Miracle-dz/UniFAR-FTUs huggingface dataset:
Sampling at unknown locations: Uniqueness under constraints

Traditional sampling results assume that the sample locations are known. Motivated by simultaneous localization and mapping (SLAM) and structure from motion (SfM), we investigate sampling at unknown locations. We show that, without further constraints, the problem is often hopeless. More precisely, we show that, for polynomial and bandlimited signals, it is possible to find two signals, arbitrarily far from each other, that fit the measurements. To overcome this, we propose to add constraints to the sample positions. As we show, this leads to a uniform sampling of a composite of functions. Our formulation retains the key aspects of the SLAM and SfM problems, whilst providing uniqueness, in many cases. We demonstrate this by studying two simple examples of constrained sampling at unknown locations. In the first, we consider sampling a periodic bandlimited signal composite with an unknown linear function. We derive the sampling requirements for uniqueness and present an algorithm that recovers both the bandlimited signal and the linear warping. Furthermore, we prove that, when the requirements for uniqueness are not met, the cases of multiple solutions have measure zero. For our second example, we consider polynomials sampled such that the sampling positions are constrained by a rational function. We prove that, if a specific sampling requirement is met, uniqueness is achieved. In addition, we present an alternate minimization scheme for solving the resulting nonconvex optimization problem. Finally, simulation results are provided to support our theoretical analysis. Keywords—Sampling, sampling at unknown locations, SLAMpling.
Interdependent Values without Single-Crossing

We consider a setting where an auctioneer sells a single item to n potential agents with interdependent values. That is, each agent has her own private signal, and the valuation of each agent is a known function of all n private signals. This captures settings such as valuations for oil drilling rights, broadcast rights, pieces of art, and many more. In the interdependent value setting, all previous work has assumed a so-called single-crossing condition. Single-crossing means that the impact of a private signal, si , on the valuation of agent i , is greater than the impact of si on the valuation of any other agent. It is known that without the single-crossing condition, an efficient outcome cannot be obtained. We ask what approximation to the optimal social welfare can be obtained when valuations do not exhibit single-crossing. We show that, in general, without the single-crossing condition, one cannot hope to approximate the optimal social welfare any better than assigning the item to a random bidder. Consequently, we consider a relaxed version of single-crossing, c-single-crossing, with some parameter c≥1 , which means that the impact of si on the valuation of agent i is at least 1/ c times the impact of si on the valuation of any other agent ( c =1 is single-crossing). Using this relaxed notion, we obtain a host of positive results. These include a prior-free universally truthful 2√ nc3/2 -approximation to welfare, and a prior-free deterministic ( n -1) c -approximation to welfare. Under appropriate concavity conditions, we improve this to a prior-free universally truthful 2 c -approximation to welfare as well as a universally truthful O(c2)-approximation to the optimal revenue.
SketchStudio: Experience Prototyping with 2.5-Dimensional Animated Design Scenarios

Recent subject matters of design have become complex systems involving various elements and multiple users' interactions in large-scale spaces. In addition, visualizing these complex design subjects without preparing heavy resources in the early design phases is challenging. In this paper, we present SketchStudio, a prototyping tool for generating, sharing, and reviewing an animated design scenario involving complex design subjects. The tool allows designers to define the user experience by simply creating a node graph of the user's journey over time and space. SketchStudio instantly generates unique 2.5D animated design scenarios by blending 2D sketches and 3D characters. In addition, the tool supports the virtual reality mode for immersive views of the created scenario prototype. We also report on the result of a user study with nine potential users in the design practice and education fields. Based on our tool-developing experiences as well as on the study results, we discuss possible applicable areas and points for further improvement.
Role of Fibroblast Growth Factor-23 in Innate Immune Responses

Fibroblast growth factor-23 (FGF-23) is a bone-derived hormone that activates FGFR/α-Klotho binary complexes in the kidney renal tubules to regulate phosphate reabsorption and vitamin D metabolism. The objective of this review is to discuss the emerging data that show that FGF-23 has functions beyond regulation of mineral metabolism, including roles in innate immune and hemodynamic responses. Excess FGF-23 is associated with inflammation and adverse infectious outcomes, as well as increased morbidity and mortality, particularly in patients with chronic kidney disease. Enhancer elements in the FGF-23 promoter have been identified that mediate the effects of inflammatory cytokines to stimulate FGF-23 gene transcription in bone. In addition, inflammation induces ectopic expression of FGF-23 and α-Klotho in macrophages that do not normally express FGF-23 or its binary receptor complexes. These observations suggest that FGF-23 may play an important role in regulating innate immunity through multiple potential mechanisms. Circulating FGF-23 acts as a counter-regulatory hormone to suppress 1,25D production in the proximal tubule of the kidney. Since vitamin D deficiency may predispose infectious and cardiovascular diseases, FGF-23 effects on innate immune responses may be due to suppression of 1,25D production. Alternatively, systemic and locally produced FGF-23 may modulate immune functions through direct interactions with myeloid cells, including macrophages and polymorphonuclear leukocytes to impair immune cell functions. Short-acting small molecules that reversibly inhibit FGF-23 offer the potential to block pro-inflammatory and cardiotoxic effects of FGF-23 with less side effects compared with FGF-23 blocking antibodies that have the potential to cause hyperphosphatemia and soft tissue calcifications in animal models. In conclusion, there are several mechanisms by which FGF-23 impacts the innate immune system and further investigation is critical for the development of therapies to treat diseases associated with elevated FGF-23.
Tolvaptan: Clinical Evidence for Slowing the Progression of Autosomal Dominant Polycystic Kidney Disease

G TN D -1 700 28 Europea dei Farmaci (EMA) ha approvato l’impiego di tolvaptan (JINARC®) per il trattamento di ADPKD. Sul sito ufficiale EMA (http://www.ema.europa.eu/ema/index.jsp? curl=pages/ medicines/human/medicines/002788/human_med_001857. jsp) è riportata l’indicazione terapeutica di registrazione della molecola: rallentamento della progressione di sviluppo delle cisti e dell’insufficienza renale di ADPKD negli adulti con stadio di insufficienza renale cronica (stadio CKD) da 1 a 3 all’inizio del trattamento con evidenza di malattia rapidamente progressiva. In questo breve editoriale cercheremo di riassumere le principali evidenze cliniche ricavate dagli studi clinici disponibili per orientare il nefrologo e l’internista circa le potenzialità e i limiti del primo trattamento farmacologico attivo nei confronti di ADPKD.
Religious Involvement and Marijuana Use for Medical and Recreational Purposes

In this article, we use data from the 2016 National Survey on Drug Use and Health (NSDUH) to examine the association between religious involvement and marijuana use for medical and recreational purposes in U.S. adults (N = 41,517). We also consider whether the association between religious involvement and marijuana use varies according to personal health status. Our results show that adults who attend religious services more frequently and hold more salient religious beliefs tend to exhibit lower rates of medical and recreational marijuana use. We also find that these “protective effects” are less pronounced for adults in poor health. Although our findings confirm previous studies of recreational marijuana use, we are the first to examine the association between religious involvement and medical marijuana use. Our moderation analyses suggest that the morality and social control functions of religious involvement may be offset under the conditions of poor health.
A worldwide model for boundaries of urban settlements

The shape of urban settlements plays a fundamental role in their sustainable planning. Properly defining the boundaries of cities is challenging and remains an open problem in the science of cities. Here, we propose a worldwide model to define urban settlements beyond their administrative boundaries through a bottom-up approach that takes into account geographical biases intrinsically associated with most societies around the world, and reflected in their different regional growing dynamics. The generality of the model allows one to study the scaling laws of cities at all geographical levels: countries, continents and the entire world. Our definition of cities is robust and holds to one of the most famous results in social sciences: Zipf’s law. According to our results, the largest cities in the world are not in line with what was recently reported by the United Nations. For example, we find that the largest city in the world is an agglomeration of several small settlements close to each other, connecting three large settlements: Alexandria, Cairo and Luxor. Our definition of cities opens the doors to the study of the economy of cities in a systematic way independently of arbitrary definitions that employ administrative boundaries.
Is successional research nearing its climax? New approaches for understanding dynamic communities

Summary Succession has been a focus of extensive ecological study for well over a century. Despite this sustained interest, succession remains a central theme in ecological research and is positioned to continue that prominence in this era of expanding human impacts. Community ecology is currently experiencing a profound conceptual expansion, providing many new insights into succession. Here we present an existing conceptual framework of successional drivers that includes variation in site conditions, species availability and species performance, and expand it to include both evolutionary and geographic sources of variation. This framework is useful because it specifies relationships among individual drivers and is causally complete. While we generally think about succession as a within-site process, the inclusion of phylogenetic and geographic processes allows integration across broader scales. We use the conceptual framework to highlight several opportunities for successional research that have developed within community ecology, but have not been fully integrated into succession work. These ideas represent not only individual drivers of succession, but also potential synergistic processes operating through interaction with other drivers. The complexity of drivers in succession strongly argues for the need to move away from single factor studies towards combinatorial studies that incorporate multiple drivers. Utilizing a trait-based approach should allow researchers to address successional drivers at multiple ecological scales and lead to new insights that integrate ecological systems. Our ability to do this will depend on the availability of equivalent data across multiple systems, suggesting the need for more standardization in successional studies. Addressing the research opportunities highlighted here will not only produce insights into successional systems, but also expand our understanding of fundamental questions in community ecology as a whole. Of particular importance is the ability to address broader scale questions that go beyond the idiosyncrasies of individual sites and systems. Understanding the dynamics of successional systems will remain critical to understanding, managing and predicting anthropogenic impacts on natural systems.
Extracting and Using Medical Expert Knowledge to Advance in Video Processing for Gynecologic Endoscopy

Modern day endoscopic technology enables medical staff to conveniently document surgeries via recording raw treatment footage, which can be utilized for planning further proceedings, future case revisitations or even educational purposes. However, the prospect of manually perusing recorded media files constitutes a tedious additional workload on physicians' already packed timetables and therefore ultimately represents a burden rather than a benefit. The aim of this PhD project is to improve upon this situation by closely collaborating with medical experts in order to devise datasets and systems to facilitate semi-automatic post-surgical media processing.
Pressure or Movement? Usability of Multi-Functional Foot-Based Interfaces

Despite considerable prior work exploring foot-based interaction techniques, direct comparisons of the performance of these approaches have been lacking. Here, we compare the performance of the two most common approaches found in previous studies: rocking (applying pressure to different parts of the foot) versus rotating and sliding, considering the use case of a hands-free interface intended for seated musicians. Participants performed a number of representative operations, such as setting the tempo of a metronome, using the two strategies. Results indicate superiority of the rotating and sliding approach, both in completion time and responses to NASA TLX questionnaires, although rocking was preferred by some participants due to its ergonomics and subtle movements required for parameter-controlling tasks. Beyond the comparison itself, the decisions we faced related to menu design and feedback for our use case may offer helpful insight for the design of future foot-based interfaces.
Biodegradability standards for carrier bags and plastic films in aquatic environments: a critical review

Plastic litter is encountered in aquatic ecosystems across the globe, including polar environments and the deep sea. To mitigate the adverse societal and ecological impacts of this waste, there has been debate on whether ‘biodegradable' materials should be granted exemptions from plastic bag bans and levies. However, great care must be exercised when attempting to define this term, due to the broad and complex range of physical and chemical conditions encountered within natural ecosystems. Here, we review existing international industry standards and regional test methods for evaluating the biodegradability of plastics within aquatic environments (wastewater, unmanaged freshwater and marine habitats). We argue that current standards and test methods are insufficient in their ability to realistically predict the biodegradability of carrier bags in these environments, due to several shortcomings in experimental procedures and a paucity of information in the scientific literature. Moreover, existing biodegradability standards and test methods for aquatic environments do not involve toxicity testing or account for the potentially adverse ecological impacts of carrier bags, plastic additives, polymer degradation products or small (microscopic) plastic particles that can arise via fragmentation. Successfully addressing these knowledge gaps is a key requirement for developing new biodegradability standard(s) for lightweight carrier bags.
Text/Non-Text Separation from Handwritten Document Images Using LBP Based Features: An Empirical Study

Isolating non-text components from the text components present in handwritten document images is an important but less explored research area. Addressing this issue, in this paper, we have presented an empirical study on the applicability of various Local Binary Pattern (LBP) based texture features for this problem. This paper also proposes a minor modification in one of the variants of the LBP operator to achieve better performance in the text/non-text classification problem. The feature descriptors are then evaluated on a database, made up of images from 104 handwritten laboratory copies and class notes of various engineering and science branches, using five well-known classifiers. Classification results reflect the effectiveness of LBP-based feature descriptors in text/non-text separation.
A Logical Framework for Verifying Privacy Breaches of Social Networks

We present a novel approach to deal with transitivity permission-delegation threats that arise in social networks when content is granted permissions by third-party users thereby breaking the privacy policy of the content owner. These types of privacy breaches are often unintentional in social networks like Facebook, and hence, (more) in-place mechanisms are needed to make social network users aware of the consequences of changing their privacy policies. Our approach is unique in its use of formal methods tools and techniques. It builds on a predicate logic definition for social networking that caters for common aspects of existing social networks such as users, social network content, friendship, permissions over content, and content transmission. Our approach is implemented in Yices. For the predicate logic model, we formulate a security policy for the verification of the permission flow of content owned by social network users and demonstrate how this security policy can be verified.
Robust resource allocation for heterogeneous wireless network: a worst-case optimisation

With the development of fifth generation wireless communication technology, how to improve system capacity and spectrum efficiency is a crucial problem in resource sharing of heterogeneous networks (HetNets). Most of existing resource allocation (RA) schemes in HetNets focus on perfect channel state information, however, exact channel information is difficult to obtain under link delay and stochastic channel condition. In order to resolve the RA issues under channel uncertainties, a robust RA algorithm is proposed to maximise the sum data rate of microcell users where the users are subjected to the individual transmission power constraint and the cross-tier interference constraint of macrocell users. The multiuser RA problem in HetNets is formulated under the consideration of bounded channel gain uncertainties where both the cross-tier channel and intra-tier channel are simultaneously considered. The non-linear optimisation problem is converted into a geometric programming problem that is solved by using Lagrange dual methods in a distributed way. Simulation results show that the proposed algorithm can well restrain the effect of channel uncertainty and achieve a good robustness.
Noise-based control of social dynamics

Designing practical control strategies for opinion dynamics of social size has never been an easy job. It requires the control law cannot 1) be implemented on all individuals of the society; 2) rely on the specific opinion values of the social system. Thanks to the emerging studies on noise-induced consensus of opinion dynamics, the noise-based intervention strategy seems meet the above two requirements and displays its potential in social control, yet its general theory still lacks. In this paper, we establish a theoretical analysis on the noise-based control strategy where only part of agents are affected by randomly generated noises. That is, no matter how many agents (even only one) receive noise, the system will a.s. achieve quasi-consensus in finite time, and the critical noise strength is obtained. The result provides solid ground for implementing social control using noise.
Modular Continuum Manipulator: Analysis and Characterization of Its Basic Module

We present the basic module of a modular continuum arm (soft compliant manipulator for broad applications (SIMBA)). SIMBA is a robotic arm with a hybrid structure, namely a combination of rigid and soft components, which makes the arm highly versatile, dexterous, and robust. These key features are due to the design of its basic module, which is characterized by a three-dimensional workspace with a constant radius around its rotation axis, large and highly repeatable bending, complete rotation, and passive stiffness. We present an extensive analysis and characterization of the basic module of the SIMBA arm in terms of design, fabrication, kinematic model, stiffness, and bending behavior. All the theoretical models presented were validated with empirical results. Our findings show a positional typical error of less than ≈6% in module diameter (highly repeatable) with a passive stiffness of 0.8 N/mm (≈1 kg load). Our aim is to demonstrate that this kind of robotic element can be exploited as an elementary module of a more complex structure, which can be used in any application requiring high directional stiffness but without the need for an active stiffness mechanism, as is the case in daily activities (e.g., door opening, water pouring, obstacle avoidance, and manipulation tasks).
Object‐oriented modeling approach of universal education software

Since learning process could be very challenging task for scholars in this article an attempt to analyze and model a universal education software (UES) was made. The software was modeled from beginning of the life cycle by object‐orientated modeling approach. In order to visually represent any research problem unified modeling language is the most appropriate and efficient tool. In this paper UES was modeled by unified modeling language diagrams which could lead to better development and understanding of the behavior and structure of the software. Modeling by unified modeling language is a new way of thinking about systems and the development process which involved object modeling. The main concept of the object modeling is the object identification within the system environment, and the relationships and interactions between the objects.
Sensing or Watching?: Balancing Utility and Privacy in Sensing Systems via Collection and Enforcement Mechanisms

Devices with embedded sensors are permeating the computing landscape, allowing the collection and analysis of rich data about individuals, smart spaces, and their interactions. This class of devices enables a useful array of home automation and connected workplace functionality to individuals within instrumented spaces. Unfortunately, the increasing pervasiveness of sensors can lead to perceptions of privacy loss by their occupants. Given that many instrumented spaces exist as platforms outside of a user's control---e.g., IoT sensors in the home that rely on cloud infrastructure or connected workplaces managed by one's employer---enforcing access controls via a trusted reference monitor may do little to assuage individuals' privacy concerns. This calls for novel enforcement mechanisms for controlling access to sensed data. In this paper, we investigate the interplay between sensor fidelity and individual comfort, with the goal of understanding the design space for effective, yet palatable, sensors for the workplace. In the context of a common space contextualization task, we survey and interview individuals about their comfort with three common sensing modalities: video, audio, and passive infrared. This allows us to explore the extent to which discomfort with sensor platforms is a function of detected states or sensed data. Our findings uncover interesting interplays between content, context, fidelity, history, and privacy. This, in turn, leads to design recommendations regarding how to increase comfort with sensing technologies by revisiting the mechanisms by which user preferences and policies are enforced in situations where the infrastructure itself is not trusted.