Miracle-dz/UniFAR-FTUs huggingface dataset:
Flood risk reduction and resilient city growth in sub-Saharan Africa: searching for coherence in Accra's urban planning

Urban resilience experts have highlighted that frequent extreme weather events are a result of rapid, unplanned development and climate change. To ensure coherent urban planning, effective land governance has been a priority since the introduction of the national urban policy in 2012. However, despite implementing this policy for over a decade, poor land governance continues to negatively impact city development, yet this subject has received limited academic attention. Our study focuses on Santa Maria, a community historically neglected by planning officials and currently facing unregulated urbanization and increasing flood risks. We used qualitative research methods, including key informant interviews and document reviews, to unpack land ownership and management complexities. These complexities have led to “planning by the commons,” the creation of green space deserts, and challenges related to residents' mobility and livelihood. Our study affirms that auto-constructed communities like Santa Maria reflect a form of tenacious urbanism that should be acknowledged and respected. Incorporating its logic into proposals for consolidation, informed by the opinions and desires of the residents themselves, can help integrate “planning by the commons” into the urban planning process of Accra. Rather than being viewed as a problem to be cured, this approach should be incorporated into the planning process, incorporating locally specific social functions and traditional structures to ensure equitable and just urban societies. The public sector must recognize that building on local capacity, skills, and expertise is essential in the quest for a resilient city. The experience from Santa Maria provides a great opportunity to nurture local development, fulfill the growing demand for solutions and services without biases, and provide an excellent opportunity for inclusive growth.
Pipeline Health Monitoring to Optimise Plant Efficiency

This chapter presents technological innovations that support asset integrity management—a crucial activity for optimising plant efficiency. In ageing thermal and geothermal power plants, critical assets such as steam piping are subject to high pressures and temperatures that accelerate damage mechanisms. Traditionally, the critical locations of these assets undergo routine inspection which is both costly and time consuming and affects the plant reliability and energy availability. There is an increasing trend in the application of non-destructive testing (NDT) and information technologies to in-service monitoring of these assets. The aim of this chapter is to provide a comprehensive overview of the state-of-the-art monitoring technologies for steamlines, with a focus on high temperature ultrasonic guided wave techniques. The enabling technologies, which include high temperature sensors, diagnostic data analysis algorithms and their monitoring performances, are reviewed. These technological advancements enable inspection without interruption of plant operations, and provide diagnosis and prognosis data for condition-based maintenance, increasing plant safety and its operational efficiency.
AIS Electronic Library (AISeL)

This study uses the concept of absorptive capacity to provide a framework for exploring benefit realization in the post-implementation phase of ERP systems. Success factors of ERP adoption such as: training, communication, process change, and integration extension are organized into two types of knowledge absorptive capacity: potential capacity and realization capacity. We propose that absorptive capacity is one of the key determinants of benefits realization from ERP implementation. Although the frequently mentioned factors training and communication are important activities for organizations to assimilate the knowledge of the system processes, these represent potential capacity that requires realization through refinement and execution of what has been absorbed. ERP adopting organizations wishing to continuously generate benefits need to both build potential absorptive capacity by investing in training and education, and leverage realized capacity through extension of integration of the system processes. Although planned for further testing, this study tries to explain post-adoptive behaviors and provides a source for further understanding of the management of post-ERP adoption.
The impact of subjective consumer knowledge on consumer behavioral loyalty through psychological involvement and perceived service quality: sports clubs

PurposeThe study advances an enhanced model encompassing psychological involvement, denoted as the psychological continuum model (PCM) and perceived customer service quality as intermediaries in the association between subjective customer knowledge (SCK) and behavioral loyalty. The purpose of this study is to assess the mediating role of psychological engagement and consumers' perceived service quality in the relationship between SCK and behavioral loyalty among members of nonprofit sports service organizations. Additionally, the study aims to examine the impact of membership duration on the relationship between consumer knowledge and behavioral loyalty.Design/methodology/approachThe study used a quantitative research design, and primary data were collected through a structured questionnaire from 527 members of nonprofit Chinese sports clubs who were selected using a simple random sampling technique. A 5-point Likert scale questionnaire was developed to measure all constructs in the intended research model. The suitability of the measurement model was analyzed by performing confirmatory factor analysis (CFA). Structural equation modeling (SEM) was used to analyze the data using AMOS-24.FindingsThe results of the overall direct effect indicate a significant influence of subjective knowledge on perceived service quality, perceived service quality significantly and positively influences psychological engagement; psychological engagement was found to be an important predictor of consumer behavioral loyalty.Originality/valueThe results offer information for nonprofit sports club (NPSC) managers who seek to increase the attractiveness and retention of their clubs' members by establishing the importance of subjective consumer knowledge.
Bending Tolerance of React&Wind Nb3Sn Conductors for Fusion Magnets

The react-and-wind technique for manufacturing of large Nb3Sn fusion magnets (RW) is very attractive because of the superior performance of the Nb3Sn with lower thermal strain compared to the wind-and-react technique. The procedure for magnet winding is also drastically simplified for the RW approach. The flat cable, made of a large number of Nb3Sn strands, is heat treated on a spool with constant radius. Then the cable is unspooled to assemble the conductor with stabilizer/steel jacket and wound on a spool to be shipped to the winding factory, where the conductor is unspooled and wound in the final geometry – either round shape for Central Solenoid or D-shape for Toroidal Field Coils. The bending strain must be controlled during the handling from heat treatment to the final magnet in order not to exceed the irreversible strain limit. For design purposes, it is assumed so far that a bending strain ±0.3% during handling is acceptable. In this work, the bending tolerance of a 63 kA RW fusion conductor is investigated by monitoring the performance in the SULTAN test facility after bending/straightening at decreasing radii till a degradation of the current sharing temperature performance, Tcs, is observed. The experimental assessment of the bending tolerance during handling is a major instrument for dimensioning of the cable thickness and heat treatment radius of the RW conductors for fusion.
Dual-band and Dual-sense Circularly Polarized Dielectric Resonator Antenna with Filtering Response

: A dual-band dual-sense (DBDS) circularly polarized (CP) filtering dielectric resonator antenna (FDRA) with a quasi-elliptic band-pass response is proposed in this paper. The proposed antenna consists of a rectangular dielectric resonator (DR) with a Z-shaped strip at the top, a ground plane with a rectangular slot, and a microstrip feedline etched with a section of the spur line. By using the microstrip coupled slot line structure to excite DR with a Z-shaped strip, different senses of circular polarization are achieved in the two bands. The results show that the lower and upper bands are independently controlled by the strip and the DR, respectively. In addition, three radiation nulls are generated at the passband’s edge by elaborately designing a half-wavelength open stub and etching the spur line. For demonstration, a prototype DBDS CPFDRA is fabricated and measured. The measurements illustrate that the antenna achieves a wide impedance bandwidth of 38.2%, as well as a dual axial ratio (AR) bandwidth of 2.2% for the left-hand circular polarization (LHCP) and 4% for the right-hand circular polarization (RHCP). The realized gain exhibits a decline of 25dB at the passband edge, indicating high selectivity.
Low-Complexity Single-Image Super-Resolution based on Nonnegative Neighbor Embedding

Single-image super-resolution (SR) is the problem of generating a single high resolution (HR) image, given one low resolution (LR) image as input. In this paper we propose a low-complexity and yet efficient algorithm that reconstruct the HR image in one pass (instead, e.g. of 7 passes for a magnification factor of 4 in [3]). The proposed algorithm falls into the family of example-based SR. Taking inspiration from machine learning, it aims at learning the mapping from the LR image(s) to the HR image by using a dictionary: the learning process is performed locally, by trying to infer the HR details through the use of small “examples”. For general SR purposes the examples used are patches (sub-windows of image); the dictionary is formed by pairs of LR and HR patches. In particular, our method adopts the Neighbor Embedding (NE) approach [1, 2], that assumes a local similarities between the LR and HR spaces. For each LR input patch xi t , we construct the corresponding HR output by following three steps.
Validity and Reliability of the Turkish Version of the Scale for Measuring Well-Being of Children in Lockdown

Background: Due to the COVID-19 pandemic, millions of people, including children, have been confined to their homes to maintain social distance. It would be beneficial to evaluate the well-being of children from a holistic perspective under the difficult conditions experienced during that period. Aim: This study was conducted to evaluate the validity and reliability of the Turkish version of the Well-Being of Children in Lockdown Scale (WCLS). Methods: This methodological, descriptive, correlational study was conducted with 406 parents with children aged 3–14 years between January 2022 and April 2022. Study data were collected with a sociodemographic data collection form and the WCLS using the online survey technique. Factor analysis, Cronbach’s alpha, and item-total score analysis were used in the evaluation of the data. Results: It was determined that the scale consisted of 22 items and six dimensions and that six dimensions explained 61.02% of the total variance. In both exploratory and confirmatory factor analysis (CFA), it was determined that all factor loads were > 0.30. In the CFA, all of the fit indices were found to be > 0.85, and the root mean square errors of approximate was < 0.080. Cronbach’s alpha coefficient was found as 0.89 for the total scale and > 0.70 for all of the dimensions. Conclusion: As a result of the analyses and evaluations conducted in this study, it was found that the WCLS was a valid and reliable measurement tool for the Turkish sample. The Scale for Measuring Well-being of Children in Lockdown can help evaluate the well-being of children during lockdown holistically, considering physical, mental, and social aspects, and facilitates the timely performance of interventions.
An intensionally fully-abstract sheaf model for (expanded version)

Following previous work on CCS, we propose a compositional model for the π -calculus in which processes are interpreted as sheaves on certain simple sites. Such sheaves are a concurrent form of innocent strategies, in the sense of Hyland-Ong/Nickau game semantics. We deﬁne an analogue of fair testing equivalence in the model and show that our interpretation is intensionally fully abstract for it. That is, the interpretation preserves and reﬂects fair testing equivalence; and furthermore, any innocent strategy is fair testing equivalent to the interpretation of some process. The central part of our work is the construction of our sites, relying on a combinatorial presentation of π -calculus traces in the spirit of string diagrams.
Reconstruction and Representation of 3d Objects with Radial Basis Functions

1. Briefly summarize the paper's contributions. Does it address a new problem? Does it present a new approach? Does it show new types of results?  [AS] This paper presents a fast approach to reconstruct smooth, manifold surfaces from point clouds and to repair incomplete meshes using polyharmonic Radial Basis Functions (RBFs), which were previously thought to be too slow to compute to be scalable.  [DS] The paper presents a way to use polyharmonic Radial Basis Functions (RBFs) to reconstruct smooth, manifold surfaces from point-cloud data. RBFs are fitted and evaluated using fast methods without which this was computationally infeasible to do on large point sets and complex surfaces with arbitrary topology. The fast method used for RBF evaluation is the Fast Multipole Method (FMM). The RBF center reduction method is used to fit the RBF function to a point set. This has smaller memory requirements and faster evaluation times without a loss of accuracy. The resulting implicit function can be easily manipulated through Boolean operations. It also allows for arbitrary accuracy. RBFs slo allow for mesh repair and surface extrapolation.  [FP] Surface is implicitly defined from a global function given by the sum of biharmonics at sample positions and a linear shift. The nature of the radial basis functions used by the authors, |í µí±¥−í µí±¥í µí±| , contrast with the type of functions used in previous approaches (e.g., Othake) : instead of being monotonic decreasing these are monotonic increasing functions. According to the authors, this selection of basis functions provides the smoothest interpolation. This characteristic makes the method robust to undersampling and useful for mesh repair.  [JD]  [LF]  [MK] The paper presents a new approach for surface reconstruction that fits RBF to the point, seeking the coefficients that evaluate to zero at the input samples. To avoid the trivial solution, the authors also add off-surface constraints, adding constraint points at a distance of d from the samples along the normal, and constraining the function to be at these points (depending on whether they are inside or outside the surface.) 2. What is the key insight of the paper? (in 1-2 sentences)  [AS] One key insight of this paper is the use of non-compactly supported basis functions, which are independent of sampling density, hence making their system scale independent and suitable for irregular, non-uniformly sampled data. However, such basis functions lead to systems …
A Pedestrian Approach to Ray Shooting: Shoot a Ray, Take a Walk

We propose a very simple ray-shooting algorithm, whose only data structure is a triangulation. The query algorithm, after locating the triangle containing the origin of the ray, walks along the ray, advancing from one triangle to a neighboring one until the polygon boundary is reached. The key result of the paper is a Steiner triangulation of a simple polygon with the property that a ray can intersect at most O(log n) triangles before reaching the polygon boundary. We are able to compute such a triangulation in linear sequential time, or in O(log n) parallel time using O(n/log n) processors. This gives a simple, yet optimal, ray-shooting algorithm for a simple polygon. Using a well-known technique, we can extend our triangulation procedure to a multiconnected polygon with k components and n vertices, so that a ray intersects at most O(? k log n) triangles.
Analysis of interrelations between business models and knowledge management strategies in consulting firms

Knowledge is an important matter for consulting firms − as a resource, as a product or service, and as a trigger for internal value creation processes. Therefore, a strategy for management and utilisation of knowledge in its different state is needed. It is sensible to assume, that this strategy is strongly influenced by a respective consulting firm’s business model. This paper provides an analysis of the interrelation between business model and Knowledge Management strategy. Four determinants are defined to allow a detailed description of different Knowledge Management strategies. Methods and techniques of Knowledge Management are subsumed under these determinants. The use of these methods determine, whether a Knowledge Management strategy is dominated by central or de-central elements. This article describes different types of business models and derives recommendations for corresponding Knowledge Management strategies. Case studies of four international consulting firms with different business models and different Knowledge Management strategies are used to validate these recommendations.
University of Pennsylvania Center for Sensor Technologies SUNFEST

A difficult problem in robotics is enabling a robot to navigate autonomously through a previously unexplored indoor environment. Part of this difficulty stems from the stringent requirements on the mobility and the power of a robotic platform. It is necessary that the platform has sufficient maneuverability to operate in a cluttered area and that it has sufficient power to carry the necessary sensors to operate autonomously. The Segway Robotic Mobility Platform (RMP) combines unusually high mobility with the power to carry a sufficient number of sensors to navigate in an indoor environment. This paper discusses how, using a laser range finder, a stereo camera, and the Segway’s on-board encoders, the Segway RMP can be enabled to perform tasks of autonomous navigation while navigating through an area with obstacles.
On The Power of Membership Queries in Agnostic Learning

We study the properties of the agnostic learning framework of Haussler [Hau92] and Kearns, Schapire and Sellie [KSS94]. In particular, we address the question: is there any situation in which membership queries are useful in agnostic learning? Our results show that the answer is negative for distribution-independent agnostic learning and positive for agnostic learning with respect to a specific marginal distribution. Namely, we give a simple proof that any concept class learnable agnostically by a distribution-independent algorithm with access to membership queries is also learnable agnostically without membership queries. This resolves an open problem posed by Kearns et al. [KSS94]. For agnostic learning with respect to the uniform distribution over {0, 1}n we show a concept class that is learnable with membership queries but computationally hard to learn from random examples alone (assuming that one-way functions exist).
Identiﬁcation of Differentially Expressed Gene Modules in Heterogeneous Diseases

Motivation: Identiﬁcation of differentially expressed genes is necessary for unraveling disease pathogenesis. This task is complicated by the fact that many diseases are heterogeneous at the molecular level and samples representing distinct disease subtypes may demonstrate different patterns of dysregulation. Biclustering methods are capable of identifying genes that follow a similar expression pattern only in a subset of samples and hence can consider disease heterogeneity. However, identifying biologically signiﬁcant and reproducible sets of genes and samples remains challenging for the existing tools. Many recent studies have shown that the integration of gene expression and protein interaction data improves the robustness of prediction and classiﬁcation and advances biomarker discovery. Results: Here we present DESMOND, a new method for identiﬁcation of Differentially ExpreSsed gene MOdules iN Diseases. DESMOND performs network-constrained biclustering on gene expression data and identiﬁes gene modules — connected sets of genes up-or down-regulated in subsets of samples. We applied DESMOND on expression proﬁles of samples from two large breast cancer cohorts and have shown that the capability of DESMOND to incorporate protein interactions allows identifying the biologically meaningful gene and sample subsets and improves the reproducibility of the results.
Using machine learning to track dogs’ exploratory behavior in presence and absence of their caregiver

The dog-human relationship exhibits characteristics of human attachment bonds. In particular, dogs have been found to show a secure base effect, i.e., they explored and played more in the presence of their owner as compared to a stranger. In the current study, we presented the dogs with a procedure in which the dogs could move freely in a room equipped with trial-unique objects. We manipulated across trials whether the owner and/or a stranger was present in the room or not. Crucially, we applied and validated machine learning to track the dogs’ behavior throughout the trials. The three-dimensional (3D) tracking of the dogs’ bodies allowed us to extract behavioral responses with high spatial and temporal resolution without relying on subjective human ratings. The results show that both the owner and stranger significantly increased the dogs’ exploration; the dogs also spend more time in the proximity of the owner and stranger location when they were present. Even though the presence of owner and stranger had a significant effect on the dogs’ behavior, the effect of the owner was more pronounced. We conclude that machine-driven 3D tracking provides a reliable access for detailed behavioral analyses of dogs’ exploration and attachment-related behaviors.
Equilibrium Technology Diffusion , Trade , and Growth

——————————————————————————————————— We study how opening to trade affects economic growth in a model where heterogeneous firms can choose to adopt a new technology already in use by other firms. We characterize the growth rate using summary statistics of the profit distribution—the ratio of profits between the average and marginal adopting firm. Opening to trade increases the spread in profits through increased export opportunities and foreign competition, induces more rapid technology adoption, and generates faster growth. Quantitatively, opening to trade yields large increases in growth, but welfare effects are muted due to loss of variety and reallocation of labor away from production. —————————————————————————————————————————— JEL Classification: A1, E1, O4, F00, F43