Miracle-dz/UniFAR-FTUs huggingface dataset:
Current Evidence, Limitations and Future Challenges of Survival Prediction for Glioblastoma Based on Advanced Noninvasive Methods: A Narrative Review

Background and Objectives: Survival estimation for patients diagnosed with Glioblastoma (GBM) is an important information to consider in patient management and communication. Despite some known risk factors, survival estimation remains a major challenge. Novel non-invasive technologies such as radiomics and artificial intelligence (AI) have been implemented to increase the accuracy of these predictions. In this article, we reviewed and discussed the most significant available research on survival estimation for GBM through advanced non-invasive methods. Materials and Methods: PubMed database was queried for articles reporting on survival prognosis for GBM through advanced image and data management methods. Articles including in their title or abstract the following terms were initially screened: ((glioma) AND (survival)) AND ((artificial intelligence) OR (radiomics)). Exclusively English full-text articles, reporting on humans, published as of 1 September 2022 were considered. Articles not reporting on overall survival, evaluating the effects of new therapies or including other tumors were excluded. Research with a radiomics-based methodology were evaluated using the radiomics quality score (RQS). Results: 382 articles were identified. After applying the inclusion criteria, 46 articles remained for further analysis. These articles were thoroughly assessed, summarized and discussed. The results of the RQS revealed some of the limitations of current radiomics investigation on this field. Limitations of analyzed studies included data availability, patient selection and heterogeneity of methodologies. Future challenges on this field are increasing data availability, improving the general understanding of how AI handles data and establishing solid correlations between image features and tumor’s biology. Conclusions: Radiomics and AI methods of data processing offer a new paradigm of possibilities to tackle the question of survival prognosis in GBM.
Quasistatic heat front and delocalized heat flux

New results concerning the mathematical properties of the Fokker–Planck equation describing the electron distribution function are presented. The validity of the approximations obtained by using a finite number of Legendre polynomials to describe the electron distribution function is discussed. It is shown that, due to the Landau form of the electron‐ion collision operator, it is sufficient to use two or three Legendre polynomials in problems of interest. The theory is applied to the classical albedo problem as a test, and is also applied to determine the distribution and the heat flux in a heat front typical of laser plasma experiments. It is shown that the heat flux can be expressed as a sort of convolution of the Spitzer–Harm heat flux by a delocalization function. The convolution formula leads in a physically relevant way to the saturation and the delocalization of the heat flux.
High-intensity interval training: a brief review on the concept and different applications

Introduction: Due to its highly dynamic characteristic and the time efficiency generated in relation to other training methods, High Intensity Interval Training (HIIT) has become a strategy used in different contexts. HIIT is understood as a training method that intersperses periods of effort performed at high intensity with periods of active (when an activity is performed at low intensity) or passive (when no activity is performed) recovery. Based on this concept that does not discriminate types of exercises, different HIIT models can be found in the literature, such as classic HIIT, Sprint Interval Training (SIT), HIIT with bodyweight, High Intensity Functional Training (HIFT), High Intensity Circuit Training (HICT), and High Intensity Resistance Training (HIRT), expanding the possibilities of applying HIIT to different purposes and audiences. Aim: a) to revisit, through a brief update, the concept of HIIT and its different aspects; b) present, from a scientific perspective, different protocols that can be applied based on the concept of HIIT and its effects. Conclusion: Based on the exposed concept and on the HIIT intensity control variables, this approach can be applied to different training modalities. In addition, it can be used as a strategy to provide safe and efficient training across different populations.
Enhancing Melatonin Secretion: The Methodical Consumption of Tryptophan from Whole Cowâ•Žs Milk to Regulate Sleep Quality in Individuals Aged 18-30 with Delayed Sleep-Wake Phase Disorder

Young adults in the United States are increasingly affected by DSPD (delayed sleepwake phase disorder), a prevalent circadian rhythm disorder that delays evening sleep and morning wake times relative to the solar cycle. Although medicinal supplements have shown to produce effective results on immediate sleep induction, they lack the ability to aid in regulation and maintenance of routine sleep schedules. Alternatively, a dietary method may be able to adjust the deficits of supplements. A review of the literature on clinical nutrition and endocrinology suggests that dietary alterations through the timed consumption of tryptophanabundant whole cow’s milk may be an auxiliary option of improving sleep quality and morning alertness in individuals with DSPD. Studies on chrono-nutrition indicate that dietary components absorbed by the bloodstream can alter the circadian schedule of melatonin secretion from the pineal gland, and the timed consumption of tryptophan-abundant foods, such as whole cow’s milk, can consequently spike melatonin levels before a DSPD patient’s desired sleep time and promote circadian rhythm advancement. Based on the stated studies, this research proposes the MILC (Melatonin Intake through Lactalbumin (a-lac) Consumption) treatment, the consistent, timed consumption of milk. The MILC treatment may decrease a DSPD patient’s morning sleepiness on the basis that disordered, high-stressed, and sleep deprived individuals are susceptible to minimal changes in hormones because their bodies naturally attempt to attain homeostatic equilibrium. The correlation between chrono-nutrition and dietary effectiveness is a novel idea, and testing is needed to quantify the optimal timings and ranges of dietary tryptophan that can produce a significant effect on the sleep quality of a DSPD patient. THE CONSUMPTION OF MILK TO ADJUST DSPD SLEEP 3
The impact of stay-at-home orders on mental health: Evidence from search-based symptoms

I investigate the impact of the implementation of stay-at-home orders on the incidence of mental health conditions in the US during the first year of the coronavirus pandemic. I use a novel dataset that maps search queries to thirty mental health symptoms. Exploiting the staggered implementation of lockdowns, I document that the enaction of the stay-at-home orders increased mental health searches related to various anxiety disorders, severe forms of depression, sleep disorders, attention deficit, and epilepsy. Treated states are estimated to have experienced two mental distress waves in April-May and November-December. JEL classification : I10, I14, I18, I30.
Analysis of the Links between Social Intelligence and Coping Strategies of Business Managers in Terms of Development of Their Potential

The social as well as psychological development of individuals’ potential is influenced by many factors, including managerial competences such as social intelligence and ways of coping with stress. This paper presents the links between social intelligence and strategies for coping with demanding situations by business managers, as well as gender differences in the perception of social intelligence and in the preference for coping strategies between male and female business managers. The research sample consisted of 149 business managers, of which 76 (51%) were male and 73 (49%) were female managers. The results were obtained through research based on two methodologies: MESI for the detection of social intelligence, and Brief COPE, designed to identify coping strategies. Based on the research results, it can be concluded that the links between the social intelligence factors and coping strategies, as well as gender differences in the perception of social intelligence and coping strategies by male and female business managers, have been confirmed. Research into the relationship between these two aspects and its results could contribute to the elimination of undesirable factors influencing the work process and to the subsequent development of the psychological, social and work potential of business managers.
Online Learning of Optimal Control Signals in Stochastic Linear Dynamical Systems

Among the most canonical systems are linear time-invariant dynamics governed by differential equations and stochastic disturbances. Since in many application the true dynamics are not known, an interesting problem in this class of systems is learning to minimize a quadratic cost function when system matrices are unknown. This work initiates theoretical analysis of implementable reinforcement learning policies for balancing exploration versus exploitation in such systems. We present an online policy that learns the optimal control actions fast by carefully randomizing the parameter estimates to explore. More precisely, we establish performance guarantees for the presented policy showing that the regret grows as the square-root of time multiplied by the number of parameters . Implementation of the policy for a ﬂight control task shows its efﬁcacy. Further, we prove tight results that ensure stability under inexact system matrices and fully specify unavoidable performance degradations caused by a non-optimal policy. To obtain the results, we conduct a novel analysis for matrix perturbation, bound comparative ratios of stochastic integrals, and introduce the new method of policy differentiation. These technical novelties are expected to provide a useful cornerstone for similar continuous-time reinforcement learning problems.
Some recent developments in microstrip antenna design

The fundamental radiation mechanism occurring at an open-circuit discontinuity is discussed to reveal limitations on bandwidth, efficiency, and sidelobe level control inherent in microstrip antennas, based on resonator action. Extraneous radiation from feed transitions is also assessed and shown to be a problem in some cases. Novel two-dimensional arrays using resonant elements are described which illustrate these performance limitations. In contrast, a nonresonant circularly polarized spiral element has a very wide bandwidth at the expense of lower efficiency. Other designs are then noted to show how a particular parameter or aspect can be optimized for antenna applications demanding choice of polarization, frequency scanning, log periodic behavior, low angle radiation, and integration with circuitry on a common substrate.
Discovery of 16-Androstenes (Androstenone and Androstenol), Their Synthesis Pathway, and Possible Role in Reproduction of Mouse Deer (Moschiola indica)

We discovered odorous 16-androstenes (Androstenone and Androstenol) in endangered mouse deer during a captive breeding program. This study examined the molecular characteristics, their synthesis pathway, and the possible functional role of these compounds in the reproduction of mouse deer. CYP17A1 and CYB5 genes were cloned and expressed in HEK-293, COS-7 cell lines, and gonads of mouse deer to investigate the CYP17A1 gene’s andien-β-synthase activity towards the synthesis of 16-androstenes in mouse deer. An enzyme immunoassay was further developed and standardized to measure fecal androstenone during the reproductive cycles of mouse deer. Results showed that the mouse deer CYP17A1 gene possesses andien-β-synthase activity and could transform pregnenolone into 5,16-androstadien-3β-ol. The expression of the CYP17A1 gene upregulated in the testis and ovary compared to other tissues in mouse deer. Significantly elevated androstenone and estrogens were recorded prior to delivery and postpartum estrus/mating in mouse deer. Further, there were weak correlations between fecal androstenone and estrogens/androgens in mouse deer during the breeding season. These findings suggest that androstenone probably plays a role in the reproductive activities of mouse deer. This knowledge can be used for captive breeding programs of mouse deer in India and elsewhere.
Deep Reinforcement Learning Policies in the Frequency Domain

Reinforcement learning policies based on deep neural networks are vulnerable to imperceptible adversarial perturbations to their inputs, in much the same way as neural network image classiﬁers. Recent work has proposed several methods for adversarial training for deep reinforcement learning agents to improve robustness to adversarial perturbations. In this paper, we study the effects of adversarial training on the neural policy learned by the agent. In particular, we compare the Fourier spectrum of minimal perturbations computed for both adversarially trained and vanilla trained neural policies. Via experiments in the OpenAI Atari environments we show that minimal perturbations computed for adversarially trained policies are more focused on lower frequencies in the Fourier domain, indicating a higher sensitivity of these policies to low frequency perturbations. We believe our results can be an initial step towards understanding the relationship between adversarial training and different notions of robustness for neural policies.
Tailoring Choices Made in Scrum Projects: A Systematic Literature Review

Among various Agile Software Development (ASD) methods, Scrum is one of the most widely adopted ones. The Scrum Guide gives a clear description of the Scrum practices, artifacts, and roles. However, due to various project characteristics such as team size, team distribution, project domain, technology, and requirement stability levels, Scrum practices need to be tailored. In this study, we performed a Systematic Literature Review to understand how software development companies adopt Scrum into their contexts, and explore the tailoring choices made in Scrum practices, roles and artifacts. The results of this SLR show that most organizations tailor the existing Scrum components by either not implementing a specific practice, role, or an artifact or modifying the duration limits of the practices. We specified that there are limited number of studies reporting successful Scrum adoptions. Most of the studies in our paper pool report that the tailored Scrum components cause difficulties in getting customer feedback on time, not understanding the sprint goal well enough, having an unordered, unclear product and sprint backlog, and an increase in project failures.
Potentials and currents in the edge tokamak plasma: simplified approach and comparison with two-dimensional modelling

A method of reduction of the two-dimensional equation for the potential to a one-dimensional ordinary equation is suggested and implemented in the B2SOLPS5.0 transport code to simulate a divertor tokamak. The one-dimensional version, which gives similar results as the full two-dimensional version, provides better understanding of the role of various mechanisms of perpendicular conductivity and reduces computational time. The scheme of poloidal (parallel) current calculation is presented and compared to the two-dimensional code results both for the core region and for the scrape-off layer.
ProGenVR: Natural Interactions for Procedural Content Generation in VR

3D content creation for virtual worlds is a difficult task, requiring specialized tools based typically on a WIMP interface for modelling, composition and animation. But these interfaces pose several limitations, namely regarding the 2D-3D mapping required both for input and output. To overcome such limitations, VR modelling approaches have been proposed. However, translating relevant tools for creating large 3D scenes to VR settings is not trivial. Procedural content generation (PCG) is one such tool that allows content to be automatically generated following a set of parameterized rules. In this work, we propose a novel approach for immersive 3D modelling based on a set of procedural rules for content generation and natural interactions to bridge the gap between immersive content creation and PCG. We developed a prototype implementing our approach and conducted a user evaluation to assess its applicability. Results suggest that the cost of time and mental effort associated with the rules’ definition can be compensated by the saved time and physical effort when creating complex scenes.
Coevolutionary Algorithm Applied to Skip Reentry Trajectory Optimization Design

This paper proposed a coevolutionary algorithm combining improved particle swarm optimization algorithm with differential evolution method and its application was provided. Adaptive position escapable mechanism is introduced in the particle swarm optimization to improve the diversity of population and guarantee to achieve the global optima. The differential algorithm is employed in a cooperative manner to maintain the characteristic of fast convergence speed in the later convergence phase. The coevolutionary algorithm is then applied to skip trajectory optimization design for crew exploration vehicle with low-lift-to-drag and several comparative cases are conducted, Results show that coevolutionary algorithm is quite effective in finding the global optimal solution with great accuracy.
Probability and Statistics in the Tinbergen-Keynes Debates

As part of a book symposium on Erwin Dekker's Jan Tinbergen (1903–1994) and the Rise of Economic Expertise (2021), William Peden reflects on shared views on the objectivity and nature of statistics between Tinbergen and Keynes underlying the Tinbergen-Keynes debates.
Employment Regulations and Creation of Skilled Manpower in Industry in East Java Province

The purpose of this study is to further analyze the effect of labor regulations in Indonesia on the provision of skilled labor and encourage entrepreneurs to provide labor in Indonesia to improve export quality. This research uses mixed methods, with a combination of qualitative and quantitative methods to be able to provide results and descriptions related to the influence of labor regulations on workforce creation. This study underscores three important things. First, the understanding of business actors towards labor regulations is still low, and some do not yet know it. Second, the limited capacity of business actors (funds, time, and experts) to conduct intensive and unique training in obtaining skilled workers. Third, the government's attention to labor regulations is still relatively low. So far, the routine is the determination of the UMK every year. Overall, this study observes that no derivative regulations are applied at the local level in creating skilled workers, which causes employers to seek to provide skilled workers with available resources.
Postural orthostatic tachycardia syndrome and orthostatic hypotension in post-acute sequelae of COVID-19 during pregnancy: a case report

Abstract Background Patients with post-acute sequelae of COVID-19 (PASC) often experience the addition of new symptoms after recovery from COVID-19 illness. These may include orthostatic intolerance and autonomic dysfunction, and postural orthostatic tachycardia syndrome has been described to occur in a proportion of patients with PASC. Case summary In this report, we present a 32-year-old pregnant woman (G3P2) who experiences severe orthostatic symptoms as part of her PASC syndrome, which is decoupled from normal physiologic changes of pregnancy. At 25 weeks of gestation, she was evaluated for increasing episodes of dyspnoea, marked tachycardia with minimal exertion, intermittent non-exertional chest pain, and presyncope. This patient had a moderate course of COVID-19 at 12 weeks of gestation, for which she received monoclonal antibody therapy (casirivimab/imdevimab). The patient then had complete resolution of COVID-19 symptoms and felt well for 1 month prior to developing orthostatic symptoms at 25 weeks of gestation. Evaluation with a NASA Lean Test revealed marked orthostatic tachycardia, as well as delayed orthostatic hypotension. Given her COVID-19 illness 4 months prior, PASC involving autonomic dysfunction was diagnosed. Discussion Patients with orthostatic symptoms in PASC should be carefully evaluated with dedicated active stand tests, such as the NASA Lean Test, to characterize the autonomic response to standing. In pregnant patients, an understanding of normal pregnancy physiology is crucial to correctly identify abnormal findings in such tests.
Cooperative negotiation in value-driven engineering and systems design: a technical note

The traditional practice of value-driven engineering and systems design is mainly based on net present values (NPVs). It is essentially enacted as a budgetary technique that neglects the future risk and strategic flexibility of a design project. Incorporating real options theory in value-driven decision models can improve the inability of NPV analysis in dealing with the upside potential of managerial flexibility and operational uncertainty over the design project life. This paper examines the critical issues and research opportunities for establishing a theoretical foundation of value-driven multiplayer game decision making in large complex engineering and systems design projects. This paper envisions a research framework for value-driven cooperative negotiation by synthesising the mathematical foundations of utility theory, real options theory and game theory into a coherent framework of design decision analysis. Fundamental issues and research directions are discussed to develop a variety of new methods for enhancing the formulation of value models for value-driven design with decision support to achieving equilibrium solutions with optimal value allocation among multiple decision agents involved in engineering and systems design.
Cycle‐consistent generative adversarial network optimized with water strider optimization algorithm fostered intrusion detection framework for securing cloud computing environment

Cloud computing is the delivery of computing services including servers, storage, databases, networking, software, analytics, and intelligence over the internet (“the cloud”) to offer faster innovation, flexible resources, and economies of scale. In this article, cycle‐consistent generative adversarial network (CCGAN) optimized with water strider optimization (WSO) algorithm fostered intrusion detection system (IDS) is proposed to secure the cloud computing (CC) environment (IDS‐CC‐CCGAN‐WSOA). Initially, the input data's are gathered via NSL‐KDD benchmark dataset. Then it is given to preprocessing. During preprocessing, it debugs the redundancy and missing value is restored using local least squares. Then, the preprocessed output is fed to the feature selection level. The optimum features are compiled utilizing correlation feature selection approach. This optimum features based, the data's are categorized as normal and anomalous data. The weights of this network are optimized by water strider optimization to attain effectual and optimum solution for recognizing the intruders. The proposed approach is executed in MATLAB. The performance metrics is examined to validate the performance of the proposed approach. Finally, the proposed approach attains 13.9367%, 13.268%, and 13.739% higher accuracy analyzed to the existing approaches, such as IDS‐CC‐DBN‐CSSA, IDS‐CC‐DNN‐IGASAA, and IDS‐CC‐MLPNN‐ABC.