Miracle-dz/UniFAR-FTUs huggingface dataset:
Experimental evidence suggesting temperature-driven dormancy in the planktotrophic larvae of the sea cucumber Isostichopus fuscus

ABSTRACT While larval ecology is central to the population dynamics of marine benthic species with multiphasic life histories, the adaptations of larvae to environmental variability remain incompletely understood in many species. Using the holothuroid echinoderm (sea cucumber) Isostichopus fuscus, we examined how a planktotrophic species can use pre-competency plasticity to withstand suboptimal conditions of temperature over extended periods. Five cohorts of propagules (embryos/larvae) were exposed to temperature treatments (28–29, 24–25 and 20–22°C) in standardized culture settings. Under the coldest temperatures (typical of offshore upwelling areas), development mirrored that obtained under warmer temperatures until the early auricularia stage, where development was arrested for ~5 months in a manner consistent with quiescence. When temperature was increased again, larvae quickly resumed development and settled; no lasting negative impact was noted. The findings suggest that the larvae can use a form of dormancy to withstand suboptimal oceanic conditions for indefinite periods of time until successful delivery to appropriate inshore locations, the habitat were I. fuscus is exclusively found.
Managing tardiness bounds and overload in soft real-time systems

Jeremy P. Erickson: Managing Tardiness Bounds and Overload in Soft Real-Time Systems (Under the direction of James H. Anderson) In some systems, such as future generations of unmanned aerial vehicles (UAVs), different software running on the same machine will require different timing guarantees. For example, flight control software has hard real-time (HRT) requirements—if a job (i.e., invocation of a program) completes late, then safety may be compromised, so jobs must be guaranteed to complete within short deadlines. However, mission control software is likely to have soft real-time (SRT) requirements—if a job completes slightly late, the result is not likely to be catastrophic, but lateness should never be unbounded. The global earliest-deadline-first (G-EDF) scheduler has been demonstrated to be useful for the multiprocessor scheduling of software with SRT requirements, and the multicore mixed-criticality (MC2) framework using G-EDF for SRT scheduling has been proposed to safely mix HRT and SRT work on multicore UAV platforms. This dissertation addresses limitations of this prior work. G-EDF is attractive for SRT systems because it allows the system to be fully utilized with reasonable overheads. Furthermore, previous analysis of G-EDF can provide “lateness bounds” on the amount of time between a job’s deadline and its completion. However, smaller lateness bounds are preferable, and some programs may be more sensitive to lateness than others. In this dissertation, we explore the broader category of G-EDF-like (GEL) schedulers that have identical overhead characteristics to G-EDF. We show that by choosing GEL schedulers other than G-EDF, better lateness can be achieved, and that certain modifications can further improve lateness bounds while maintaining reasonable overheads. Specifically, successive jobs from the same program can be permitted to run in parallel with each other, or jobs can be split into smaller pieces by the operating system. Previous analysis of MC2 has always used less pessimistic execution time assumptions when analyzing SRT work than when analyzing HRT work. These assumptions can be violated, creating an overload that causes SRT guarantees to be violated. Furthermore, even in the expected case that such violations are
Analysis of Cross M- QAM OFDM systems under Gaussian and Impulsive Noise

Power line communications (PLC) allows establishing a digital communications without adding any new wires. However, the power line channel was not originally meant to be used for communications and it is a difficult channel for several reasons, for example, it has high noise. This paper derives the exact symbol error probability (SEP) for cross quadrature amplitude modulation with orthogonal frequency division multiplexing (M-QAM/OFDM) systems over Gaussian and impulsive noise. Analytical performances are evaluated and compared with computational simulations, which show good agreement. Keywords—M-QAM, OFDM, Gaussian noise, impulsive noise, SEP.
Smart home technologies that support independent living: challenges and opportunities for the building industry – a systematic mapping study

ABSTRACT Objective: To provide an overview of the state of research concerning smart technologies that support independent living in buildings, as well as a deeper literature review of the specific challenges for the building industry. Methods: A systematic mapping methodology was applied in this study to provide basis knowledge on the state of the art. The initial search on three databases gave 3485 articles. Of these, 610 articles were finally selected as relevant to the study after removing the duplicates and screening by applying inclusion and exclusion criteria based on titles and abstracts. Keywording was performed in order to answer the research questions of the study. Results: Results from the systematic mapping technology allow the detection of almost mature technologies, as well as promising technologies and research gaps. Results from the deeper literature review have identified challenges and new trends specific to the building industry. Conclusions: Efforts are still needed for the building industry in order to contribute significantly to meeting societal needs. Further research: Research fields that would benefit from further research are highlighted.
Racial/Ethnic Disparities in Health and Life Insurance Denial Due to Cancer among Cancer Survivors

This study examined racial/ethnic differences in health/life insurance denial due to cancer among cancer survivors after the passage of the Affordable Care Act (ACA). Behavioral Risk Factor Surveillance System data were obtained from 2012–2020. The dependent variable asked: “Were you ever denied health insurance or life insurance coverage because of your cancer? ” Cancer survivors were included if they were diagnosed with cancer after the Affordable Care Act (N = 14,815). Unadjusted and adjusted logistic regressions for age, sex, income, and employment provided odds ratios of insurance denial due to cancer across racial/ethnic groups: Non-Hispanic White, Black, and Other/mixed race; and Hispanic. Statistically significant differences (p < 0.05) were found between those who were denied or not denied insurance across sex, age, race/ethnicity, income, and employment. Adjusted regressions found significantly higher odds ratios of insurance denial for Blacks (OR: 3.00, 95% CI: 1.77, 5.08), Other/mixed race (OR: 2.16, 95% CI: 1.16, 4.02), and Hispanics (OR: 2.13, 95% CI: 1.02, 4.42) compared to Whites. Differences were observed across sex, income, and employment. Cancer survivors report racial/ethnic disparities in health and life insurance denial due to their cancer despite policy changes. This may be harmful for those who are already financially vulnerable due to their cancer diagnosis and exacerbate racial/ethnic cancer disparities.
Outcome of Childhood Cerebellar Pilocytic Astrocytoma: A Series With 20 Years of Follow Up

Background: Cerebellar pilocytic astrocytoma (PCA) is one of the few CNS tumors that can be cured with gross-total removal (GTR). In this series, we had 39 patients diagnosed with cerebellar PCA, 27 patients (70%) had GTR, and mean follow-up period was 62 months with no tumor recurrence. Objective: To assess the long-term outcome of childhood cerebellar PCA treated at our institute during the period 2000-2020 and to highlight our surgical protocol. Methodology: Retrospective review of all patients under 18 years of age who were diagnosed with cerebellar PCA and had surgical excision between 2000 and 2020 at the Medical City of King Saud University. Results: The study included 39 patients: 17 males and 22 females, the mean age was 8.4 years. Radiologically, the tumor was solid in eight patients, cystic in 15 patients, and mixed components were found in 16 patients. The lesion was located in the right cerebellar hemisphere in 12 patients, left cerebellar hemisphere in five patients, and midline 22 patients. The tumor size ranged from 2 to 7 cm in its greatest diameter, it was <5 cm in 13 patients and >5 cm in 26 patients. Thirty-one patients had preoperative hydrocephalus. GTR of the tumor was achieved in 27 patients and subtotal resection (STR) was done in 12 patients, 18 patients required permanent ventriculoperitoneal (V-P) shunt, and five patients had postoperative radiotherapy. Postoperative complications included infection in two patients, cerebellar mutism in two patients, and significant neurologic disability in four patients. The duration of follow-up ranged from 0 to 240 months (mean follow-up period: 62.0 months). The outcome at 10 years was good in 30 patients, fair in four patients, poor in four patients, and one patient died. Recurrence was documented in nine patients, seven of them had GTR and two had STR. Conclusion: GTR, if achievable, is curative for childhood cerebellar PCA. Many posterior fossa surgical complications could be avoided with watertight dural closure. Although new dural substitutes are available we prefer using autologous grafts (pericranium). It is easy to harvest pericranial graft from the external ventricular drain (EVD) site. The insertion of EVD synchronously with GTR of the tumor and gradual weaning of EVD could avoid the insertion of V-P shunt.
Optical single-sideband modulation with tunable optical carrier to sideband ratio in radio over fiber systems

Radio over fiber (RoF) has been considered as a promising technology for the distribution of the future high capacity wireless signals such as ultra-wideband and millimeter-wave signals. In RoF systems, optical subcarrier modulation (SCM) is commonly used, such as optical double sideband (ODSB) modulation, and optical single sideband (OSSB) modulation. However, ODSB modulation will introduce RF signal power fading due to the fiber chromatic dispersion. To evade this problem, conventional optical single sideband (OSSB) modulation was proposed and demonstrated. Unfortunately in the conventional OSSB, the modulation efficiency, defined as optical carrier-to-sideband ratio (OCSR) in optical power, is extremely low for small modulation index, i.e. low driven voltage used. On the other hand, when high voltage is applied to the modulator, i.e. high modulation index used, the nonlinear distortion will be induced due to the nonlinearities of the optical modulator response, which will degrade the receiver sensitivity and lead to a poor bit error rate (BER) and spurious free dynamic range (SFDR). Eventually, this will increase RoF system cost and render it impractical. So far, suppressing the OCSR has become a popular way to improve the modulation efficiency. Lots of related techniques have been proposed and demonstrated. The objective of this thesis is to develop a simple modulation technology that OSSB modulation and tunable OCSR are obtained simultaneously only by adjusting the direct current (DC) bias of two parallel non-ideal Mach-Zehnder Modulators (MZMs). In this thesis, the theoretical analyses to prove the functions of this modulation technique are given out first. Then by comparing the theoretical analyses with simulation results, it is found that the results are well matched. Here the impacts of imperfect situations are concerned: bias voltage drift, phase imbalance of the two parallel MZMs, mismatch of splitting and combining coupler's factors, MZM extinction ratio imbalance, inter-modulation distortions (IMDs), high order distortions and chromatic dispersion. The functions and reliability of this modulation technique are deeply discussed. Furthermore, some methods to compensate the impacts due to the non-ideal situations are also considered. Finally, the experimental results are presented to validate the proposed technique
Mobile Applications in Mood Disorders and Mental Health: Systematic Search in Apple App Store and Google Play Store and Review of the Literature

Objectives: The main objective of this work was to explore and characterize the current landscape of mobile applications available to treat mood disorders such as depression, bipolar disorder, and dysthymia. Methods: We developed a tool that makes both the Apple App Store and the Google Play Store searchable using keywords and that facilitates the extraction of basic app information of the search results. All app results were filtered using various inclusion and exclusion criteria. We characterized all resultant applications according to their technical details. Furthermore, we searched for scientific publications on each app’s website and PubMed, to understand whether any of the apps were supported by any type of scientific evidence on their acceptability, validation, use, effectiveness, etc. Results: Thirty apps were identified that fit the inclusion and exclusion criteria. The literature search yielded 27 publications related to the apps. However, these did not exclusively concern mood disorders. 6 were randomized studies and the rest included a protocol, pilot-, feasibility, case-, or qualitative studies, among others. The majority of studies were conducted on relatively small scales and 9 of the 27 studies did not explicitly study the effects of mobile application use on mental wellbeing. Conclusion: While there exists a wealth of mobile applications aimed at the treatment of mental health disorders, including mood disorders, this study showed that only a handful of these are backed by robust scientific evidence. This result uncovers a need for further clinically oriented and systematic validation and testing of such apps.
A Four-Antenna 802.11a Receiver integrated in 0.25 µm SiGe BiCMOS with Spatial Weighting

Abstract This paper presents the design and results of a four-antenna integrated receiver (RX) frontend in 0.25 µm SiGe BiCMOS. It performs antenna combining in the radio-frequency (RF) domain with IEEE 802.11a compliant signals. Therefore, the RF part of this integrated circuit (IC) includes four low noise amplifiers (LNAs), vector modulators (VMs) and a signal combiner. These circuits can weight the incoming C-band (5.6 GHz) signals in their I- and Q-components with an 8-bit resolution before superposition and downcoversion. The baseband (BB) part of the applied zero-IF architecture integrates an 8th order switched-capacitor (SC) filter for channel selection and variable gain amplifiers (VGAs) for automatic gain control (AGC). Together with digital control logic the power consumption amounts to 350 mW at an area requirement of 7.5 mm2.
Can a 280-character message explain stock returns? Evidence from South Africa

PurposeThe authors examine the contemporaneous and causal association between tweet features (bullishness, message volume and investor agreement) and market features (stock returns, trading volume and volatility) using 140 South African companies and a dataset of firm-level Twitter messages extracted from Bloomberg for the period 1 January 2015 to 31 March 2020.Design/methodology/approachPanel regressions with ticker fixed-effects are used to examine the contemporaneous link between tweet features and market features. To examine the link between the magnitude of tweet features and stock market features, the study uses quantile regression.FindingsNo monotonic relationship is found between the magnitude of tweet features and the magnitude of market features. The authors find no evidence that past values of tweet features can predict forthcoming stock returns using daily data while weekly and monthly data shows that past values of tweet features contain useful information that can predict the future values of stock returns.Originality/valueThe study is among the earlier to examine the association between textual sentiment from social media and market features in a South African context. The exploration of the relationship across the distribution of the stock market features gives new insights away from the traditional approaches which investigate the relationship at the mean.
Feature extraction and neural network training for underwater targets

Effective feature extraction is one of the key elements to underwater target recognition. The affine invariants is constructed based on region moments in order to eliminate the negative effects, which are brought by the particularity and complexity of imaging environment. Aiming at the drawbacks of traditional BP neural network, such as converging slowly and tending to get into the local minimizer, the particle swarm algorithm is introduced into the training of neural networks. The affine invariant features of four different objects are extracted and selected as the input of the trained neural network. The experimental results show that the extracted features and the improved neural network can result in fast convergence rate and high accuracy.
Attributed-based Label Propagation Method for Balanced Modularity and Homogeneity Community Detection

Community Detection is an expanding field of interest in many scopes, e.g., social science, bibliometrics, marketing and recommendations, biology etc. Various community detection tools and methods have been proposed in the last years. This research is to develop an improved Label Propagation algorithm (Attribute-Based Label Propagation ABLP) that considers the nodes' attributes to achieve a fair Homogeneity value, while maintaining high Modularity measure. It also formulates an adaptive Homogeneity measure, with penalty and weight modulation, that can be utilized in consonance with the user's requirements. Based on the literature review, a research gap of employing Homogeneity in Community Detection was identified, and accordingly, Homogeneity as a constraint in Modularity based methods is investigated. In addition, a novel dataset constructed on COVID-19 contact tracing in the Kingdom of Bahrain is proposed, to help identify communities of infected persons and study their attributes' values. The implementation of proposed algorithm performed high Modularity and Homogeneity measures compared with other algorithms.
Status and Prospects of Botanical Biopesticides in Europe and Mediterranean Countries

Concerning human and environmental health, safe alternatives to synthetic pesticides are urgently needed. Many of the currently used synthetic pesticides are not authorized for application in organic agriculture. In addition, the developed resistances of various pests against classical pesticides necessitate the urgent demand for efficient and safe products with novel modes of action. Botanical pesticides are assumed to be effective against various crop pests, and they are easily biodegradable and available in high quantities and at a reasonable cost. Many of them may act by diverse yet unexplored mechanisms of action. It is therefore surprising that only few plant species have been developed for commercial usage as biopesticides. This article reviews the status of botanical pesticides, especially in Europe and Mediterranean countries, deepening their active principles and mechanisms of action. Moreover, some constraints and challenges in the development of novel biopesticides are highlighted.
Nonlinear Complementarity Problems for n-Player Strategic Chance-constrained Games

In this paper, we focus on n-player strategic chance-constrained games where the payoff of each player follows either Cauchy or normal distribution. We transform the Nash equilibrium problem into its equivalent nonlinear complementarity problem (NCP) through the Karush-Kuhn-Tucker (KKT) conditions. Then, we prove the existence of the Nash equilibrium by the mean of Brouwer’s fixed-point theorem. In order to show the efficiency of our approach, we perform numerical experiments on a set of randomly generated instances.
Undergraduate employability training and employment: a UAE study

Purpose – The purpose of this paper is to investigate the link between female undergraduate student participation in a university-sponsored employment skills development program and employment post-graduation. Design/methodology/approach – From historical institutional data a random sample was analyzed using the logistic regression model. The main variable investigated was participation in the World of Work (WOW) program during undergraduate study. It was hypothesized that participation would contribute positively to the probability of employment after graduation. Findings – Grade point average at the time of graduation was also expected to have a positive relationship with employability. The study found that those who participated in the WOW program while undergraduates were more 6.7 times more likely to find post-graduate employment than non-participants. Research limitations/implications – Data were collected at a single institution as such findings may not be generalizable. Practical implications – Th.
Visualisasi Data Iris Menggunakan Analisis Komponen Utama dan Analisis Komponen Utama Kernel Visualization of Iris Data Using Principal Component Analysis and Kernel Principal Component Analysis

Principal component analysis (PCA) is a method used to reduce dimentionality of the dataset. However, the use of PCA failed to carry out the problem of non-linear and non-separable data. To overcome this problem such data is more appropriate to use PCA method with the kernel function, which is known as the kernel PCA (KPCA). In this paper, Iris dataset visualized with PCA and KPCA, that contains are the length and the width of sepal and petal.
Hydatidiform Mole Presents As Pregnancy in a 48-Year-Old Perimenopausal Female: A Case Study

Pregnancy should be suspected whenever a woman in her childbearing years misses a menstrual period. Clinical suspicion is increased if she also reports any sexual activity while not using contraception or is inconsistent in her use of contraception. Laboratory findings that aid in the diagnosis of pregnancy include the detection of human chorionic gonadotropin (hCG) in blood or urine. Hydatidiform mole (HM) is part of a group of diseases classified under gestational trophoblastic disease (GTD), which originate in the placenta and have the potential to locally invade the uterus and metastasize. Although molar pregnancies are designated as benign, they have the potential to develop into a malignancy. In this case study, we present a 48-year-old peri-menopausal female patient, with a 1+ year history of irregular menses, who presented to the clinic with signs and symptoms of pregnancy, unprotected sexual activity, and a positive at-home pregnancy test. Upon further workup of the patient, it was diagnosed that the patient had a hydatidiform molar pregnancy. It is interesting to note that benign gestational trophoblastic diseases generally occur in younger women, of “reproductive age” (generally in their twenties to early thirties), and is extremely rare in peri- and post-menopausal women.
Bias Assessment in Medical Imaging Analysis: A Case Study on Retinal OCT Image Classification

Deep learning classifiers can achieve high accuracy in many medical imaging analysis problems. However, when evaluating images from outside the training distribution — e.g., from new patients or generated by different medical equipment — their performance is often hindered, highlighting that they might have learned specific characteristics and biases of the training set and can not generalize to real-world scenarios. In this work, we discuss how Transfer Learning, the standard training technique employed in most visual medical tasks in the literature, coupled with small and poorly collected datasets, can induce the model to capture such biases and data collection artifacts. We use the classification of eye diseases from retinal OCT images as the backdrop for our discussion, evaluating several well-established convolutional neural network architectures for this problem. Our experiments showed that models can achieve high accuracy in this problem, yet when we interpret their decisions and learned features, they often pay attention to regions of the images unrelated to