Miracle-dz/UniFAR-FTUs huggingface dataset:
Primary Angiitis of the Central Nervous System – Diagnosis and Management

Primary angiitis of central nervous system (PACNS) is a rare idiopathic disorder affecting blood vessels of brain, spinal cord, and meninges, consequently leading to infarct and less frequently hemorrhage. CNS vasculitis can also occur as part of systemic vasculitis or secondary to autoimmune diseases or infections. The clinical manifestations of PACNS are non-specific and no single laboratory investigation or neuroimaging finding can reliably diagnose this condition. Histopathological evidence of transmural inflammation of blood vessels of CNS is the gold standard, but is generally pursued subsequent to conventional angiogram (CA) because of its invasive nature. The differentials of PACNS are exhaustive and include systemic vasculitis, secondary vasculitis, non-inflammatory intracranial vasculopathies, demyelination, and neoplasm. These alternative conditions can often be distinguished by history, examination, immunological testing, cerebrospinal fluid analysis, and neuroimaging. CA can detect vasculitic changes in the large to medium cerebral arteries but the specificity is low. Recent advancements in vessel wall imaging techniques have further enabled the distinction of various intracranial vasculopathies from CNS vasculitis. The disease has considerable morbidity and fatality unless timely treatment with immunosuppressive agents is initiated. Induction therapy with glucocorticoids and cyclophosphamide followed by azathioprine, mycophenolate mofetil, or methotrexate as maintenance therapy is the cornerstone of management. Biological agents such as rituximab and anti-tumour necrosis factor alpha inhibitors (infliximab and etanercept) may be used in refractory cases. This review discusses the approach to the diagnosis, determinants of outcome, and management.
Incident Atrial Fibrillation and In-Hospital Mortality in SARS-CoV-2 Patients

(1) Background: Among the different cardiovascular (CV) manifestations of the coronavirus disease 2019 (COVID-19), arrhythmia and atrial fibrillation (AF) in particular have recently received special attention. The aims of our study were to estimate the incidence of AF in patients hospitalized for COVID-19, and to evaluate its role as a possible predictor of in-hospital all-cause mortality. (2) Methods: We enrolled 3435 people with SARS-CoV2 infection admitted to three hospitals in Northern Italy from February 2020 to May 2021. We collected data on their clinical history, laboratory tests, pharmacological treatment and intensive care unit (ICU) admission. Incident AF and all-cause in-hospital mortality were considered as outcomes. (3) Results: 145 (4.2%) patients developed AF during hospitalization, with a median time since admission of 3 days (I-III quartile: 0, 12). Patients with incident AF were admitted more frequently to the ICU (39.3 vs. 12.4%, p < 0.001), and more frequently died (37.2 vs. 16.9%, p < 0.001). In the Cox regression model, the significant determinants of incident AF were age (HR: 1.041; 95% CI: 1.022, 1.060 per year), a history of AF (HR: 2.720; 95% CI: 1.508, 4.907), lymphocyte count (HR: 0.584; 95% CI: 0.384, 0.888 per 103/µL), estimated glomerular filtration rate (eGFR, HR: 0.988; 95% CI: 0.980, 0.996 per mL/min) and ICU admission (HR: 5.311; 95% CI: 3.397, 8.302). Incident AF was a predictor of all-cause mortality (HR: 1.405; 95% CI: 1.027, 1.992) along with age (HR: 1.057; 95% CI: 1.047, 1.067), male gender (HR: 1.315; 95% CI: 1.064; 1.626), dementia (HR: 1.373; 95% CI: 1.045, 1.803), lower platelet (HR: 0.997; 95% CI: 0.996, 0.998 per 103/µL) and lymphocyte counts (HR: 0.843; 95% CI: 0.725, 0.982 per 103/µL), C-Reactive protein values (HR: 1.004; 95% CI: 1.003, 1.005 per mg/L), eGFR (HR: 0.990; 95% CI: 0.986, 0.994 per mL/min), and ICU admission (HR: 1.759; 95% CI: 1.292, 2.395). (4) Conclusions: Incident AF is a common complication in COVID-19 patients during hospitalization, and its occurrence strongly predicts in-hospital mortality.
Review of nano piezoelectric devices in biomedicine applications

The piezoelectric devices, based on micro–nano electromechanical systems, are well known nowadays due to their small features, ability for integration with the integrated circuit in a single platform, robust, and easily fabricated in bulk. The enhanced performance of piezoelectric systems, which is soft, flexible, and stretchable made them have unique opportunities to be used in bio-integrated applications as nanodevices for energy harvesting, sensing, actuation, and cell stimulation. The selection of optimized configurations depends on thin geometries, neutral mechanical plane construction, and controlled buckling, while inorganic piezoelectric materials are preferred for interfaces with human bodies. The key considerations in designs, the analytical derivations for voltage and displacement, and the effect of the voltmeter resistance on the voltage measurements are presented. Devices for energy harvesting from natural motions of internal organs, sensors, and actuators for medical applications are reviewed. The PMN-PT energy harvester that produced current of 0.22 mA is higher than the rest of the discussed harvesters. Thus, it is more suitable to be used as a sufficient source of energy in biomedical applications. The use of piezoelectric nanowires and ribbons proved successful, and the dual features of device (sensor and actuator) seem advantageous.
Building the Next Generation of Smart BMPs: Media Enhancements for Phosphorus Removal

The science and practice of stormwater management to improve best management practices to protect and restore water resources is an ongoing field of study. Innovation to develop smart BMPs is an essential component of stormwater management given the high cost of retrofitting urban areas and required pollutant load reductions to meet TMDLs and other local program goals. The focus of this paper is a review of the use of media additives to enhance the phosphorus (P) removal from BMPs and to identify information needs to move this innovation from research to practical application. A review of different types of additives and their pollutant removal capabilities is described along with information needs to move this smart BMP from research into practice.
Alcohol Use, Trait Anger, and Intimate Partner Violence in College Alcohol Use, Trait Anger, and Intimate Partner Violence in College Student Couples Student Couples

Intimate Partner Violence (IPV) is a significant public health problem, and risk for IPV is often highest among young adults. Numerous studies have found alcohol use to temporally precede and increase the risk for IPV perpetration. Trait anger is also associated with greater levels of physical, sexual, and psychological IPV perpetration. Daily diary research using one member of the dyad has found that alcohol is associated with increased physical IPV perpetration among men high, but not low, in levels of trait anger. However, IPV is a dyadic process that is impacted by the behavior of both partners, and little is known about whether alcohol use and trait anger may interact to predict IPV in couples. The present thesis utilized a sample of 181 couples between the ages of 18-25 years old to examine alcohol use/problems and trait anger as predictors of physical, sexual, and psychological IPV perpetration. Data were analyzed using an Actor-Partner Interdependence (APIM) framework, allowing for both actor and partner effects to be examined. Results indicated that actor trait anger was associated with increased levels of psychological IPV perpetration ( B = 1.25, p < .001). Both actor alcohol use/problems (ERR = 1.08, 95% CI = 1.01 – 1.16) and actor trait anger (ERR = 1.10, 95% CI = 1.02, 1.17) were associated with increased physical IPV perpetration. A significant interaction ( p < .001) between partner alcohol use/problems and partner trait anger predicting sexual IPV perpetration indicated that at high levels of partner trait anger, partner alcohol use/problems were associated with lower
ON THE IMPORTANCE OF DIFFERENT COMPONENTS IN A MULTICOMPONENT SYSTEM

Abstract : In a system whose functioning or failure depends on the functioning or failure of its components, some components may play a more important part than others. A quantitative definition of this notion of importance is proposed in the present paper for systems with coherent structures, assuming (1) that only the structure of the system is known, or (2) that also the reliabilities of all components are known. Some theoretical properties of the so defined concepts are discussed, and applications are presented to such problems as allocation of spare parts or appropriation of funds for improvement of component reliability.
Revisiting the Trade Restrictions-Industrialization Nexus in Developing Countries: The Case of Log Export Ban and Wood Processing

Many developing countries impose restrictions on the export of logs primarily to promote local wood processing. This study focuses on the Log Export Ban (LEB) policy and investigates if this policy impacts both the production and exports of two processed wood, i.e., sawnwood (ﬁrst stage of processing) and veneer (second stage of processing). We implement the propensity score matching method to assess the average treatment eﬀect on the treated (ATT) of the LEB policy in 101 developing countries. We ﬁnd a positive and signiﬁcant eﬀect of the LEB policy on both sawnwood and veneer production while the eﬀect is stronger in the case of sawnwood (about 4 percents) compared to veneer (about 1 percent). Moreover, we also ﬁnd a positive and signiﬁcant eﬀect on the exports of sawnwood (around 10 percents) while we do not ﬁnd any signiﬁcant results on the exports of veneer. In addition, we investigate the heterogeneity in treatment eﬀects using control function with some institutional variables such as the level of corruption, the quality of law and order as well as the bureaucracy quality. The results found are comparable to the ATTs results. Also, to avoid endogeneity issue, we apply the two-step GMM estimation model that conﬁrms the ATTs results. Taking together, these results suggest than the LEB policy has mainly contributed to improve the ﬁrst stage of wood processing rather than the second stage.
Running head: ME AGAINST MYSELF

Two studies investigated adult age differences in the frequency and emotional consequences of motivational conflicts (i.e., feeling that one wants to or should do something else in a given situation). Study 1 compared younger and older adults. Study 2 included a more ageheterogeneous sample ranging from 20 to 70 years. Data were obtained using diary and experience-sampling methods. Multilevel regression showed that motivational conflict was associated with lower emotional well-being. With age, the frequency of motivational conflict decreased, while emotional well-being increased. Importantly, the age-related decrease in motivational conflicts partly accounted for the age-related increase in emotional well-being. Findings were consistent across studies and robust after controlling for age differences in a number of control variables including time use. We conclude that an age-related decrease in motivational conflicts in daily life may be among the factors underlying the positive development of emotional well-being into older adulthood.
Efficacy of traditional chinese medicine Magnolia bark (Magnolol and Honokiol extract) on dental caries and gingivitis: a systematic review

: Background: Magnolia bark is a traditional Chinese medicine that was originated thousands of years back. It received scientific attention as an anti-inflammatory effect used in Gingivitis and dental caries. Aim: To evaluate the efficacy of Magnolia bark extract on Gingivitis and dental caries. Methods: A literature review was performed using Pub Med, science direct, Medline, Cochrane, Scopus using keywords Magnolia bark, Gingivitis, dental caries and dental plaque. A total of 184 articles were from various sources; 6 articles were related to research topics. According to PRISMA guidelines, the review is reported. Results and Conclusion: Magnolia bark effectively against the bacteria that cause dental .
Characterization of Acrocarpus fraxinifolius wood submitted to heat treatment

Aiming to provide greater visibility for the wood species Acrocarpus fraxinifolius , the present study sought to analyze the influence of heat treatment on an industrial scale applied to wood species, also popularly known as Indian cedar. The heat treatment was carried out in an autoclave, with temperature and pressure control, and with saturated steam injection, for temperatures 155 ºC, 165 ºC, 175 ºC, and 185 ºC. Physical, chemical, and mechanical tests were carried out for the analyzed wood. The content of holocellulose and total lignin decreased, while the content of extractives showed a substantial increase. The density increased after the heat treatment, however the treated wood showed cracks, and these cracks influenced the significant loss of the values of the mechanical properties of compression, tension, and flexion. The shear showed strength gain for the temperature of 155 ºC, and the wood treated at 165 ºC was equivalent to untreated wood. The woods submitted to temperatures of 175 ºC and 185 ºC presented strength losses. The heat treatment in question con-tributes to increase the visibility, use and market value of wood.
Artefact Classi�cation: A Deep Learning Approach to Fight Illicit Tra�cking of Antiquities

We approach the task of detecting the illicit movement of cultural heritage from a machine learning perspective by presenting a framework for detecting a known artefact in a new and unseen image. To this end, we explore the machine learning problem of instance classiﬁcation for large archaeological images datasets, i.e. where each individual object (instance) is itself a class that all of the multiple images of that object belongs. We focus on a wide variety of objects in the Durham Oriental Museum with which we build a dataset with over 24,502 images of 4,332 unique object instances. We experiment with state-of-the-art convolutional neural network models, the smaller variations of which are suitable for deployment on mobile applications. We ﬁnd the exact object instance of a given image can be predicted from among 4,332 others with ∼ 72% accuracy, showing how effectively machine learning can detect a known object from a new image. We demonstrate that accuracy signiﬁcantly improves as the number of images-per-object instance increases (up to ∼ 83%), with an ensemble of classiﬁers scoring as high as 84%. We ﬁnd that the correct instance is found in the top 3, 5, or 10 predictions of our best models ∼ 91%, ∼ 93%, or ∼ 95% of the time respectively. Our ﬁndings contribute to the emerging overlap of machine learning and cultural heritage, and highlights the potential available to future applications and research.
Cloud to IDA: Efficient fragility assessment with limited scaling

Incremental dynamic analysis (IDA) leads to curves expressed in terms of structural response versus intensity, commonly known as the IDA curves. It is known that implementation of IDA usually involves significant computational effort and most often significant scaling of the original records to various intensity levels. Employing as the performance variable the critical demand to capacity ratio (DCR) throughout the structure, which is equal to unity at the onset of the limit state, facilitates the identification of the intensity values at the onset of a desired limit state and hence the implementation of the IDA procedure. Employing the structural response to un‐scaled records and the corresponding regression‐based response predictions (a.k.a., the “Cloud Analysis”) helps in identifying the range of intensity values corresponding to demand to capacity ratio values in the vicinity of unity. The Cloud to IDA procedure for structural fragility assessment is proposed on the premise of exploiting the Cloud Analysis results to obtain the IDA curves both with minimum number of analyses and minimum amount of scaling. The transverse frame of a shear‐critical 7‐story older RC building in Van Nuys, CA, which is modeled in Opensees with fiber‐section considering the flexural‐shear‐axial interactions and the bar slip, is employed as a case study. It is demonstrated, by comparing the results to IDA and other state of the art non‐linear dynamic procedures based on no scaling or spectral‐shape‐compatible scaling, that the Cloud to IDA procedure leads to reliable results in terms of structural fragility and risk for the prescribed limit state.
Evaluating the Implementation and Adoption Potential of a Saliva-based Malaria Detection Technique in the Democratic Republic of the Congo

John Diaz (  john.diaz@u .edu ) University of Florida Cody Gusto University of Florida Kaci McCoy University of Florida Colby Silvert University of Florida Joseph A. Bala Kinshasa School of Public Health, Democratic Republic of the Congo Joseph Atibu Kinshasa School of Public Health, Democratic Republic of the Congo Antoinette Tshefu Kinshasa School of Public Health, Democratic Republic of the Congo Melchior Mwandagalirwa Kinshasa School of Public Health, Democratic Republic of the Congo Rhoel R. Dinglasan University of Florida
Design, characterization and preliminary usability testing of a portable robot for unsupervised therapy of hand function

Introduction: There is evidence that increasing therapy dose after stroke might promote recovery. Unfortunately, in clinical practice, therapy dose is limited by financial and organizational constraints. Simple robotic devices could be used without supervision in the clinic or at home to increase dose without requiring additional resources. For this purpose, we developed HandyBot, a portable three-degrees-of-freedom end-effector haptic device to perform sensorimotor task-oriented therapy of hand function (i.e., grasping, forearm pronosupination, wrist flexion-extension) in different environments. Methods: We present the mechatronic design of the device and its technical evaluation in terms of workspace, dynamics (i.e., max end-effector velocity, acceleration and force), sensing (i.e., position, velocity and force resolution) and haptic performance (i.e., transparency, maximum stable impedance range, rigid contact rendering accuracy). In addition, its feasibility and usability (in terms of System Usability Scale (SUS)) were assessed in a single-session experiment with four subjects with chronic stroke that tested the HandyBot therapy platform (i.e., haptic device with a graphical/physical user interface and a set of therapy exercises) while simulating unsupervised use (i.e., the subject used the device independently while a therapist was only observing the session). Results: HandyBot showed hardware and control performances comparable to other less portable therapy devices for hand function (e.g., 94% accuracy in stiffness rendering, low apparent mass of 0.2 kg in transparency mode), making it a suitable platform for the implementation of sensorimotor therapy exercises. HandyBot showed good platform usability in terms of SUS (i.e., above 75 out of 100 for device and graphical user interfaces, above 65 out of 100 for the exercises) when tested in simulated unsupervised settings. These tests underlined minor design improvements that should be considered to allow using such a device in uncontrolled settings. Discussion: HandyBot is a novel robot for hand rehabilitation after stroke that revealed high-quality hardware and haptic performance. HandyBot was usable for stroke patients at first exposure for (simulated) unsupervised robot-assisted sensorimotor therapy of hand function. This therapy approach combined with this novel portable robotic device has the potential to help increase therapy dose and decrease therapy-associated costs (e.g., therapist time to therapy time ratio) in different environments.
Digital finance, development, and climate change1

Sub-Saharan African (SSA) countries are increasingly adopting digital finance, which generally represents a positive driver of development and growth. However, the digital finance sector is known to be a source of large CO2 emissions, thereby contributing to climate change, and SSA countries will likely be the ones that suffer most from climate change. This constitutes a negative channel through which digital finance could impair development. This article aims to disentangle these two channels to assess which effect prevails overall. We analyse the impact of mobile money and bitcoin on the Human Development Index (HDI). We find that mobile money mitigates the negative impact of CO2 emissions. Globally, through its interaction with CO2 emissions, mobile money has a positive impact on development. In contrast, we find weak evidence concerning bitcoin. On its own, bitcoin has a negative impact on HDI. JEL Classification: Q43; Q54; G23; E42; O14; O16; O55
Single-phase multilevel inverter topologies with self-voltage balancing capabilities

In this study, two new structures of single-phase hybrid multilevel inverter are proposed for both symmetrical and asymmetrical configurations that can be employed in drives and control of electrical machines and connection of renewable energy sources. The proposed configuration uses a less number of semiconductor devices and DC sources as compared with conventional and newly developed topologies which lead to a reduction in cost and installation area. The proposed topology poses a vital advantage of self-voltage balancing of its capacitor voltage regardless of load type, load dynamics and modulation index. Also, the proposed topology is expanded in a cascaded fashion which reduces the complexity and improves the performance significantly. A wide range of comparison is done with conventional and newly developed topologies to show the superior performance of proposed topologies regarding a total number of switches and DC sources. The multi-carrier pulse-width modulation strategy is adopted for generating switching pulses for respective switches. A laboratory prototype is developed for testing the performance of the proposed topology for 9-level and 17-level inverters.
Impact of mineral discoveries and productions on educational Intergenerational Mobility in Africa

We study the potential role of mineral discoveries and productions on educational intergenerational mobility for more than 14 million individuals across 28 African countries and 2,890 districts. We find that mineral discoveries and productions positively affect educational IM for primary education in Africa for individuals exposed to the mineral sites and living in districts with discoveries. Specifically, upward primary IM increases by 2.7 percent following mineral discoveries and 6.7 percent following mineral productions. Downward primary IM decreases by 1.2 percent following both mineral discoveries and productions. However, no significant effects are found for secondary and tertiary educational IM. We also unveil four transmission channels through which the positive effects of mineral discoveries and productions on educational primary IM operate, including the income effect proxied by parents working in the mining sector, the structural transformation of the local economy, the returns to education, and the provision of infrastructures.