Miracle-dz/UniFAR-FTUs huggingface dataset:
Patients' Knowledge about Chronic Diseases towards Risk Factors and Warning Signs of Stroke

Objectives: to assess chronic diseases patients’ knowledge toward stroke risk factors and warning signs, besidesdetermining the relationship between chronic diseases patients’ knowledge and their sociodemographicalcharacteristics.Methodology: A descriptive study was carried out at public medical clinics which has started from December2nd, 2008 to August 8th, 2009. A purposive "non-probability" sample of (300) chronic diseases individuals whowere clients of Public Medical Clinics who have one or more of the following chronic diseases (hypertension,diabetes mellitus, heart diseases, and previous stroke), in Baghdad city. The data were collected through the useof a constructed questionnaire which consists of three parts (1) Sociodemographic data form that consist 7-items(2) Medical data form that consists of 10-items and (3) Main domains of the studied phenomena form consists of3-sections (domains) of definition, warning sings, and risk factors of 62 items, by means of direct interviewtechnique with the chronic diseases patients. Descriptive statistical analysis procedures (frequency, percentage,mean of scores, standard deviation, and relative sufficiency) and inferential statistical analysis procedures(pearson correlation coefficient, contingency coefficient, Chi-square test, and Fisher exact probability test) wereused.Results: The findings of the study indicated that there is a knowledge deficit of chronic diseases patients mainlyin stroke warning signs followed by stroke risk factors. No significant relationship was found between chronicdiseases patients’ knowledge and their gender, employment, while significant relationship was found betweenchronic diseases patients’ knowledge and their age and level of education.Recommendations: The study recommends that an intensive comprehensive, evidence-based obligatory widepopulation-based health education programs are needed to improve awareness of stroke, especially among themost vulnerable groups (chronic diseases patients), eldeely, and less educated persons as well as lay people.
kMaX-DeepLab: k-means Mask Transformer

The rise of transformers in vision tasks not only advances network backbone designs, but also starts a brand-new page to achieve end-to-end image recognition (e.g., object detection and panoptic segmentation). Originated from Natural Language Processing (NLP), transformer architectures, consisting of self-attention and cross-attention, effectively learn long-range interactions between elements in a sequence. However, we observe that most existing transformer-based vision models simply borrow the idea from NLP, neglecting the crucial difference between languages and images, particularly the extremely large sequence length of spatially flattened pixel features. This subsequently impedes the learning in cross-attention between pixel features and object queries. In this paper, we rethink the relationship between pixels and object queries and propose to reformulate the cross-attention learning as a clustering process. Inspired by the traditional k-means clustering algorithm, we develop a k-means Mask Xformer (kMaX-DeepLab) for segmentation tasks, which not only improves the state-of-the-art, but also enjoys a simple and elegant design. As a result, our kMaX-DeepLab achieves a new state-of-the-art performance on COCO val set with 58.0% PQ, Cityscapes val set with 68.4% PQ, 44.0% AP, and 83.5% mIoU, and ADE20K val set with 50.9% PQ and 55.2% mIoU without test-time augmentation or external dataset. We hope our work can shed some light on designing transformers tailored for vision tasks. TensorFlow code and models are available at https://github.com/google-research/deeplab2 A PyTorch re-implementation is also available at https://github.com/bytedance/kmax-deeplab
College Managers’ Views on The Employability of Vocational Engineering Graduates: A Case of The South African TVET College Sector

This study investigated the required competencies that TVET college engineering graduates need to be employable and become successful entrepreneurs after completing their studies. The study used a qualitative design and semi-structured interviews to collect the data. Purposive sampling was used to select the participants from three public TVET colleges in Gauteng. The study reported that National Certificate Vocational college engineering graduates need relevant engineering content knowledge, authentic practical engineering workplace experience, soft skills, technical skills and their application in the real world. It was also found that the engineering sector has a negative attitude towards TVET engineering graduates and that there is a lack of lecturers with engineering industry experience. We relied on a small sample; hence, the results of this study may not be generalisable, but moving forward, a cross-national study including all TVET programmes may be required; and, most probably, different results will be generated. We concluded by advocating the review of the TVET engineering curriculum and a paradigm shift to an intense formally supervised and examined industry-oriented workplace component that would boost the technical expertise of graduates. A widespread advocacy campaign in the engineering sector could also help to raise their awareness of TVET programmes.
Determinants of Outward FDI from Developing Economies: Evidence for a Sample of Latin American Countries

Abstract Grounded on a conceptual framework that combines contributions from the investment development path (IDP) theory, the Ownership, Location, Internalization (OLI) paradigm, and the institutional theory, this work aims to analyze the home country’s determinants of outward Foreign Direct Investments (OFDI). Based on panel data for a set of 14 Latin American countries between 2000 and 2019, the results of random effects estimations support the propositions of the IDP and institutional theories. Economic development, inward FDI, and institutional quality are strong determinants of OFDI. Results also highlight the role of the openness level and the membership of regional trade agreements in explaining OFDI from Latin America countries.
Mass Dependence of Galaxy–Halo Alignment in LOWZ and CMASS

We measure the galaxy-ellipticity (GI) correlations for the Sloan Digital Sky Survey Data Release 12 LOWZ and CMASS samples with the shape measurements from the DESI Legacy Imaging Surveys. We model the GI correlations in an N-body simulation with our recent accurate stellar–halo mass relation from the Photometric object Around Cosmic webs (PAC) method. The large data set and our accurate modeling turns out an accurate measurement of the alignment angle between central galaxies and their host halos. We find that the alignment of central elliptical galaxies with their host halos increases monotonically with galaxy stellar mass or host halo mass, which can be well described by a power law for the massive galaxies. We also find that central elliptical galaxies are more aligned with their host halos in LOWZ than in CMASS, which might indicate an evolution of galaxy–halo alignment, though future studies are needed to verify this is not induced by the sample selections. In contrast, central disk galaxies are aligned with their host halos about 10 times more weakly in the GI correlation. These results have important implications for intrinsic alignment (IA) correction in weak lensing studies, IA cosmology, and theory of massive galaxy formation.
Entanglement and Disordered-Enhanced Topology in the Kitaev Chain

Over the recent years tools from quantum information theory have become indispensable in characterizing many body systems. In this work we employ measures of entanglement to study the interplay between disorder and topology in 1D systems of the Kitaev type, which can host Majorana end modes at their edges. We find that the entanglement entropy may actually increase as a result of disorder, and identify the origin of this behavior in disorder-induced quantum criticality. We also employ the entanglement spectrum to accurately determine the phase diagram of the system, and find that disorder may enhance topology, and lead to the appearance of Majorana zero modes in systems whose clean version is trivial.
Decentralised adaptive control of switched interconnected high-order nonlinear systems with unknown control direction and time-delay

ABSTRACT This paper studies the dynamic state feedback control problem for a class of interconnected large-scale switched high-order nonlinear systems with unknown control direction and time-varying time-delay. The adaptive laws are designed to estimate the bounds of switched parameters under arbitrary switching for subsystems. The Nussbaum function is used to deal with the unknown control direction problem. By combining the backstepping and homogeneous domination technique, the decentralised adaptive control strategies are developed and the resulting closed-loop system is asymptotically stable. Finally, a simulation example is given and the results show the effectiveness of the proposed control design method.
Safety and Healthcare Resource Utilization in Patients Undergoing Left Atrial Appendage Closure—A Nationwide Analysis

Percutaneous left atrial appendage closure (LAAC) has emerged as a non-pharmacological alternative for stroke prevention in patients with atrial fibrillation (AF) not suitable for anticoagulation therapy. Real-world data on peri-procedural outcomes are limited. The aim of this study was to analyze outcomes of peri-procedural safety and healthcare resource utilization in 11,240 adult patients undergoing LAAC in the United States between 2016 and 2019. Primary outcomes (safety) were in-hospital ischemic stroke or systemic embolism (SE), pericardial effusion (PE), major bleeding, device embolization and mortality. Secondary outcomes (resource utilization) were adverse discharge disposition, hospital length of stay (LOS) and costs. Logistic and Poisson regression models were used to analyze outcomes by adjusting for 10 confounders. SE decreased by 97% between 2016 and 2019 [95% Confidence Interval (CI) 0–0.24] (p = 0.003), while a trend to lower numbers of other peri-procedural complications was determined. In-hospital mortality (0.14%) remained stable. Hospital LOS decreased by 17% (0.78–0.87, p < 0.001) and adverse discharge rate by 41% (95% CI 0.41–0.86, p = 0.005) between 2016 and 2019, while hospital costs did not significantly change (p = 0.2). Female patients had a higher risk of PE (OR 2.86 [95% CI 2.41–6.39]) and SE (OR 5.0 [95% CI 1.28–43.6]) while multi-morbid patients had higher risks of major bleeding (p < 0.001) and mortality (p = 0.031), longer hospital LOS (p < 0.001) and increased treatment costs (p = 0.073). Significant differences in all outcomes were observed between male and female patients across US regions. In conclusion, LAAC has become a safer and more efficient procedure. Significant sex differences existed across US regions. Careful considerations should be taken when performing LAAC in female and comorbid patients.
Covariance Correction Step for Kalman Filtering with an Attitude

Redundant attitude representations are often used in Kalman filters for estimating dynamic states that include an attitude. A minimal three-element attitude deviation is combined with a reference attitude, where the deviation is included in the filter state and has an associated covariance estimate. This paper derives a reset step that adjusts the covariance matrix when information is moved from the attitude deviation to the reference attitude. When combined with the extended or unscented Kalman filter prediction and measurement steps, the reset allows one to easily construct a Kalman filter for a system for which the state includes an attitude. This algorithm is closely related to (and a correction to) the multiplicative extended Kalman filter or the unscented quaternion estimator, depending on whether the reset is combined with an extended or unscented Kalman filter. In comparison to the multiplicative extended Kalman filter, it is more general and includes a reset after the measurement update, as well .
COSMOS: Catching Out-of-Context Image Misuse Using Self-Supervised Learning

Despite the recent attention to DeepFakes, one of the most prevalent ways to mislead audiences on social media is the use of unaltered images in a new but false context. We propose a new method that automatically highlights out-of-context image and text pairs, for assisting fact-checkers. Our key insight is to leverage the grounding of images with text to distinguish out-of-context scenarios that cannot be disambiguated with language alone. We propose a self-supervised training strategy where we only need a set of captioned images. At train time, our method learns to selectively align individual objects in an image with textual claims, without explicit supervision. At test time, we check if both captions correspond to the same object(s) in the image but are semantically different, which allows us to make fairly accurate out-of-context predictions. Our method achieves 85% out-of-context detection accuracy. To facilitate benchmarking of this task, we create a large-scale dataset of 200K images with 450K textual captions from a variety of news websites, blogs, and social media posts
Event-Triggered Reference Governors for Collisions-Free Leader–Following Coordination Under Unreliable Communication Topologies

Reference governors are add-on control schemes, which enforce state constraints on prestabilized systems by modifying, whenever necessary, the reference. This article studies the design schemes of reference governors for collisions-free leader–following coordination (CF-LFC) of nonlinear multiagent systems under unreliable communications. The “unreliability” is characterized as irregular topology switchings (e.g., due to communication failures, adversarial attacks, or other agents' blockages), which will often cause large transient coordination errors and further result in interagent collisions. To address it, an event-triggered reference governor is proposed, which dominates agents to perform the leader–following task if the tracking error meets the closed-loop system performance requirement, and otherwise the agents will temporarily “forget” the task and focus on avoiding collisions. By constructing heterogeneous Lyapunov functions, it is shown that the reference governor can achieve the CF-LFC despite the presence of topology switchings. Also, for a special class of nonlinear systems with strict-feedback form, a nonevent-triggered reference governor is further proposed by reconstructing the controller with a high-order integrator of barrier function as the control gain to adaptively adjust the transient tracking errors.
Low-Complexity Hybrid Beamforming for MMSE-Based Symbol-Level Precoding in Multi-User MISO System

Data-aided symbol-level precoding can exploit constructure interference for improving the energy and system efficiency in the multiantenna downlink channel, where multiple users are simultaneously served over the same channel resources. This article attempts at the end-to-end joint design of hybrid symbol-level precoder, which deals with a flexible form of constructive interference region, while allowing for multi-level constellations mixed among the different users. It considers the minimum mean square error-based optimization problem to ensure the minimum required gain under a fixed total-power constraint, which involves critical implementation issues regarding the computational complexity. An iterative closed-form solution has been presented while deriving the optimum solution in a closed form for a digital precoder subject to a fixed analog beam, serving as a key implementation block for low-complexity implementation. Furthermore, a mathematical framework is developed for employing the different number of radio frequency chains dynamically for the analog precoder as an efficient means of achieving a tradeoff between the power consumption and the performance in practice. It is shown that the performance of our proposed algorithm is similar to that of the fully-digital precoder within approximately 1 dB, suggesting that its implementation complexity can be overcome, even for numerous antenna elements, in practice.
Research and Development on Galengdowo Village’s Tahu Walik Cracker Using Different Seasonings

Tahu walik is a snack product originating from Banyuwangi but has been developed in other areas such as Galengdowo Village, Jombang. To develop Galengdowo's tahu walik products that were able to compete inmarket, it was necessary to conduct research related to product sensory and consumer acceptance. The five sample variants used in this study were tahu walik without seasoning (T0), original seasoning (T1), balado seasoning (T2), salted pepper seasoning (T3), and commercial tahu walik (T4) for comparison. A total of 40 panelists conducted a hedonic analysis of the product's appearance in the packaging, shape, color, crispness, taste, and oily. The results showed that the highest purchase motivation was seen in T1 and T2, which were reddish, while the assessment of the packaging and sample's shape was not significantly different. The crispness value of T0 was the lowest compared to the other four samples which were not significantly different. Panelists most liked the taste of T3, T2, and T4 while T0 was the lowest, while the oily feeling was felt the most in sample T0 and the lowest in T2. Based on Simple Additive Weighting, T2 has the highest rank while T0 is the lowest. The difference in the type and color of the seasoning greatly influenced the panelists' preferences and their decision to buy tahu walik products. It can be concluded that the tahu walik processing industry in Galengdowo Village needs to develop its products to increase competitiveness in the market.
Autour de l'entropie des difféomorphismes de variétés non compactes

Dans ce memoire, nous etudions l'entropie des systemes dynamiques differentiables definis sur des varietes riemanniennes non compactes. Dans un premier temps, nous eclaircissons les liens entre differentes notions d'entropie dans ce cadre non compact. Ensuite, nous utilisons ces premiers resultats pour y etudier la validite de l'inegalite de Ruelle. Rappelons ici que cette inegalite, pour des diffeomorphismes de varietes riemanniennes compactes, nous dit que l'entropie est majoree par la somme des exposants de Lyapounov positifs. Nous montrons que, lorsque nous enlevons l'hypothese de compacite, l'inegalite de Ruelle n'est pas toujours satisfaite. Nous obtenons ce resultat en construisant une famille explicite de contre-exemples. En revanche, nous montrons, dans le cas d'un diffeomorphisme de comportement asymptotique lineaire, ou du flot geodesique sur le fibre unitaire tangent d'une variete riemannienne a courbure negative, que l'inegalite de Ruelle est toujours satisfaite. Pour finir, nous nous interessons au probleme de la perte possible de masse d'une suite de mesures de probabilite d'une variete riemannienne non compacte. Dans le cas du flot geodesique, nous montrons que l'entropie permet de controler la masse d'une limite vague de mesures de probabilite invariantes par le flot pour une classe particuliere de varietes geometriquement finies. Plus precisement, nous montrons qu'une suite de mesures d'entropie assez grande ne peut pas perdre la totalite de sa masse. De plus, le minorant optimal de l'entropie dans ce resultat est lie a la geometrie de la partie non compacte de la variete: c'est l'exposant critique maximal des sous-groupes paraboliques du groupe fondamental.
Methanolic Extract Of Swietenia macrophylla Exhibits Antibacterial And Antibiofilm Efficacy Against Gram-Positive Pathogens

Gram-positive pathogens cause infections such as pneumonia, skin infections, anthrax, and sinusitis. The objective of this study was to determine the phytochemical profile, antibacterial and antibiofilm efficacy of Swietenia macrophylla methanolic extract (SMME) against Gram-positive pathogens. The secondary metabolites of SMME were analyzed using GC-MS while the antibacterial efficacy of SMME against Staphylococcus aureus ATCC 33862, Bacillus cereus ATCC 11778, Streptococcus pneumonia ATCC 19615, and Clostridium sporogenes ATCC 13124 was assessed using MIC and MBC assays. Biofilm biomass assay and time-kill assay were performed to determine the antibiofilm activity of SMME against the pathogens. Results demonstrated that six common antibacterial secondary metabolites were present in the SMME. The major compound was found to be β-amyrin (22.8%). The SMME showed the lowest MIC values against B. cereus (31.25 µg/mL) and C. sporogenes (31.25 µg/mL) and the lowest MBC value against S. aureus (1000 µg/mL). The SMME also significantly (p<0.05) inhibited all the biofilms. It started to inhibit S. pneumonia and C. sporogenes biofilms after 12 h of exposure. On the other hand, the BIC50 value showed that the SMME was most effective against B. cereus. In conclusion, the secondary metabolites in the SMME may contribute to the antibacterial and antibiofilm efficacy against Gram-positive pathogens.
Extraction of input parameters for the theory of radiative energy transfer using deconvolution

The ever growing application of wireless communication systems requires accurate models for characterising radiowave propagation when affected by the presence of a variety of obstacles. In particular if the obstacles take the shape of vegetation volumes, like single trees or groups of trees and are present in the radio path, they give rise to absorption and scattering of radio signals. This thesis presents a literature review of common models for radiowave propagation through vegetation, the theory of Radiative Energy Transfer (RET) is one of these models and provides an accurate analysis of radiowave propagation through a vegetation media. Extensive measurements have been designed and conducted in a controlled indoor environment to provide valuable measurement data for later development of deconvolution approaches. It can be shown that the measured directional spectra are convolution products of the phase function pattern and the receiver antenna radiation patterns, which impacts determination of the RET input parameters. Consequently, in order to achieve more accurate determination of the RET input parameters, the adverse influence caused by receiver antenna radiation patterns have to be removed from measured directional spectra by implementing a process of deconvolution. This thesis provides successful implementation of two iterative based deconvolution techniques on the measurement directional spectra. To the author's knowledge, this is its first kind of application to eliminate distortion caused by the receiver antenna radiation pattern during measurements. This thesis reports a number of novel approaches. These include the further development and extension of deconvolution techniques such as combining the Bennia-Riad criterion and an error function to determine optimal parameters, as well as using pre-filtering techniques to improve the deconvolution results. Development of clearly defined criteria based on the knowledge of the central-limit theorem and discussion of loss of information avoidance during convolution is another novel contribution. Further novelty lies in the modification of the two methods to suit implementation on the measurement data from radiowaves impacting on vegetation volumes. As a result of these refinements, extracted RET input parameters from the restored patterns after applying the deconvolution processes show evident improvements compared to those extracted from directly measured patterns. Early stage results of this project are published in the IEEE Proceedings on Next Generation Applications, Services and Technologies.