Miracle-dz/UniFAR-FTUs huggingface dataset:
Iterative Design of L_p Digital Filters

The design of digital filters is a fundamental process in the context of digital signal processing. The purpose of this paper is to study the use of $\lp$ norms (for $2 < p < \infty$) as design criteria for digital filters, and to introduce a set of algorithms for the design of Finite (FIR) and Infinite (IIR) Impulse Response digital filters based on the Iterative Reweighted Least Squares (IRLS) algorithm. The proposed algorithms rely on the idea of breaking the $\lp$ filter design problem into a sequence of approximations rather than solving the original $\lp$ problem directly. It is shown that one can efficiently design filters that arbitrarily approximate a desired $\lp$ solution (for $2 < p < \infty$) including the commonly used $l_\infty$ (or minimax) design problem. A method to design filters with different norms in different bands is presented (allowing the user for better control of the signal and noise behavior per band). Among the main contributions of this work is a method for the design of {\it magnitude} $\lp$ IIR filters. Experimental results show that the algorithms in this work are robust and efficient, improving over traditional off-the-shelf optimization tools. The group of proposed algorithms form a flexible collection that offers robustness and efficiency for a wide variety of digital filter design applications.
An In Silico Analysis of Malaria Pre-Erythrocytic-Stage Antigens Interpreting Worldwide Genetic Data to Suggest Vaccine Candidate Variants and Epitopes

Failure to account for genetic diversity of antigens during vaccine design may lead to vaccine escape. To evaluate the vaccine escape potential of antigens used in vaccines currently in development or clinical testing, we surveyed the genetic diversity, measured population differentiation, and performed in silico prediction and analysis of T-cell epitopes of ten such Plasmodium falciparum pre-erythrocytic-stage antigens using whole-genome sequence data from 1010 field isolates. Of these, 699 were collected in Africa (Burkina Faso, Cameroon, Guinea, Kenya, Malawi, Mali, and Tanzania), 69 in South America (Brazil, Colombia, French Guiana, and Peru), 59 in Oceania (Papua New Guinea), and 183 in Asia (Cambodia, Myanmar, and Thailand). Antigens surveyed include cell-traversal protein for ookinetes and sporozoites, circumsporozoite protein, liver-stage antigens 1 and 3, sporozoite surface proteins P36 and P52, sporozoite asparagine-rich protein-1, sporozoite microneme protein essential for cell traversal-2, and upregulated-in-infectious-sporozoite 3 and 4 proteins. The analyses showed that a limited number of these protein variants, when combined, would be representative of worldwide parasite populations. Moreover, predicted T-cell epitopes were identified that could be further explored for immunogenicity and protective efficacy. Findings can inform the rational design of a multivalent malaria vaccine.
Environmental risk assessment of inter-well partitioning tracer compounds shortlisted for the offshore oil and gas industry

Quantifying residual oil saturation (SOR) in the inter-well region of oil and gas reservoirs is key for successfully implementing EOR solutions. Partitioning inter-well tracer tests (PITTs) has become a common method for quantifying SOR. A new group of seven chemicals – pyridine, 2,3-dimethyl pyrazine, 2,6-dimethyl pyrazine, 4-methoxybenzyl alcohol, 3,4-dimethoxybenzyl alcohol, 4-chlorobenzyl alcohol, and 2,6-dichlorobenzyl alcohol – have been proposed as potential partitioning tracers for quantifying SOR. Using these tracers can lead to their environmental release in the marine environment through produced water discharges, with currently limited knowledge on impacts in the marine ecosystem. The primary objective of the present study is to assess the environmental risk of discharging the tracer compounds in the marine environment. We investigated the fate and effect of these tracers in the marine environment. Biodegradability in seawater was measured to understand the fate of tracers in the marine environment. The acute toxicity of tracers was measured in terms of the percent cell viability of a rainbow trout gill cell line (RTgill-W1) and growth inhibition of the algae Skeletonema costatum. The ecotoxicological information obtained from these experiments was used in the dynamic risk and effects assessment model (DREAM) to calculate the tracers’ contribution to the environmental impact factor (EIF). The results from the DREAM simulations suggest no contribution towards EIF values from any of the tracers at the expected back-produced concentrations. Results from simulations at higher concentrations suggest that both pyrazines have the lowest environmental risk, followed by 3,4-dimethoxybenzyl alcohol, 4-methoxybenzyl alcohol, and pyridine; while both chlorobenzyl alcohols show the highest environmental risk.
Profiles of Sleep Duration and Psychological Distress among Puerto Ricans Living in the United States: A Cross-Sectional Survey and Latent Class Analysis

Sleep duration affects physiological functioning and mental health outcomes among Hispanics/Latinos. The limited research reports that Hispanic/Latino subpopulations like Puerto Ricans carry a disproportionate burden. To understand this burden, we identified profiles of sleep duration by psychological distress among Puerto Rican adults (N = 4443) using latent class analysis on 2010–2019 National Health Interview Survey data. The outcome of sleep was constructed from self-reports of sleep duration and difficulties falling and staying asleep. Sleep duration was categorized as short sleep (≤6 h), normal sleep (7 to 8 h), and long sleep (≥9 h). Mental health indicators included psychological distress items from the Kessler-6 scale. Health behaviors (nicotine and alcohol use), weight (calculated body mass index), food security, acculturative factors (language use), and socio-economic/socio-demographic covariates were considered to further differentiate profiles. Six profiles were identified: troubled shortest sleep (5.0% of sample) with high psychological distress; highly troubled short sleep (8.0%) with little psychological distress; some disturbed and shortened sleep (10.0%) with moderate psychological distress; undisturbed and shortened sleep (28.0%) with little psychological distress; normal/average sleep (49.0%); and long sleep (1.0%) with moderate psychological distress. While our study is among the first to identify profiles that are at the highest mental health risk due to sleep issues, the findings and approach help examine the complex disparity among Puerto Ricans to then leverage complex survey data for interventional designs.
Embracing mobile shopping: what matters most in the midst of a pandemic?

PurposeThe COVID-19 pandemic has brought about significant changes to the lives of many people. One of which is the accelerated digitalization in the commerce sector. Hence, this study looks to determine the antecedents that affect users' mobile shopping actual use during a pandemic.Design/methodology/approachThe research model was founded on the integration of the Protection Motivation Theory and Transactional Theory of Stress. This is in addition to further extending the integrated research model with other constructs to develop a multi-dimensional framework that accounted for the health, personal, technological and social dimensions. The data was collected from users of mobile shopping through an online survey which was then analyzed via Partial Least Squares–Structural Equation Modeling.FindingsThis study provides empirical support to establish the major role of COVID-19 pandemic in affecting the actual usage of mobile shopping. Furthermore, the determinants of actual usage of mobile shopping were found to be multi-dimensional. In particular, the Importance-Performance Map Analysis revealed that emphasis should be place on perceived vulnerability.Originality/valueAs other studies focused on users' intentions, this study looked into the factors that influence the actual usage of mobile shopping. Furthermore, this study emphasizes on the contextualization of time and situation in addition to a multi-dimensional approach toward the subject matter. Overall, this study offers practical insights to stakeholders to better tailor their mobile shopping services in times of a pandemic and advances the literature on actual usage of mobile shopping.
Extraction and characterization of cellulase from forest and compost soil fungal isolates for the application of straw degradation

Cellulases are complex hydrolytic enzymes working synergistically on the hydrolysis of cellulolytic materials for the production of simple sugars. These enzymes have tremendous environmental, industrial and agricultural applications including enhancement of the degradability of lignocellulosic materials for cattle’s feed. The aim of this study was to isolate fungus and extract cellulose enzyme from forest and compost soil samples and examine the extent to which these enzymes enhance the degradability of finger millet and oat straw for making palatable cattle’s feed. Accordingly, a total of 53 fungal isolates were isolated from forest and compost soil. On 1% CMC media resulted 40% were cellulolytic fungal species. Six were selected based on their clear zone. These isolates belonged to the genera Trichoderma, Aspergillus and Penicillium based on their morphological characteristics. Cultivation of fungal isolates for cellulase production using submerged fermentation and Solid-state fermentation was undertaken through make the variation on their levels of different growth conditions such as temperature, pH, minerals and substrates. The results showed that the highest cellulase production i.e CMCase 83.12 ± 3.18 U/dL and FPase 44.51± 0.391FPU/dL were obtained from FSI6 in FMS supplemented SSF at 280C and a pH of 6.
Use of Digital Tachograph Data to Provide Traffic Safety Education and Evaluate Effects on Bus Driver Behavior

Traffic safety education was conducted with data from a vehicle-mounted digital tachograph device to promote bus driver awareness of safe driving behavior. The objectives were to evaluate the duration of the effects of traffic safety education on abnormal driving behaviors and to identify the differences in education effects between two driver groups: normal and dangerous. A 9-week tracing survey was conducted for 61 bus drivers. Traffic safety education was administered to individual drivers according to their daily driving behaviors. For analysis, a survival model was used to identify the effects of traffic safety education on abnormal driving behaviors. The two main results follow: (a) the effects of safety education decreased more quickly on acceleration-related abnormal driving behaviors than on steering- and deceleration-related abnormal driving behaviors and implied that more concentrated education is required for acceleration-related behaviors and (b) the education effects for the dangerous group lasted longer than for the normal group and implied that abnormal driving behaviors could be reduced if safety education were tailored to the dangerous group. Specialized traffic safety education that reflects individual driving behaviors is recommended for bus drivers, along with periodic traffic safety education to prevent a recurrence (yo-yo effect) in the increased frequency of abnormal driving behaviors.
Physical Rehabilitation Programs for Bedridden Patients with Prolonged Immobility: A Scoping Review

Bedridden patients usually stay in bed for long periods, presenting several problems caused by immobility, leading to a long recovery process. Thus, identifying physical rehabilitation programs for bedridden patients with prolonged immobility requires urgent research. Therefore, this scoping review aimed to map existing physical rehabilitation programs for bedridden patients with prolonged immobility, the rehabilitation domains, the devices used, the parameters accessed, and the context in which these programs were performed. This scoping review, guided by the Joanna Briggs Institute’s (JBI) methodology and conducted in different databases (including grey literature), identified 475 articles, of which 27 were included in this review. The observed contexts included research institutes, hospitals, rehabilitation units, nursing homes, long-term units, and palliative care units. Most of the programs were directed to the musculoskeletal domain, predominantly toward the lower limbs. The devices used included lower limb mobilization, electrical stimulation, inclined planes, and cycle ergometers. Most of the evaluated parameters were musculoskeletal, cardiorespiratory, or vital signs. The variability of the programs, domains, devices and parameters found in this scoping review revealed no uniformity, a consequence of the personalization and individualization of care, which makes the development of a standard intervention program challenging.
Phytochemical profile and biological effects of essential oils from three Inula species grown in Tunisia

ABSTRACT This work investigated the chemical composition of essential oils (EOs) obtained from the aerial parts of three Inula species of the Tunisian flora as well as their biological properties. Inula viscosa essential oil (IVEO) contained mainly α-costic acid (65.4%). The EOs of Inula graveolens (IGEO) and Inula crithmoides (ICEO) were characterized by high contents of p-cymene derivatives while ICEO stands out by high levels of modheph-2-ene (16.5%) and tiglic esters (14.1%). Moreover, a notable antioxidant power was proved by the ORAC test for the three EOs. Finally, the cytotoxic activity was evaluated on two healthy cell lines (CCD45-SK, HUVECs) and two cancer cell lines (HepG-2, MCF-7) and it appeared that the EOs were particularly effective on MCF-7 human breast cancer cells with LC50 equal to 79, 16, and 63 µg. mL−1 for IVEO, IGEO, and ICEO, respectively.
Global total ozone recovery trends attributed to ozone-depleting substance (ODS) changes derived from five merged ozone datasets

Abstract. We report on updated trends using different merged zonal mean total ozone datasets from satellite and ground-based observations for the period from 1979 to 2020. This work is an update of the trends reported in Weber et al. (2018) using the same datasets up to 2016. Merged datasets used in this study include NASA MOD v8.7 and NOAA Cohesive Data (COH) v8.6, both based on data from the series of Solar Backscatter Ultraviolet (SBUV), SBUV-2, and Ozone Mapping and Profiler Suite (OMPS) satellite instruments (1978–present), as well as the Global Ozone Monitoring Experiment (GOME)-type Total Ozone – Essential Climate Variable (GTO-ECV) and GOME-SCIAMACHY-GOME-2 (GSG) merged datasets (both 1995–present), mainly comprising satellite data from GOME, SCIAMACHY, OMI, GOME-2A, GOME-2B, and TROPOMI. The fifth dataset consists of the annual mean zonal mean data from ground-based measurements collected at the World Ozone and Ultraviolet Radiation Data Centre (WOUDC). Trends were determined by applying a multiple linear regression (MLR) to annual mean zonal mean data. The addition of 4 more years consolidated the fact that total ozone is indeed slowly recovering in both hemispheres as a result of phasing out ozone-depleting substances (ODSs) as mandated by the Montreal Protocol. The near-global (60∘ S–60∘ N) ODS-related ozone trend of the median of all datasets after 1995 was 0.4 ± 0.2 (2σ) %/decade, which is roughly a third of the decreasing rate of 1.5 ± 0.6 %/decade from 1978 until 1995. The ratio of decline and increase is nearly identical to that of the EESC (equivalent effective stratospheric chlorine or stratospheric halogen) change rates before and after 1995, confirming the success of the Montreal Protocol. The observed total ozone time series are also in very good agreement with the median of 17 chemistry climate models from CCMI-1 (Chemistry-Climate Model Initiative Phase 1) with current ODS and GHG (greenhouse gas) scenarios (REF-C2 scenario). The positive ODS-related trends in the Northern Hemisphere (NH) after 1995 are only obtained with a sufficient number of terms in the MLR accounting properly for dynamical ozone changes (Brewer–Dobson circulation, Arctic Oscillation (AO), and Antarctic Oscillation (AAO)). A standard MLR (limited to solar, Quasi-Biennial Oscillation (QBO), volcanic, and El Niño–Southern Oscillation (ENSO)) leads to zero trends, showing that the small positive ODS-related trends have been balanced by negative trend contributions from atmospheric dynamics, resulting in nearly constant total ozone levels since 2000.
Performance of a Rotational Sensor to Decipher Volcano Seismic Signals on Etna, Italy

Volcano‐seismic signals such as long‐period events and tremor are important indicators for volcanic activity and unrest. However, their wavefield is complex and characterization and location using traditional seismological instrumentation is often difficult. In 2019 we recorded the full seismic wavefield using a newly developed 3C rotational sensor co‐located with a 3C traditional seismometer on Etna, Italy. We compare the performance of the rotational sensor, the seismometer and the Istituto Nazionale di Geofisica e Vulcanologia‐Osservatorio Etneo (INGV‐OE) seismic network with respect to the analysis of complex volcano‐seismic signals. We create event catalogs for volcano‐tectonic (VT) and long‐period (LP) events combining a STA/LTA algorithm and cross‐correlations. The event detection based on the rotational sensor is as reliable as the seismometer‐based detection. The LP events are dominated by SH‐type waves. Derived SH phase velocities range from 500 to 1,000 m/s for LP events and 300–400 m/s for volcanic tremor. SH‐waves compose the tremor during weak volcanic activity and SH‐ and SV‐waves during sustained strombolian activity. We derive back azimuths using (a) horizontal rotational components and (b) vertical rotation rate and transverse acceleration. The estimated back azimuths are consistent with the INGV‐OE event location for (a) VT events with an epicentral distance larger than 3 km and some closer events, (b) LP events and tremor in the main crater area. Measuring the full wavefield we can reliably analyze the back azimuths, phase velocities and wavefield composition for VT, LP events and tremor in regions that are difficult to access such as volcanoes.
The “Loss” of Perineuronal Nets in Alzheimer's Disease: Missing or Hiding in Plain Sight?

Perineuronal nets (PNNs) are chondroitin-sulfate glycosaminoglycan (CS-GAG) containing extracellular matrix structures that assemble around neurons involved in learning, memory, and cognition. Owing to the unique patterning of negative charges stemming from sulfate modifications to the attached CS-GAGs, these matrices play key roles in mediating glycan-protein binding, signaling interactions, and charged ion buffering of the underlying circuitry. Histochemical loss of PNN matrices has been reported for a range of neurocognitive and neurodegenerative diseases, implying that PNNs might be a key player in the pathogenesis of neurological disorders. In this hypothesis and theory article, we begin by highlighting PNN changes observed in human postmortem brain tissue associated with Alzheimer's disease (AD) and corresponding changes reported in rodent models of AD neuropathology. We then discuss the technical limitations surrounding traditional methods for PNN analyses and propose alternative explanations to these historical findings. Lastly, we embark on a global re-evaluation of the interpretations for PNN changes across brain regions, across species, and in relation to other neurocognitive disorders.
Application of Tree-Based Ensemble Models to Landslide Susceptibility Mapping: A Comparative Study

Ensemble machine learning methods have been widely used for modeling landslide susceptibility, but there has been no uniform ensemble method for this problem. The main objective of this study is to compare popular ensemble machine learning-based models and apply them to landslides susceptibility mapping. The selected models include the random forest (RF), which is a typical bagging ensemble model, and three advanced boosting models, namely, adaptive boosting (AB), gradient boosting decision trees (GBDT), and extreme gradient boosting (XGBoost). This study considers 94 landslide points and 12 affecting factors. The data are divided into a training dataset consisting of 70% of the overall data, and a validation dataset, containing the remaining 30% of the data. The models are evaluated using the area under the receiver operating characteristic curve (AUC) and three common performance metrics: sensitivity, specificity, and accuracy. The results indicate that the four ensemble models have an AUC of more than 0.8, suggesting that they can appropriately and accurately predict landslide susceptibility maps. In particular, the XGBoost model achieves the best performance among all models, having a sensitivity of 92.86, specificity of 90.00, and accuracy of 91.38. Furthermore, the bagging model has a sensitivity of 89.29, specificity of 86.67, and accuracy of 87.93, and it is superior to the GBDT, which achieves a sensitivity of 86.21, specificity of 86.21, and accuracy of 86.21, and the AB, reaching a sensitivity of 82.14, specificity of 80.00, and accuracy of 81.03. The results presented in this study indicate that the advanced ensemble model, the XGBoost model, could be a promising tool for the selection of ensemble models for predicting landslide susceptibility mapping.
LiNbO3 High Speed Travelling Wave Electro-Optic Waveguide Devices

The fabrication of LiNbO3 travelling wave electrodes is described. It is shown that devices with plasma etched Al electrodes can perform as well as devices employing the more conventional electro-plated Au technology and that bandwidths in excess of 12 GHz can readily be achieved. The reliability of travelling wave devices with plasma etched Al electrodes is considered and it is shown that metallisation lifetimes in excess of 16 years are currently predicted. The problems of using LiNb03 travelling wave devices in practical optical fibre systems are reviewed and it is shown that the use of a dedicated high speed drive amplifier can result in considerable simplification. The design and fabrication of such an amplifier based on GaAs technology is described and its use in a 1.8 Gbit s-1 optical fibre system reported.
La simulación como herramienta de diseño y evaluación arquitectónica. Pautas resueltas desde la ingeniería

Se presenta un panorama sobre la importancia del proceso de diseno sostenible aplicado a las edificaciones. Teniendo en cuenta que el sector de la construccion es una de las areas de mas alto impacto ambiental, es importante analizar cuales serian los nuevos procesos de diseno de las edificaciones en terminos de sostenibilidad. Estos conceptos se aplicaron a un estudio de caso por medio de la simulacion discreta, la cual permite una evaluacion de la capacidad en un edificio junto con sus recursos, a fin de tomar decisiones de ampliacion en el proceso de diseno arquitectonico. Los datos se analizaron en el programa estadistico SPSS y se simularon en ProModel. El modelo pedagogico propuesto puede llegar a ser de utilidad al momento de aplicarse en un contexto multidisciplinar, en donde interactuen estudiantes de ingenieria industrial y arquitectura. Este ejercicio puede aplicarse en las aulas de clase; con el se reducirian los tiempos de diseno, y la comunicacion entre estudiantes mejoraria porque implica el trabajo multidisciplinar.
The hidden compliance zone of fiscal rules

ABSTRACT This paper studies fiscal rule compliance under uncertainty and irreversibility. I show that a broad class of fiscal rule designs contain a state space in which the government optimally complies with the rule in place, a compliance zone. Outside the compliance zone, the government exerts control on the path committed by the rule. I also show that the size of the rule’s compliance zone depends on two elements: first, how the rule copes with the uncertainty regarding the macro variable that underlies it; and second, how the fiscal spending path committed by the rule accommodates the demand for public goods.