Miracle-dz/UniFAR-FTUs huggingface dataset:
Diagnosing severity levels of Autism Spectrum Disorder with Machine Learning

Autism Spectrum Disorders (ASDs) are neurodevelopmental disorders which inhibits linguistic, cognitive, communication and social skills of affected individuals. Currently, ASD is diagnosed by means of time-consuming and expensive screening tests. Hence, Machine Learning (ML) techniques have been applied to construct predictive models able to diagnose autism at early stages. However, the binary setting (ASD vs not-ASD) and the not-exciting performance reached by such models highlight the need for further de-identiﬁed datasets and interdisciplinary work linking computer scientists and Subject Domain Experts (SDEs). In this work, we propose a novel dataset in which labels refer to the severity level of autism as required by the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) standard reference. Then we analyze the quality of resulting ML models (i.e. Random Forest, XGBoost, Neural Network) based not only on their performance metrics (i.e. precision, recall, F1) but also on the most important features they consider for classiﬁcation and their similarity with the ones suggested by the SDE.
Intersection Coordination with Priority-Based Search for Autonomous Vehicles

The development of connected and autonomous vehicles opens an opportunity to manage intersections without signals. One promising approach is to use a central autonomous intersection manager to optimize the movement of the vehicles in the intersection. Existing work uses Mixed Integer Linear Programming (MILP) to find optimal solutions for this problem but is time-consuming and cannot be applied in real-time. On the other hand, the coordination of the vehicles is essentially a Multi-Agent Path Finding (MAPF) problem, for which dozens of efficient algorithms have been proposed in recent years. Inspired by these MAPF algorithms, we propose a three-level algorithm called PSL to solve the intersection coordination problem. Theoretically, PSL is complete and polynomial-time in the number of vehicles. Empirically, PSL runs significantly faster with only a slight compromise in the solution quality than the optimal MILP method. It also generates significantly better solutions with a slightly larger runtime than the traditional First-Come-First-Served strategy.
A PDE Approach to the Problems of Optimality of Expectations

Let (X, Z) be a bivariate random vector. A predictor of X based on Z is just a Borel function g(Z). The problem of "least squares prediction" of X given the observation Z is to find the global minimum point of the functional E[(X − g(Z))2] with respect to all random variables g(Z), where g is a Borel function. It is well known that the solution of this problem is the conditional expectation E(X|Z). We also know that, if for a nonnegative smooth function F: R×R → R, arg ming(Z)E[F(X, g(Z))] = E[X|Z], for all X and Z, then F(x, y) is a Bregmann loss function. It is also of interest, for a fixed ϕ to find F (x, y), satisfying, arg ming(Z)E[F(X, g(Z))] = ϕ(E[X|Z]), for all X and Z. In more general setting, a stronger problem is to find F (x, y) satisfying arg miny∈RE[F (X, y)] = ϕ(E[X]), ∀X. We study this problem and develop a partial differential equation (PDE) approach to solution of these problems.
Lightweight Collaborative Inferencing for Real-Time Intrusion Detection in IoT Networks

The security in Internet-of-Things (IoT) networks becomes increasingly important with the growing popularity of IoT devices and their wide applications (e.g., critical infrastructure monitoring). However, traditional intrusion detection systems (IDS) are not suitable for IoT networks due to their large resource requirements. Moreover, IoT networks tend to have multiple access points for IoT devices and thus benefit from a distributed framework to enable collaborative prevention of potential attacks. To this end, we propose a lightweight collaborative distributed network IDS (NIDS) based on widely-utilized machine learning (ML) models, which are trained through a federated learning framework with two known datasets. We evaluate the distributed NIDS using the trained ML models on an IoT network testbed under seven types of attacks in comparison with Snort (a state-of-the-art IDS) and a centralized implementation of our proposed NIDS. An offline benchmark is also designed to measure the system’s performance with regard to resource usage and response time. Our results show that the proposed distributed NIDS outperforms Snort in identifying malicious traffic and achieves a much lower false positive rate compared to the centralized version in real-time for all seven types of network attacks tested.
Projection of population structure in China using least squares support vector machine in conjunction with a Leslie matrix model

China is a populous country that is facing serious aging problems due to the singleâ€ child birth policy. Debate is ongoing whether the liberalization of the singleâ€ child policy to a twoâ€ child policy can mitigate China's aging problems without unacceptably increasing the population. The purpose of this paper is to apply machine learning theory to the demographic field and project China's population structure under different fertility policies. The population data employed derive from the fifth and sixth national census records obtained in 2000 and 2010 in addition to the annals published by the China National Bureau of Statistics. Firstly, the sex ratio at birth is estimated according to the total fertility rate based on least squares regression of time series data. Secondly, the ageâ€ specific fertility rates and ageâ€ specific male/female mortality rates are projected by a least squares support vector machine (LSâ€ SVM) model, which then serve as the input to a Leslie matrix model. Finally, the male/female ageâ€ specific population data projected by the Leslie matrix in a given year serve as the input parameters of the Leslie matrix for the following year, and the process is iterated in this manner until reaching the target year. The experimental results reveal that the proposed LSâ€ SVMâ€ Leslie model improves the projection accuracy relative to the conventional Leslie matrix model in terms of the percentage error and mean algebraic percentage error. The results indicate that the total fertility ratio should be controlled to around 2.0 to balance concerns associated with a large population with concerns associated with an aging population. Therefore, the twoâ€ child birth policy should be fully instituted in China. However, the fertility desire of women tends to be low due to the high cost of living and the pressure associated with employment, particularly in the metropolitan areas. Thus additional policies should be implemented to encourage fertility.
Eﬀicient spectral volumetric rendering based on astrophysical assumptions

Physically accurate spectral rendering generally brings further computational complexity to RGB rendering pipelines which precludes real-time rates. In this report, we show that by building on several physical a-prioris for the spectral phenomena in standard astronomical scenes, we achieve to obtain a model greatly reducing the complexity of the spectral aspect for volumetric rendering - by up to 83 factor in our examples. By projecting the total local contribution on a small optimal basis, thus providing scalability for the method, our rendering scheme then makes it possible to render a volumetric scene with any number and spectra of lights in real-time and no significant visual discrepancies
Evaluating Machine Learning Models for Internet Network Security with Data Slices

By using public data about the structure of the internet, practitioners can identify what assets organizations own on the internet, many of which are vulnerable to cybersecurity attacks. With current knowledge of what servers and assets are exposed to the internet, organizations are able to remediate vulnerabilities before they are exploited. As part of managing an AI/ML system for this "internet asset attribution" task, we make extensive formal use of "data slices", subsets of data that share particular properties. Data slices make managing models and datasets more repeatable and sustainable. Data slice evaluation lets us systematically manage regressions, user trust, experiment evaluation, and data space characterization.
Turbulence Measurements from Five-Beam Acoustic Doppler Current Profilers

AbstractTwo new five-beam acoustic Doppler current profilers—the Nortek Signature1000 AD2CP and the Teledyne RDI Sentinel V50—are demonstrated to measure turbulence at two energetic tidal channels within Puget Sound, Washington. The quality of the raw data is tested by analyzing the turbulent kinetic energy frequency spectra, the turbulence spatial structure function, the shear in the profiles, and the covariance Reynolds stresses. The five-beam configuration allows for a direct estimation of the Reynolds stresses from along-beam velocity fluctuations. The Nortek’s low Doppler noise and high sampling frequency allow for the observation of the turbulent inertial subrange in both the frequency spectra and the turbulence structure function. The turbulence parameters obtained from the five-beam acoustic Doppler current profilers are validated with turbulence data from simultaneous measurements with acoustic Doppler velocimeters. These combined results are then used to assess a turbulent kinetic energy budget .
Design and Construction of a Low-Cost Diamond Turning Lathe and Workflow for Ultra-Precision Manufacturing

Diamond turning lathes (DTL’s) are the state of the art in ultraprecision manufacturing and enable modern high precision mass production. They use monocrystalline diamond cutting tools in conjunction with nanometer precise kinematic frames to machine parts to sub-micron accuracies with optical quality surface finishes, seen in Figure 1. Limitations to the state of the art include cost and inefficient workholding techniques like vacuum chucks. A low-cost diamond turning lathe was developed concurrently with a novel kinematic coupling based workholding system to address these limitations and bring ultra-precision manufacturing capability to Auburn University. The goals for this project included less than 1 μm and 10 nm Ra (roughness average) form and surface roughness tolerances, respectively.
Small Data in NLU: Proposals towards a Data-Centric Approach

Domain-speciﬁc voice assistants often suffer from the problem of data scarcity. Publicly available, annotated datasets are in short supply and rarely ﬁt the domain and the language required by a speciﬁc use case. Insufﬁcient attention to data quality can generally be problematic when it comes to training and evaluation. The Computational Linguistics (CL) community has gained expertise and developed best practices for high-quality data annotation and collection as well as for for qualitative data analysis. However, the recent model-centric focus in AI and ML has not created ideal conditions for a fruitful collaboration with CL and the more data-centric ﬁelds of NLP to tackle data quality issues. We showcase principles and methods from CL / NLP research, which can potentially guide the development of data-centric NLU for domain-speciﬁc voice assistants - but have been typically overlooked by common practices in ML / AI. Those principles can potentially be of help to shape data-centric practices also for other domains. We argue that paying more attention to data quality and domain speciﬁcity can go a long way in improving the NLU components of today’s voice assistants.
On a certain diophantine equation

The unit of currency on Mars is the zonk, which consists of a whole number of zinks. An enlightened, though somewhat green, government recently decided to revamp the taxation system, which at the time was manifestly unfair to male Martians as it required them to pay less tax than females. (Martians are very unselfish and feel aggrieved if they are better off than other Martians.) Previously, only females had had to pay ‘Population Tax’, each having to pay a certain number of zonks, that number being the total number of males. (The idea was to encourage polygamous marriages.) After the change, all Martians, male and female, were to pay Population Tax, which was to be a certain number of zinks, that number being the total number of males and females.
To Boldly Prototype What Everyone Has Prototyped Before: The Voyages and Perspectives of Prototyping Novices

Microcontroller chips are commonly used in everyday electronics. Household items as well as industrial machinery and even defensive technologies rely on these Very-large-scale integration integrated circuits (VLSI IC) computing units. For a long time, experts in the fields of electrical engineering, computer science, or similar domains were required to program such units and design the components around them. Even though projects like “Basic Stamp” tried to popularize microcontrollers like the PIC16, making them more accessible for novice users in the early 90s, and several educational kits attempted the same later, it is fair to state that the concept used by the Arduino Prototyping platform enabled a broader range of people with a more diverse professional background to use microcontroller technology for themselves. Artists, hobbyists, but also people from the aforementioned technical fields use the platform for their projects, due to its simplified software and hardware environment, as well as their low entry barrier. However, with advances in electronics and the creativity of groups and individuals, projects and extensions have become more complex, and therefore, the requirements towards the capabilities, as well as the usability of such prototyping platforms have increased. With this position paper, we want to give an insight into the challenges and obstacles novice users of the Arduino platform can encounter by analyzing data from a web-forum and interpreting it by comparing it to our own observations we made as instructors in the field of hardware prototyping, followed by suggestions to an initial set of promising directions for easing the entry level for novice users.
Evolutionary walks through flower colour space driven by gene expression in Petunia and allies (Petunieae)

The structure and function of biochemical and developmental pathways determine the range of accessible phenotypes, which are the substrate for evolutionary change. Accordingly, we expect that observed phenotypic variation across species is strongly influenced by pathway structure, with different phenotypes arising due to changes in activity along pathway branches. Here, we use flower colour as a model to investigate how the structure of pigment pathways shapes the evolution of phenotypic diversity. We focus on the phenotypically diverse Petunieae clade in the nightshade family, which contains ca 180 species of Petunia and related genera, as a model to understand how flavonoid pathway gene expression maps onto pigment production. We use multivariate comparative methods to estimate co-expression relationships between pathway enzymes and transcriptional regulators, and then assess how expression of these genes relates to the major axes of variation in floral pigmentation. Our results indicate that coordinated shifts in gene expression predict transitions in both total anthocyanin levels and pigment type, which, in turn, incur trade-offs with the production of UV-absorbing flavonol compounds. These findings demonstrate that the intrinsic structure of the flavonoid pathway and its regulatory architecture underlies the accessibility of pigment phenotypes and shapes evolutionary outcomes for floral pigment production.
The effect of stent graft curvature on the hemodynamic displacement force after abdominal aortic aneurysm endovascular repair

Endovascular aortic aneurysm repair is a minimally invasive procedure with low mortality and morbidity. Clinical studies have revealed that a displacement force (DF) can cause stent graft (SG) migration in some circumstances requiring repeated intervention. This study aims to determine the relationship between the SG curvature and the calculated DF from four patient-specific computational fluid dynamics models. The SG's curvature was defined according to the centrelines of the implanted SG's branches. The centrelines were defined as either intersecting or separated lines. The centreline curvature (CLC) metrics were calculated based on the local curvature radii and the distances from the centrelines of idealized straight branches. The average CLC value and average variation were calculated to represent the entire graft's curvature. These CLC calculations were compared, and the method that gave the best correlation to the calculated DF was found. The optimal correlation is obtained from calculating the CLC average variation using separated centrelines and distance from straight lines, with an R2 = 0.89. Understanding the relationship between vascular morphology and DF can help identify at-risk patients before the procedure. In these cases, we can provide appropriate treatment and follow up with the patient to prevent future failure.
Colonization–persistence trade-offs in natural bacterial communities

Fitness equalizing mechanisms, such as trade-offs, are recognized as one of the main factors promoting species coexistence in community ecology. However, they have rarely been explored in microbial communities. Although microbial communities are highly diverse, the coexistence of their multiple taxa is largely attributed to niche differences and high dispersal rates, following the principle ‘everything is everywhere, but the environment selects’. We use a dynamical stochastic model based on the theory of island biogeography to study highly diverse bacterial communities over time across three different systems (soils, alpine lakes and shallow saline lakes). Assuming fitness equalization mechanisms, here we newly analytically derive colonization–persistence trade-offs, and report a signal of such trade-offs in natural bacterial communities. Moreover, we show that different subsets of species in the community drive this trade-off. Rare taxa, which are occasional and more likely to follow independent colonization/extinction dynamics, drive this trade-off in the aquatic communities, while the core sub-community did it in the soils. We conclude that equalizing mechanisms may be more important than previously recognized in bacterial communities. Our work also emphasizes the fundamental value of dynamical models for understanding temporal patterns and processes in highly diverse communities.
Feeding Aspects of Common Dolphinfish, Coryphaena hippurus (Linnaeus, 1758), Exploited from Indian Waters

ABSTRACT Manas, H.M. ; Ghosh, S. ; Rohit, P.; Rajesh, K.M. ; Abdussamad, E.M. ; Satishkumar, M. ; Pokkathappada, A.A. ; Rathinam, M.M. , and Divipala, I. , 2023. Feeding aspects of dolphinfish, Coryphaena hippurus (Linnaeus, 1758), exploited from Indian waters. Journal of Coastal Research, 39(4), 675–684. Charlotte (North Carolina), ISSN 0749-0208. The common dolphinfish, Coryphaena hippurus, is one of the top predatory fish in pelagic waters, landed all along the Indian coast. The present study was conducted to gain a holistic knowledge of the food and feeding habits of the common dolphinfish from Indian waters. Around 2559 specimens were studied, of which 65.8% were male and 34.2% were female. The species fed on several prey items encountered in all months, scads being the dominant group and the highest preference in fishes >60 cm total length (TL). Fishes of TL <45 cm mainly fed on whitebaits; those 45–60 cm fed on crabs and scads, indicating a shift in prey preference with change in body size and the species being opportunistic feeders, preferring abundant prey species in the environment. August to March showed similar food preferences and overlapping of prey items. This study will help us understand the trophodynamics of the common dolphinfish, allowing policy makers to formulate unified management and conservation measures for sustainable exploitation of the species from Indian waters.
Compressibility effects on the secondary instabilities of the circular cylinder wake

Abstract With a growing interest in low Reynolds number compressible flows, compressibility effects on the secondary instabilities developing on the circular cylinder periodic wake are investigated. The unsteady and time-averaged two-dimensional flows are characterised for Reynolds numbers ${{Re}} \in [200;350]$ and Mach numbers up to ${{M}}_{\infty }=0.5$, revealing different flow structures which influence the characteristics of the secondary unstable modes. The two-dimensional time-periodic solution is used as the base state for a global linear stability analysis performed by means of Floquet theory coupled with a time-stepping finite-difference approach of the nonlinear operator. The influence of compressibility on mode A and mode B secondary instabilities which are responsible for the three-dimensionalisation of the two-dimensional periodic wake is analysed. A stabilising or a destabilising effect of compressibility is observed on mode A, depending on the Reynolds number and the spanwise wavelength of the mode, while mode B is stabilised by the increase of the Mach number. Compressibility is indeed found to decrease the mode kinetic energy production due to base flow shear conversion, which drives the growth of mode B. This results in a delay of the three-dimensionalisation process of the wake due to compressibility.
Extended home visits can provide multidimensional adapted professional support for parents – an intervention study

Abstract Aim: The aim of this study was to explore healthcare professionals’ experiences of working with extended home visits for parents. Background: It is essential to identify parents, both expectant and with a newborn child, who need support in their parenting abilities at an early stage because children’s health and well-being are affected by their home environment as well as by their parents’ health and social relationships. Home visits represent a cost-effective way of identifying and supporting families with a newborn. Further research is needed to explore healthcare professionals’ experiences working with extended home visits for parents. Methods: This was a qualitative interview study focusing on an intervention introduced in the Enhanced Parenting—Extended Home Visits project in Sweden. Data were collected via 13 semi-structured interviews with healthcare professionals who provide the intervention in antenatal care (midwives) and child health care (CHC nurses and family supporters), and a qualitative content analysis was performed. Findings: Data analysis resulted in one theme and four categories. The theme – to provide multidimensional adapted professional support, – and the four categories – strengthened collaboration between professionals enriches their work. Home visits provide time for conversation, which promotes continuity of care and relationships with parents; being humble guests in parents’ homes provides insight; and home visits provide the opportunity to strengthen parenting and participation in the family centre. The goals of the Enhanced Parenting—Extended Home Visits project were to strengthen parents’ confidence in their parenting abilities and to build trusting relationships with healthcare professionals. The conclusion of this study, from the participants’ perspective, is that these goals can be achieved with the intervention. Implications for Practice: Extended home visits seem to help healthcare professionals provide collaborative, multi-professional support for parents, both expectant and with a newborn child, with unique support needs.