Miracle-dz/UniFAR-FTUs huggingface dataset:
From Biomarkers to the Molecular Mechanism of Preeclampsia—A Comprehensive Literature Review

Preeclampsia (PE) is a prevalent obstetric illness affecting pregnant women worldwide. This comprehensive literature review aims to examine the role of biomarkers and understand the molecular mechanisms underlying PE. The review encompasses studies on biomarkers for predicting, diagnosing, and monitoring PE, focusing on their molecular mechanisms in maternal blood or urine samples. Past research has advanced our understanding of PE pathogenesis, but the etiology remains unclear. Biomarkers such as PlGF, sFlt-1, PP-13, and PAPP-A have shown promise in risk classification and preventive measures, although challenges exist, including low detection rates and discrepancies in predicting different PE subtypes. Future perspectives highlight the importance of larger prospective studies to explore predictive biomarkers and their molecular mechanisms, improving screening efficacy and distinguishing between early-onset and late-onset PE. Biomarker assessments offer reliable and cost-effective screening methods for early detection, prognosis, and monitoring of PE. Early identification of high-risk women enables timely intervention, preventing adverse outcomes. Further research is needed to validate and optimize biomarker models for accurate prediction and diagnosis, ultimately improving maternal and fetal health outcomes.
Prioritization of the key underlying sustainability indicators of urban green drainage infrastructure systems

ABSTRACT Assessments of urban green drainage infrastructure (UGDI) have always been a headache in contemporary times which is a roadblock to enticing investors. This study prioritized the underlying sustainability indicators of UGDI systems in Ghana. After an exhaustive literature review, some identified sustainability indicators were compounded into semi-structured questionnaires. Sixty-two built environment professionals were asked to rate the significance of each indicator. A parametric test was used to prioritize the indicators. The results indicated that the most significant underlying sustainability indicators were; ‘Flood control’, ‘Compliance with sustainable development goals’, ‘multi-functionality’, ‘energy efficiency and GHG emissions’ and ‘Initial Construction Cost’. To understand how UGDI performs with regards to flood and pollution mitigation, specific geographical performance indicators are required. This is an under-explored area in the Ghanaian context. Hence, the indicators espoused in this study serve as a starting point for the development of appropriate frameworks to aid the implementation of UGDI.
Predictors of Medication Adherence in Patients with Type 2 Diabetes: A Cross-Sectional Study

Objective: This study aimed to investigate the predictors of medication adherence behavior and the role of self-efficacy in the medication adherence of people with diabetes. Materials and methods: This is a cross-sectional descrip-tive-analytical study. One hundred forty-eight samples were selected through the formula of difference of means. Measure tools consisted of a demographic questionnaire, Morisky Medication Adherence Scale, and psychological constructs questionnaires. SPSS20 software was used for descriptive statistics tests and calculation of correlation coefficients between vari - ables. Amos 8.80 was used to implement the structural equation modeling method. Results: The mean age of participants was 54.1 ± 8.2 and mean of body mass index (BMI) was 28.3 ± 4.5. Correlation coefficients between medication com - pliance behavior and the constructs of knowledge (r = 0.382, p < 0.01), attitude (r = 0.422, p < 0.01), subjective norms (r = 0.312, 05 p < 0.05), self-efficacy (r = 0.481, p < 0.05) and fear (r = 0.305, p < 0.05) were positive and significant. In general, the strongest correlation coefficient was reported between attitude and self-efficacy (r = 0.516, p < 0.01). The fit indices generally showed that the data fitted well with the assumed model. Self-efficacy was the most impor - tant construct that directly influenced medication adherence ( β = 0.585, p < 0.05), followed by attitude ( β = 0.328, p < 0.05) and fear ( β = 0.265, p < 0.05). Conclusions: According to the findings of this study, it was shown that various factors affect medication adherence behavior, among which self-efficacy is the most important reason, and subjective norms, attitude and norms and awareness of factors affecting medication adherence behavior. (Clin Diabetol 2023; 12; 4: 253–260)
Cerebrovascular Fibromuscular Dysplasia – A Practical Review

Abstract Fibromuscular dysplasia (FMD) is a rare idiopathic, segmental, noninflammatory and nonatherosclerotic arteriopathy of medium-sized arteries. It is classically considered to be a disease of young and middle adulthood, with females more commonly affected than males. FMD is a systemic disease. Although historically considered to be rare, cerebrovascular FMD (C-FMD) has now been recognized to be as common as the renovascular counterpart. Extracranial carotid and vertebral arteries are the most commonly involved vascular territories in C-FMD with the clinical presentation determined by vessels affected. Common symptoms include headaches and pulsatile tinnitus, with transient ischemic attacks, ischemic stroke and subarachnoid or intracerebral hemorrhage constituting the more severe clinical manifestations. Cervical artery dissection involving carotids more often than vertebral arteries and intracranial aneurysms account for the cerebrovascular pathologies detected in C-FMD. Our understanding regarding C-FMD has been augmented in the recent past on account of dedicated C-FMD data from North American, European and other international FMD cohorts. In this review article, we provide an updated and comprehensive overview on epidemiology, clinical presentation, etiology, diagnosis and management of C-FMD.
Multi-Scale Aggregation Transformers for Multispectral Object Detection

Multispectral object detection for autonomous driving is multi-object localization and classification task on visible and thermal modalities. In this scenario, modality differences lead to the lack of object information in a single modality and the misalignment of cross-modality information. To alleviate these problems, most existing methods extract information based on a single scale (e.g., these methods mainly focus on detecting significant cars or pedestrians), which leads to insufficient performance in capturing multi-scale discriminative information (e.g., small bicycles and blurred pedestrians) and safety hazards in the driving process. In this letter, we propose a Multi-Scale Aggregation Network (MSANet) consisting of two parts Multi-Scale Aggregation Transformer (MSAT) and the Cross-modal Merging Fusion Mechanism (CMFM), which combined with the advantages of Transformer and CNN to extract rich image information from two modalities by mining both local and global context dependencies. Firstly, to reduce the lack of information in a single modality, we design a novel MSAT module to extract rich details and texture from multi-scale. Secondly, to alleviate feature misalignment caused by modality differences, the CMFM is utilized to aggregate complementary information on multiple levels. Comprehensive experiments on two benchmarks demonstrate that our approach shows better results than several state-of-the-art methods.
The Perfectible Body: The Western Ideal of Male Physical Development

In many cultures, physical perfection is a contradiction in terms; the physical--the realm of the body--is, by definition, thought of as imperfect. Yet in Western cultures, the pervasive tradition in depicting human or superhuman perfection has been that of a conscpicuously masculine physique. This fascinating book explores the origins and evolution of this Western ideal. Photos.
A Dual-Layer Reconfigurable Transmitarray Antenna Based on Two Orthogonal Modes

A novel 1-bit dual-layer reconfigurable transmitarray antenna (RTA) based on two orthogonal modes is presented in this letter. In contrast to traditional multilayer designs, the proposed element has a compact structure with only two metallic layers printed on opposite sides of a single dielectric substrate. The upper and lower patches of the element form a cavity-like structure with two orthogonal modes. An L-shaped slot is loaded on the upper patch to make the structure asymmetric and the two orthogonal modes in the cavity can be converted to each other, realizing the polarization rotation. To realize a reconfigurable structure, a pair of PIN diodes are placed at both ends of the π-shaped slot (combined by an L-shaped slot and a reverse L-shaped slot) to change the direction of the mode rotation clockwise or counterclockwise. The bias network for controlling the PIN diodes is also integrated into the two metallic layers. An RTA prototype with 16 × 16 elements is designed, fabricated, and measured. The measured 3 dB bandwidth of the RTA is 21.2% from 3.8 to 4.7 GHz, with a realized gain of 18.2 dBi at 4 GHz. Good beam scanning performance has also been achieved in the E- and H-planes.
The Approach for Simulation of the Noise-Related Characteristics for Radio-Over-Fiber Transmission Systems

Recently, significant attention has been paid to utilizing fiber optical access networks for the highly-demanded mobile X-haul (X-front or back). Integrating new technology means changing the architecture, evaluating the coexistence, and defining new standards and recommendations for the existing fiber optical access network. Consequently, the reliable and effective mathematical modeling of the physical layer becomes very important for evaluating the various options for developing the access network. Addressing this, we focus on improving the modeling of the converged fiber optical transmission systems aimed at defining the limits and requirements that can be utilized in the design and standardization of the transmission systems. In the scope of current research, we offer the solution for the problem of the diversity of the parameters of the elements of the converged fiber optical transmission system to be simulated. Respectively, we propose the approach for the simulation of the thermal noise and received optical signal power for the orthogonal-frequency-division multiplexed, multi-frequency-band, radio-over-fiber transmission system. The approach aims to adapt the simulation results for different power budgets, signal quality thresholds, and optical receiver sensitivities without additional simulation. The adoption is ensured by the recalculations performed in Matlab software. The signal quality is evaluated in terms of error-vector-magnitude (EVM). The analysis of the number of simulated bits is performed to ensure the efficiency and precision of the simulation. The high-ranking fiber optical simulation software (VPI Design Suite) provides the EVM versus thermal noise curve. Further, it is expanded to received optical signal power versus thermal noise and EVM versus received optical signal power curves via mathematical calculations implemented in program-development software (Matlab). The approach's feasibility is explicitly proved by comparing calculated and simulated results, with the difference not exceeding 0.03% of EVM.
Correlation between Power Elbow Flexion and Physical Performance Test: A Potential Predictor for Assessing Physical Performance in Older Adults

Background: With the increasing number of older adults and their declining motor and cognitive function, it is crucial to find alternative methods for assessing physical functionality. The Short Physical Performance Battery (SPPB), the Time Up and Go (TUG) test, the 4 Meter Walk Test and the Barthel Index (BI) have been used to evaluate mobility and fragility and predict falls. But some of these functional test tasks could be difficult to perform for frail older adults or bedridden patients that cannot ambulate. This study aimed to evaluate the relationship between these functional tests and the power elbow flexion (PEF test). Material and methods: A correlation study was designed with 41 older adults over 65 years of age. The upper limb muscle power was measured using a linear encoder (VITRUBE VBT) with the flexion of the elbow. Results: Strong correlations were found between the PEF test and the 4mWT (rho = 0.715, p = 0.001) and TUG (rho= −0.768, p = 0.001), indicating that the greater the upper limb muscle power is, the greater physical performance will be. Moderate correlations were also found between the PEF and Barthel Index (rho = 0.495, p = 0.001) and SPPB (rho = 0.650, p < 0.001). Conclusions: There is a strong correlation between PEF and the functional tests, proving that older adults that have greater upper limb muscle power have better physical performance. Upper limb muscle power and PEF could be an interesting tool for the assessment of physical performance in bedridden older adults.
User Authentication by Eye Movement Features Employing SVM and XGBoost Classifiers

Devices capable of tracking the user’s gaze have become significantly more affordable over the past few years, thus broadening their application, including in-home and office computers and various customer service equipment. Although such devices have comparatively low operating frequencies and limited resolution, they are sufficient to supplement or replace classic input interfaces, such as the keyboard and mouse. The biometric application we researched verifies a user’s identity based on parameters acquired with a low-cost eye tracker. The use of the eye-tracking device in bank booths has many advantages, including the fact that eye trackers are contactless devices, which, especially in the light of the Covid pandemic, has increasing importance, in addition to providing a solution for confirming the liveness of the user. This paper describes an experiment in which 20 features extracted from eye movement data related mainly to saccades and fixations are used as a complementary biometric modality to authenticate clients at banking kiosks. Data were collected from 39 subjects while operating a banking system using engineered biometric kiosk prototypes. Authentication performance employing eye-movement tracking and parameterizing was compared for two classifiers: Support Vector Machine (SVM) and eXtreme Gradient Boosting (XGBoost). The results showed that the XGBoost-based classifier outperformed the SVM-based one regarding equal error rates (6.76% to 8% vs. 16.21 to 18.78%). Similar differences were obtained for true acceptance rates at different false acceptance rates (0.1 and 0.01), where the SVM-based classifier achieved a maximum of 81.08% and the XGBoost-based achieved 98.65%. Finally, prospects for the broader application of eye movement tracking as a biometric modality are discussed.
Bilateral Deep Vein Thrombosis (DVT) as a Harbinger of Lung Adenocarcinoma: A Rare Presentation

Oncologic disorders, such as lung adenocarcinoma, can intricately interplay with the coagulation cascade, often leading to thromboembolic events, of which deep vein thrombosis (DVT) stands out prominently. In this report, we present a unique case of a 50-year-old non-smoking Jordanian male who exhibited bilateral DVT as an unexpected preliminary manifestation of an aggressive lung adenocarcinoma. Although the patient did not possess common risk factors for DVT, the bilateral presentation drew attention to the possibility of an underlying malignancy. Subsequent investigations revealed a stage 4 primary lung adenocarcinoma. This case underscores the imperative of maintaining a broad differential in cases of DVT, especially when presenting bilaterally and without evident etiology. Such early detection and intervention, accompanied by collaborative medical strategies and specialized care, can play a pivotal role in enhancing patient prognosis and survival rates. This case exemplifies the potential of DVT, particularly when bilateral, as a harbinger of a more sinister underlying pathology like lung adenocarcinoma.
Toxicological Effects of Thimerosal and Aluminum in the Liver, Kidney, and Brain of Zebrafish (Danio rerio)

Vaccination programs in the first years of a child’s life are effective and extremely important strategies for the successful eradication of diseases. However, as no intervention is without risks, the metal-based components of some vaccines, such as thimerosal (TMS), a preservative composed of ethylmercury, and aluminum (Al), have begun to generate distrust on the part of the population. Therefore, this study evaluated the effects of exposure to thimerosal and aluminum hydroxide (alone or in mixture) on Danio rerio (zebrafish) specimens. The fish were exposed to thimerosal and/or aluminum hydroxide intraperitoneally. The liver, kidney, and brain were removed for a biochemical biomarker analysis, histopathological analysis, and metal quantification. As a result, we observed changes in the activity of the analyzed enzymes (SOD, GST, GPx) in the kidney and brain of the zebrafish, a reduction in GSH levels in all analyzed tissues, and a reduction in MT levels in the kidney and liver as well as in the brain. Changes in AChE enzyme activity were observed. The biochemical results corroborate the changes observed in the lesion index and histomorphology sections. We emphasize the importance of joint research on these compounds to increase the population’s safety against their possible toxic effects.
Super-Resolution Reconstruction for Stereoscopic Omnidirectional Display Systems via Dynamic Convolutions and Cross-View Transformer

Stereoscopic omnidirectional images (SODIs) usually require recording very high-resolution (HR) information whereby it is beneficial to exploit a super-resolution (SR) scheme to super-resolve low-resolution (LR) SODIs. Compared with traditional 2-D SR approaches, the algorithms of SODI SR (SODI-SR) need to deal with two extra aspects: binocular information and panoramic characteristics. In this article, we first build a synthetic-specific SODI-SR dataset with LR-HR image pairs. Then, we propose a dynamic convolutions (Dconvs) and transformer network (Dconv-Trans-Net) for SODI-SR. Specifically, due to the nonuniform sampling of equirectangular projection (ERP), we deploy Dconvs with the structure of atrous spatial pyramid pooling (ASPP) to adaptively select content-aware and weight-aware kernels for patch-wise feature extraction. To capture diverse feature embeddings from left and right views, we utilize a symmetric bidirectional parallax attention module (biPAM) to extract local features along epipolar lines and propose cross-view transformer (CvTrans) to mine global contextual features apart from the epipolar line. Finally, quantitative and qualitative experiments demonstrate that our proposed approach outperforms the state-of-the-art (SOTA) panoramic or stereoscopic SR methods on the constructed SODI-SR dataset with two upscaling factors.
Performance Analysis of Pow/Pow/1/∞ Queue Under Heavy Network Traffic Using Maximum Entropy Approach

A theoretical queueing model Pow/Pow/1/∞ with power law distributed inter-arrival and service times is proposed to investigate the performance of nodes in computer communication networks. Closed form expressions for queue length distribution and various performance measures such as mean queue length, variance of number of packets, overflow probability and average waiting time are derived in terms of traffic intensity ρ. The queue length distribution is found to depict power law. Numerical analysis of performance measures provide useful insights into the behavior of network nodes. Both mean queue length and average waiting time increase to infinite as ρ tends to 0.5 resulting in long delay at network nodes. The variance of number of packets also starts exploding as ρ approaches to 0.3. These results are in close agreement with the empirical studies carried out on real traffic traces in the past. The proposed model is useful in designing networks, dimensioning resources and developing congestion control algorithms.
Dynamic Simulation as an Approach to Understanding Hurricane Risk Response : Insights from the Stormview Lab

Established in 1984, the Wharton Risk Management and Decision Processes Center develops and promotes effective corporate and public policies for low‐probability events with potentially catastrophic consequences through the integration of risk assessment, and risk perception with risk management strategies. Natural disasters, technological hazards, and national and international security issues (e.g., terrorism risk insurance markets, protection of critical infrastructure, global security) are among the extreme events that are the focus of the Center's research. The Risk Center's neutrality allows it to undertake large‐scale projects in conjunction with other researchers and organizations in the public and private sectors. Building on the disciplines of economics, decision sciences, finance, insurance, marketing and psychology, the Center supports and undertakes field and experimental studies of risk and uncertainty to better understand how individuals and organizations make choices under conditions of risk and uncertainty. Risk Center research also investigates the effectiveness of strategies such as risk communication, information sharing, incentive systems, insurance, regulation and public‐private collaborations at a national and international scale. From these findings, the Wharton Risk Center's research team – over 50 faculty, fellows and doctoral students – is able to design new approaches to enable individuals and organizations to make better decisions regarding risk under various regulatory and market conditions. The Center is also concerned with training leading decision makers. It actively engages multiple viewpoints, including top‐level representatives from industry, government, international organizations, interest groups and academics through its research and policy publications, and through sponsored seminars, roundtables and forums. Abstract We explore the use of laboratory simulations as a tool to study how residents of coastal areas make decisions to prepare for a tropical cyclone. A prototype web-based simulation named " Stormview " is described that allows individuals to experience the approach of a virtual hurricane in a computer-based environment. Stormviem participants can watch television broadcasts, listen to the radio, search the Internet, hear from neighbors, and indicate their own intentions to take protective action. Stormview is used to model the dynamics of how a sample of Florida residents Florida gather information in advance of a storm, as well as how their preparedness decisions are influenced by: (1) the severity of prior storms in priming levels of concern and preparedness actions; (2) the depiction of forecast graphics; and (3) the role of word-of-mouth influences. We find that patterns of information use parallel those reported in field studies of media use during storms, and …
Effects of different silage preservatives on silage quality of Pennesitum purpureum harvested at different harvesting periods.

The study was conducted to determine the effects of preservatives on the chemical composition of elephant grass (P. purpureum Bana cv.) harvested from N-fertilized and unfertilized treatments at different periods (3, 6 and 9 months). The plants were grown on 1st November 2008 and harvested every 3 months until July 2009. The grass was chopped and a 500 g sample obtained and was mixed with 4% molasses, 4% molasses+0.25% urea and 2.5% dicalcium phosphate, respectively with plain silage as a control. The samples were ensiled with respective preservative in duplicates and were analyzed for pH and proximate after 30 days of ensiling. Molasses added silage had a higher (P<0.05) DM at 3 months on both N-fertilized and unfertilized treatments, whereas molasses added silage prepared from unfertilized treatment harvested at 3 months of growth, had lowest (P<0.05) pH and was highly (P<0.05) digestible but digestibility declined as the plant matured.