Miracle-dz/UniFAR-FTUs huggingface dataset:
Parameter optimization of LS-SVM for regression using NGA

Compared with support vector machine (SVM), least squares support vector machine (LS-SVM) has overcame the shortcoming of higher computational burden by solving linear equations, and has been widely used in classification and nonlinear function estimation. But there is no efficient method for parameter selection of LS-SVM. In this paper, the sharing function based niche genetic algorithm (SNGA) is used to the parameter optimization of LS-SVM for regression. In the SNGA approach, k-folds cross validation is used to evaluate the LS-SVM generalization performance. The inverse of the average test error of the k trials is used as the fitness value. The hamming distance between each two individuals is defined as the sharing function. Two benchmark problems, SINC function regression and Henon map time series prediction are used as examples for demonstration. The results indicate that this approach can escape from the blindness of man-made choice of the LS-SVM parameters. It enhances the efficiency and the capability of regression. With little modification, this approach is also can be used to the parameter optimization of SVM or LS-SVM for classification.
Technology-facilitated abuse among Americans age 50 and older: a latent class analysis

ABSTRACT Technology-facilitated abuse (TFA) is of growing concern and is a form of elder abuse. There is limited TFA research in general population samples in the U.S. among older adults. Researchers conducted a survey of behavior-based forms of TFA experiences in a nationally representative sample of n = 1,011 U.S. adults ages 50 and older. Within this sample, 63.8% of respondents reported some experience of TFA during their lifetime. Latent class analyses were applied to understand the pattern of older adults’ exposure to ten different forms of TFA resulting in three classes distinguished by the number of different TFA types experienced: low TFA (55%), low-mid TFA (40%) and high TFA (5%). Socio-economic characteristics associated with these TFA profiles, as well as perpetrator relationship, post-TFA behaviors, and resulting harms associated with the TFA experiences, were examined to inform research, prevention, and intervention activities. Attention across different sectors to TFA among older adults is needed.
A NOTE ON SINGULAR IDEALS

Introduction. In this note, A is a ring with identity, and modules are left, unitary. Our object here is to answer (in the negative) the following question raised by F.L. Sandomierski in [5, p. 117] : Does the condition Z (M/Z(M)) = 0 for every module M imply that A has a semi-simple maximal left quotient ring? It is known that A has a semi-simple maximal left quotient ring if, and only if, Z(A) = 0 and the dimension of AA is finite (in the sense of Goldie) [5, Th. 1.6]. In fact, we characterize a ring with Z (A) = 0 by the above given condition. This characterization also proves that the homomorphic image of an injective module over a ring A with Z(A) = 0 has its singular submodule as a direct summand. Finally, we give a characterization of a self-injective regular ring and a characterization of a self-injective non-regular ring.
ESGO/ESHRE/ESGE Guidelines for the fertility-sparing treatment of patients with endometrial carcinoma

Background The standard surgical treatment of endometrial carcinoma (EC) consisting of total hysterectomy with bilateral salpingo-oophorectomy drastically affects the quality of life of patients and creates a challenge for clinicians. Recent evidence-based guidelines of the European Society of Gynaecological Oncology (ESGO), the European SocieTy for Radiotherapy & Oncology (ESTRO) and the European Society of Pathology (ESP) provide comprehensive guidelines on all relevant issues of diagnosis and treatment in EC in a multidisciplinary setting. While also addressing work-up for fertility preservation treatments and the management and follow-up for fertility preservation, it was considered relevant to further extend the guidance on fertility sparing treatment. Objectives To define recommendations for fertility-sparing treatment of patients with endometrial carcinoma. Materials and methods ESGO/ESHRE/ESGE nominated an international multidisciplinary development group consisting of practicing clinicians and researchers who have demonstrated leadership and expertise in the care and research of EC (11 experts across Europe). To ensure that the guidelines are evidence-based, the literature published since 2016, identified from a systematic search was reviewed and critically appraised. In the absence of any clear scientific evidence, judgment was based on the professional experience and consensus of the development group. The guidelines are thus based on the best available evidence and expert agreement. Prior to publication, the guidelines were reviewed by 95 independent international practitioners in cancer care delivery and patient representatives. Results The multidisciplinary development group formulated 48 recommendations for fertility-sparing treatment of patients with endometrial carcinoma in four sections: patient selection, tumour clinicopathological characteristics, treatment and special issues. Conclusions These recommendations provide guidance to professionals caring for women with endometrial carcinoma, including but not limited to professionals in the field of gynaecological oncology, onco-fertility, reproductive surgery, endoscopy, conservative surgery, and histopathology, and will help towards a holistic and multidisciplinary approach for this challenging clinical scenario. What is new? A collaboration was set up between the ESGO, ESHRE and ESGE, aiming to develop clinically relevant and evidence-based guidelines focusing on key aspects of fertility-sparing treatment in order to improve the quality of care for women with endometrial carcinoma across Europe and worldwide.
Introducing e-health technology to routine cataract care: patient perspectives on web-based eye test for postoperative telemonitoring

For successful adoption of postoperative web-based eye testing and telemonitoring in cataract care, it is important to build trust in remote care delivery and retain access to conventional care when necessary. Purpose: To explore cataract patients' experiences with an e-health tool for self-assessing visual function (ie, a web-based eye test), and to formulate recommendations for its successful adoption in routine cataract care. Setting: Clinics in the Netherlands, Germany, and Austria. Design: Mixed-methods study. Methods: 22 participants were included in this study; in-depth interviews were conducted with 12. Questionnaires and in-depth semi-structured interviews were conducted alongside a multicenter randomized controlled trial evaluating the validity, safety and cost-effectiveness of remote care after cataract surgery (Cataract Online Refraction Evaluation, a Randomized Controlled Trial). Results were analyzed thematically. Results: Participants reported positively about performing the web-based eye test at home. 4 overarching themes were identified in the interviews. First, participants were inventive in overcoming practical barriers encountered while conducting the test. Second, participants desired a clear presentation of test results and their meaning. Third, the ability to self-monitor visual function was appreciated. Fourth, most participants preferred to keep the option to contact their eyecare professional (ECP) postoperatively, especially when experiencing symptoms. Most would be satisfied with a phone consultation or an e-consult. Participants reported positive experiences with the web-based eye test. Barriers for successful adoption were identified, including insecurity about correctly performing the test, incomplete information on how to interpret test results, and a feeling that in-hospital assessments were superior to remote assessments. Conclusions: It is recommended to focus on building trust in remote eyecare delivery and that access to the ECP be retained when medically indicated or deemed necessary by the patient.
Efficacious dosing regimens for anti-TNF therapies in inflammatory bowel disease: where do we stand?

ABSTRACT Introduction During the last decades, biologics have revolutionized the treatment of Crohn’s disease and ulcerative colitis. Even though the inflammatory bowel disease (IBD) armamentarium is rapidly expanding with novel biologics, anti-tumor necrosis factor (TNF) antibodies remain the first-line biologic therapy in most areas of the world. However, anti-TNF therapy is not effective in all patients (primary non-response) and patients can lose effect over time (secondary loss of response). Areas covered This review provides an overview of the current induction and maintenance dosing regimens of the available anti-TNF antibodies and associated challenges in adult patients with IBD. We outline different strategies to overcome these difficulties, including combination therapy, therapeutic drug monitoring (TDM), and dose escalation. Finally, we discuss expected future progress in anti-TNF management. Expert opinion Anti-TNF agents will remain a cornerstone of IBD treatment in the coming decade. Progress will be made in biomarkers for the prediction of response and individualized dosing regimens. The advent of subcutaneous infliximab challenges the need for concomitant immunosuppression.
Delegation of insulin administration to non-registered healthcare workers in community nursing teams: A qualitative study.

AIMS To explore stakeholder perspectives on the benefits and/or disadvantages of the delegation of insulin injections to healthcare support workers in community nursing services. DESIGN Qualitative case study. METHODS Interviews with stakeholders purposively sampled from three case sites in England. Data collection took place between October 2020 and July 2021. A reflexive thematic approach to analysis was adopted. RESULTS A total of 34 interviews were completed: patients and relatives (n = 7), healthcare support workers (n = 8), registered nurses (n = 10) and senior managers/clinicians (n = 9). Analysis resulted in three themes: (i) Acceptance and confidence, (ii) benefits and (iii) concerns and coping strategies. Delegation was accepted by stakeholders on condition that appropriate training, supervision and governance was in place. Continuing contact between patients and registered nurses, and regular contact between registered nurses and healthcare support workers was deemed essential for clinical safety. Services were reliant on the contribution of healthcare support workers providing insulin injections, particularly during the COVID-19 pandemic. Benefits for service and registered nurses included: flexible team working, increased service capacity and care continuity. Job satisfaction and career development was reported for healthcare support workers. Patients benefit from timely administration, and enhanced relationships with the nursing team. Concerns raised by all stakeholders included potential missed care, remuneration and task shifting. CONCLUSION Delegation of insulin injections is acceptable to stakeholders and has many benefits when managed effectively. IMPACT Demand for community nursing is increasing. Findings of this study suggest that delegation of insulin administration contributes to improving service capacity. Findings highlight the essential role played by key factors such as appropriate training, competency assessment and teamwork, in developing confidence in delegation among stakeholders. Understanding and supporting these factors can help ensure that practice develops in an acceptable, safe and beneficial way, and informs future development of delegation practice in community settings. PATIENT OR PUBLIC CONTRIBUTION A service user group was consulted during the design phase prior to grant application and provided comments on draft findings. Two people with diabetes were members of the project advisory group and contributed to the study design, development of interview questions, monitoring study progress and provided feedback on study findings.
A Quantitative Metric to Validate Risk Models

The paper applies a back-testing validation methodology of economic scenario generating models and introduces a new D-statistic to evaluate the robustness of the underlying model during a specified validation period. The statistic presented here can be used to identify the optimal model by repeating calibrations with changing initial parameters. It can compare between calibration methods, be used to rank between models, and provide a single concise reporting metric for on-going model monitoring. To illustrate this methodology and ranking between models, the closed form bond pricing solutions of the CIR 1- and 2-factor models are used. CIR model parameters were estimated using Matlab’s built-in least squares minimization routine. At each observation date during the validation period, a time-weighted point estimate of the error between the model and actual market term structure is calculated. Finally, the maximum of these time-weighted points across the validation duration is introduced as the Dstatistic. The robustness of the D-statistic is improved by implementing a first-order autoregressive sampling bootstrapping algorithm, which generates an empirical distribution for calculating the standard error of the D-statistic.
FES-rowing: a well-tolerated and highly beneficial exercise for a patient with Brown-Sequard syndrome

Context: Brown-Séquard Syndrome (BSS) is a rare neurological condition associated with Spinal Cord Injury (SCI). Hemisection of the spinal cord causes paralysis of the homolateral side, and thermoalgesic dysfunction on the opposite side. Cardiopulmonary and metabolic alterations have been reported. For all these patients, regular physical activity is highly recommended and functional electrical stimulation (FES) may be a good option, especially for those with paraplegia. However, to our knowledge, the effects of FES have primarily been studied in those with complete SCI and data regarding application and effects in patients with incomplete lesions (with sensory feedback) is lacking. The present case report therefore evaluated the feasibility and effectiveness of a 3-month FES-rowing program in a patient with BSS. Methods: Knee extensor muscle strength and thickness, walking and rowing capacities as well as quality of life were evaluated before and after 3 months of FES-rowing (two sessions per week) in a 54 year old patient with BSS. Results: The individual had excellent tolerance and adherence to the training protocol. All measured parameters were greatly improved after 3 months: on average, + 30% rowing capacity, + 26% walking capacity, + 24.5% isometric strength, + 21.9% quadriceps muscle thickness, + 34.5% quality of life. Conclusion: FES-rowing appears to be well tolerated and highly beneficial for a patient with incomplete SCI and could therefore be considered as an appealing exercise option for these patients.
Preclinical development of a novel Group B Streptococcus (GBS) vaccine candidate for maternal immunization based upon the alpha‐like protein family of GBS surface proteins (Alp)

A novel Group B Streptococcus (GBS) vaccine, based upon the GBS alpha‐like surface proteins, is being developed by MinervaX for administration to pregnant women. The vaccine is intended to generate antibodies (IgG) capable of crossing the placenta, in order to passively immunize the baby and provide protection in utero and up to 3 months after birth. An initial vaccine candidate, GBS‐NN (based on the N‐terminal domains of Rib and AlphaC surface proteins) was replaced, due to insufficient cross‐reactivity with the two other N‐terminal proteins (Alp1 and Alp2/3), by a modified vaccine candidate designated GBS‐NN/NN2 that included all four AlpNs. Preclinical studies raised no safety concerns and the subsequent Phase I clinical trial demonstrated that the vaccine was well tolerated and strongly immunogenic. As the vaccine is intended for use during pregnancy for maternal immunization, an embryofetal study in rats and a fertility and embryofetal study in rabbits were performed, in both cases using GBS‐NN/NN2. Vaccination of female rats or rabbits did not adversely affect embryofetal development or survival in either species, or mating or fertility in rabbits. In both studies, the pregnant animals developed immune responses to GBS‐NN and GBS‐NN2 proteins and concentrations of antibodies to both fusion proteins were detected in the fetuses and in the amniotic fluid. Data generated during these reproductive studies indicated a suitable safety margin (approximately 40‐fold clinical dose) considered appropriate to support a subsequent human trial of GBS‐NN/NN2 administered in the second and third trimesters of pregnancy.
GreenScale: Carbon-Aware Systems for Edge Computing

To improve the environmental implications of the growing demand of computing, future applications need to improve the carbon-efficiency of computing infrastructures. State-of-the-art approaches, however, do not consider the intermittent nature of renewable energy. The time and location-based carbon intensity of energy fueling computing has been ignored when determining how computation is carried out. This poses a new challenge -- deciding when and where to run applications across consumer devices at the edge and servers in the cloud. Such scheduling decisions become more complicated with the stochastic runtime variance and the amortization of the rising embodied emissions. This work proposes GreenScale, a framework to understand the design and optimization space of carbon-aware scheduling for green applications across the edge-cloud infrastructure. Based on the quantified carbon output of the infrastructure components, we demonstrate that optimizing for carbon, compared to performance and energy efficiency, yields unique scheduling solutions. Our evaluation with three representative categories of applications (i.e., AI, Game, and AR/VR) demonstrate that the carbon emissions of the applications can be reduced by up to 29.1% with the GreenScale. The analysis in this work further provides a detailed road map for edge-cloud application developers to build green applications.
Multi-Objective Multi-Agent Planning for Discovering and Tracking Multiple Mobile Objects

We consider the online planning problem for a team of agents to discover and track an unknown and time-varying number of moving objects from onboard sensor measurements with uncertain measurement-object origins. Since the onboard sensors have a limited field-of-view, the usual planning strategy based solely on either tracking detected objects or discovering unseen objects is inadequate. To address this, we formulate a new information-based multi-objective multi-agent control problem, cast as a partially observable Markov decision process (POMDP). The resulting multi-agent planning problem is exponentially complex due to the unknown data association between objects and multi-sensor measurements; hence, computing an optimal control action is intractable. We prove that the proposed multi-objective value function is a monotone submodular set function, which admits low-cost suboptimal solutions via greedy search with a tight optimality bound. The resulting planning algorithm has a linear complexity in the number of objects and measurements across the sensors, and quadratic in the number of agents. We demonstrate the proposed solution via a series of numerical experiments with a real-world dataset.
On the Feasibility and Robustness of Pointwise Evaluation of Query Performance Prediction

Despite the retrieval effectiveness of queries being mutually independent of one another, the evaluation of query performance prediction (QPP) systems has been carried out by measuring rank correlation over an entire set of queries. Such a listwise approach has a number of disadvantages, notably that it does not support the common requirement of assessing QPP for individual queries. In this paper, we propose a pointwise QPP framework that allows us to evaluate the quality of a QPP system for individual queries by measuring the deviations between each prediction versus the corresponding true value, and then aggregating the results over a set of queries. Our experiments demonstrate that this new approach leads to smaller variances in QPP evaluations across a range of different target metrics and retrieval models.
Comparison of Quadrature Rules for the Wielandt-Nyström Method with Statistical Applications

Many statistics used to test that a sample of n points in the unit interval [0,1] comes from a known distribution can be studied using the theory of degenerate U - and V-statistics. In this theory, a special role is played by the eigenvalues of an integral operator. The aim of the present paper is to compare several versions of the Wielandt-Nystrom method for the approximation of the eigenvalues of this integral operator. We apply it to compute the eigenvalues of the Anderson-Darling statistic.
Kernel-level Rootkit Detection, Prevention and Behavior Profiling: A Taxonomy and Survey

One of the most elusive types of malware in recent times that pose significant challenges in the computer security system is the kernel-level rootkits. The kernel-level rootkits can hide its presence and malicious activities by modifying the kernel control flow, by hooking in the kernel space, or by manipulating the kernel objects. As kernel-level rootkits change the kernel, it is difficult for user-level security tools to detect the kernel-level rootkits. In the past few years, many approaches have been proposed to detect kernel-level rootkits. It is not much difficult for an attacker to evade the signature-based kernel-level rootkit detection system by slightly modifying the existing signature. To detect the evolving kernel-level rootkits, researchers have proposed and experimented with many detection systems. In this paper, we survey traditional kernel-level rootkit detection mechanisms in literature and propose a structured kernel-level rootkit detection taxonomy. We have discussed the strength and weaknesses or challenges of each detection approach. The prevention techniques and profiling kernel-level rootkit behavior affiliated literature are also included in this survey. The paper ends with future research directions for kernel-level rootkit detection.
Synge's world function applied to causal diamonds and causal sets

One of the major tasks in discrete theories of gravity, including causal set theory, is to discover how the combinatorics of the underlying discrete structure recovers various geometric aspects of the emergent spacetime manifold. In this paper, I develop a new covariant approach to connect the combinatorics of a Poisson sprinkled causal set to the geometry of spacetime, using the so-called Synge's world function. The Poisson sprinkling depends crucially on the volume of a causal interval. I expand this volume, in 2 dimensions, in powers of Synge's world function and Ricci scalar. Other geometric properties of Synge's world function are well-known, making it easy to connect to the curvature of spacetime. I use this connection to provide a straightforward proof that the BDG action of causal sets gives the Einstein-Hilbert action in the continuum limit, without having to work in a particular coordinate system like Riemann normal coordinates.
MEASUREMENT OF THE CASIMIR FORCE BETWEEN PARALLEL METALLIC SURFACES

We report on the measurement of the Casimir force between conducting surfaces in a parallel configuration. The force is exerted between a silicon cantilever coated with chromium and a similar rigid surface and is detected looking at the shifts induced in the cantilever frequency when the latter is approached. The scaling of the force with the distance between the surfaces was tested in the 0.5 3.0 μm range, and the related force coefficient was determined at the 15% precision level. PACS numbers: 12.20. Fv, 07.07. Mp, 04.80. Cc