcam09282) and associated with topographic depressions, notably at the “Jura” (mcam10011), “Rhynie” (mcam10074) and “Highfield” localities.
Loyola Loyola Draft Genome Sequence of Lactobacillus jensenii Strain Draft Genome Sequence of Lactobacillus jensenii Strain UMB7766, Isolated from the Female Bladder UMB7766, Isolated from the Female Bladder

Lactobacillus jensenii is a beneﬁcial and prominent community member within both the vaginal and female urinary microbiota. As more genomes for L. jensenii strains are made publicly available, we gain more knowledge about this beneﬁcial community member. Here, we present the draft genome sequence of L. jensenii UMB7766, which was isolated from a urine specimen from a catheterized female patient with recurrent urinary tract infections. actobacillus jensenii is a dominant member of both the vaginal and female urinary microbiota of healthy individuals (1, 2). L. jensenii acts as a protective species within both niches, showing bactericidal effects against pathogens. Notably, in the urinary tract, L. jensenii has been shown to reduce the growth of uropathogenic Escherichia coli (3), the most common cause of infrequent urinary tract infections (4–6). Last year, our group released 11 L. jensenii genomes (7), raising the number of characterized L. jensenii strains from the bladder to 13. To add to this collection, we present ﬁndings for L. jensenii UMB7766, which was isolated from a urine specimen from a catheterized female patient with recurrent urinary tract infections. The sample collected from a patient at the Women’s Pelvic Medicine at University of California, San Diego, California, in August 2017 as of an review IRB
Visible-light photoredox-catalyzed selective carboxylation of C(sp 3 ) (cid:1) F bonds with CO 2

The dual role of CO 2 as both an electron carrier and an electrophile is demonstrated here. Based on this concept, we realize a selective carboxylation of C(sp 3 )–F bonds with CO 2 to construct various a -ﬂuorocarboxylic acids via visible-light photoredox catalysis. The ﬂuorinated substrates undergo single-electron transfer reduction by electron-rich CO 2 radical anions, which are generated from CO 2 via sequential hydride-transfer reduction and hydrogen-atom transfer processes. This methodology could be applied in the late-stage functionalization of complex molecules. SUMMARY It is because of its inertness, as a nontoxic and sustainable C1 source in the synthesis of valuable compounds. Here, we report a novel selective carboxylation of C(sp 3 ) (cid:1) F bonds with CO 2 via visible-light photoredox catalysis. A variety of mono-, di-, and triﬂuoroalkylarenes as well as a , a -diﬂuorocarboxylic esters and amides undergo such reactions to give important aryl acetic acids and a -ﬂuorocarboxylic acids, including several drugs and analogs, under mild conditions. Notably, mechanistic studies and DFT calculations demonstrate the dual role of CO 2 as an electron carrier and electrophile during this transformation. The ﬂuorinated substrates would undergo sin-gle-electron reduction by electron-rich CO 2 radical anions, which are generated in situ from CO 2 via sequential hydride-transfer reduction and hydrogen-atom-transfer processes. We anticipate our ﬁnding to be a starting point for more challenging CO 2 utilization with inert substrates, including lignin and other biomass. cleavage of allylic C(sp 3 )–F bond in triﬂuoromethyl group to yield gem -diﬂuoroalkene, 54,55 the selective ipso -functionalization of C(sp 3 )–F bonds in triﬂuoromethylarenes has been less investigated and all of these reports involved the photocatalytic SET reduction and following heterolytic cleavage of C(sp 3 )–F bonds to access aryldiﬂuoromethyl radicals, which then undergo the HAT process or alkylation with alkenes. 37–40
Scale-Equivariant UNet for Histopathology Image Segmentation

Digital histopathology slides are scanned and viewed under different magnifications and stored as images at different resolutions. Convolutional Neural Networks (CNNs) trained on such images at a given scale fail to generalise to those at different scales. This inability is often addressed by augmenting training data with re-scaled images, allowing a model with sufficient capacity to learn the requisite patterns. Alternatively, designing CNN filters to be scale-equivariant frees up model capacity to learn discriminative features. In this paper, we propose the Scale-Equivariant UNet (SEUNet) for image segmentation by building on scale-space theory. The SEUNet contains groups of filters that are linear combinations of Gaussian basis filters, whose scale parameters are trainable but constrained to span disjoint scales through the layers of the network. Extensive experiments on a nuclei segmentation dataset and a tissue type segmentation dataset demonstrate that our method outperforms other approaches, with much fewer trainable parameters.
Natural Active Ingredients for Poly (Lactic Acid)-Based Materials: State of the Art and Perspectives

This review describes the state of the art in the field of poly (lactic acid) (PLA)-based materials activated by natural compounds and extracts (active ingredients, AIs) from plant sources for food and biomedical applications. With a multidisciplinary approach, after a description of the synthesis and properties of PLA, special attention was paid to the chemical properties and unconventional extraction technologies of AIs used for PLA activation. Innovative techniques for the incorporation of AIs into PLA; characterization and the antioxidant and antimicrobial properties of the novel materials were discussed. In view of future perspectives, this study has evidenced that some aspects need to be further investigated from joint research between academia and industry, according to the green chemistry principles and circular economy strategy.
Analysis and Constructions of Subspace Codes

OF DISSERTATION Analysis and Constructions of Subspace Codes Random network coding is the most e cient way to send data across a network, but it is very susceptible to errors and erasures. In 2008, Kotter and Kschischang introduced subspace codes as an algebraic approach to error correcting in random network coding. Since this paper, there has been much work in constructing large subspace codes, as well as exploring the properties of such codes. This dissertation explores properties of one particular construction and introduces a new construction for subspace codes. We begin by exploring properties of irreducible cyclic orbit codes, which were introduced in 2011 by Rosenthal et al. As the name implies, irreducible cyclic orbit codes are the orbits of a group action of the general linear group on subspaces. By studying the stabilizers of this action, we formalize the notion of the stabilizer subfield of a subspace and utilize it to gain information about cardinality and distance of the code. Additionally, I define the linkage construction, which is recursive, and compare it to other subspace code constructions. In particular, we use the linkage construction to generalize some constructions of partial spreads. Finally, we address situations for which the linkage construction is e ciently decodable.
Peak-Hour Pricing Under Negative Externality: Impact of Customer Flexibility and Competitive Asymmetry

Several industries that provide services to customers (e.g., public utility and transportation) charge higher prices during peak hours to smooth demand. With technologies (e.g., electronic shelf labels) enabling retailers to change prices easily within each day, should supermarkets use peak-hour pricing? To examine this question formally, we introduce a stylized duopoly model in the presence of “negative externality,” where firms compete for congestion-averse customers. We characterize how customers endogenously segment themselves regarding when and where to shop, and then use the equilibrium outcomes to examine whether the firms should implement peak-hour pricing for varying types of customer flexibility and competitive asymmetry. Our analysis shows that, if customers are not flexible in their store choice, then both firms would always use peak-hour pricing. However, if store choice flexibility is present, then firms’ decisions depend on the competitive asymmetry as follows. If one firm has a clear competitive advantage (in terms of value or price) over the other firm, then the dominant firm will use peak-hour pricing, whereas the other firm will not. Otherwise, both firms will use peak-hour pricing if they engage in symmetric competition (in terms of similar value and price), or neither firm will use it if they engage in differentiated competition (high value versus low cost). Through our analysis of different extensions, we find that a firm’s ability to set its regular price would dampen the effect of peak-period pricing. Also, we obtain consistent results when there is heterogeneity in customer valuation and customer congestion aversion level.
Double-Acting Soft Actuator for Soft Robotic Hand: A Bellow Pumping and Contraction Approach

When compressing a soft bellow, the bellow will contract and pump out the fluid inside the bellow. Utilizing this property, we propose a novel actuation method called compressing bellow actuation (CBA), which can output fluidic power and tendon-driven force simultaneously. Based on the CBA method, a double-acting soft actuator (DASA) combining fluidic elastomer actuator (FEA) and tendon-driven metacarpophalangeal (MCP) joint is proposed for robotic finger design. The proposed DASA exhibits both compliance and adaptiveness of FEAs, and controllability and large output force of the tendon-driven methods. The fluid in the bellow can be either air or water or even integration of the two, thus constituting three different actuation modes. Mathematical modeling of the relationship between bellow compression displacement and DASA’s bending angle is developed. Furthermore, experimental characterizations of DASA’s bending angle and blocking force are conducted at different actuation modes. The double-acting method can availably promote the bending angle of an FEA by up to 155%, and the blocking force by up to 132% when the FEA is water-filled. A soft robotic hand with a forearm prototype based on the DASA fingers is fabricated for the demonstration of finger motion and gripping applications.