Miracle-dz/UniFAR-FTUs huggingface dataset:
Inventions and patenting in Africa: Empirical trends from 1970 to 2010

Abstract Economic development is increasingly dependent upon on utilizing new knowledge to innovate and create value, even in traditional industries and in low‐income countries. This analysis uses evidence on patent families to assess innovation activity throughout sub‐Saharan Africa. We find patent activity in sub‐Saharan Africa—both by African inventors and by foreign inventors—is comparable to similar regions around the world, when conditioned on economic size. Patent filings in Africa have grown, particularly, since the mid‐1990s, but at different rates within different African jurisdictions. Types of technologies being patented in Africa have remained stable over 30 years, with most in pharmaceuticals, chemistry, biotechnology, and engineering. The majority of patent filings in Africa are from Europe, the United States, and other high income countries. Yet, in South Africa, between 15% and 20% of patent filings are by residents of South Africa, and 3% are from other developing and emerging economies. Only a small share of inventions globally are made in sub‐Saharan Africa, but for those inventions that do arise in Africa, foreign filings are made widely outside of Africa.
A REAL-TIME AUTOMATIC METHOD FOR TARGET LOCATING UNDER UNKNOWN WALL CHARACTERISTICS IN THROUGH-WALL IMAGING

—To solve the real-time through-wall detection problem in the presence of wall ambiguities, an approach based on kernel extreme learning machine (KELM) is proposed in this paper. The wall ambiguity and propagation eﬀect are included in single-hidden-layer feedforward networks, and then the technique converts the through-wall problem into a regression problem. The relationship between the scattered data and the target properties is determined after the KELM training process. Numerical results demonstrate the good performance in terms of the eﬀectiveness, generalization, and robustness. Compared with the support vector machine (SVM) and least-squares support vector machine (LS-SVM), the KELM provides almost the same estimated accuracy but at a much faster learning speed, which greatly contributes to solving the real-time detection problem. In addition, the situations of two targets, diﬀerent target radii, and noisy circumstances are discussed.
Modélisation géométrique par primitives

Les objets naturels ou artificiels contiennent des elements geometriques repetes pouvantetre interpretes comme des formes primitives. Les plantes, les arbres, les organismes vivants ou meme les cristaux representent des primitives qui se repetent. Les primitives se retrouvent aussi couramment dans les environnements crees par l'homme, car les architectes ont tendance a reutiliser les memes modeles sur un bâtiment et utilisent generalement des formes simples, telles que des fenetres et des portes rectangulaires. Au cours de ma these, j'ai etudie les primitives geometriques sous trois angles: leur composition, leur simulation et leur decouverte autonome. Dans la premiere partie, je presente une methode pour retrouver la fonction par laquelle certaines primitives sont combinees. Notre systeme est base sur un modele de fonction de composition represente par une surface parametrique. La surface parametrique est deformee via un alignement non rigide d'une surface qui, une fois convergee, represente l'operateur souhaite. Cela permet de modeliser de maniere interactive les operateurs via une simple esquisse, ce qui resout un probleme majeur de facilite de modelisation de la composition. Dans la deuxieme partie, je presente l'utilisation d'une nouvelle primitive pour les simulations de physique en temps reel. Cette primitive convient pour modeliser efficacement les deformations des cordes preservant le volume, mais egalement celles de structures plus complexes telles que les muscles. L'un des principaux avantages de notre approche est que notre primitive peut servir de representation unifiee pour la detection de collision, la simulation et la deformation de peau. Dans la troisieme partie, je presente un cadre d'apprentissage en profondeur non supervise pour apprendre et detecter les primitives. Dans un signal contenant une repetition d'elements, le procede est capable d'identifier automatiquement la structure de ces elements (c'est-a-dire des primitives) avec une supervision minimale. Afin de former le reseau qui contient une operation non differenciable, un nouveau processus d'apprentissage en plusieurs etapes est presente.
Design of a bipedal robot for rapid acceleration and braking manoeuvres

Animals in nature are capable of performing rapid acceleration and braking manoeuvres with ease. However, they have been avoided by researchers due to the complexities of this motion. To investigate and test novel control schemes for such motions, a highly agile mechanical robot is required. The aim of this dissertation was to build a bipedal robot to perform optimal rapid acceleration manoeuvres. This focused on investigating existing robots and using the information therein to design, build and test a new bipedal robot with high agility. The author performed a vigorous investigation into existing actuator schemes and leg topologies that promote agility, balancing the numerous trade-off’s such as mass-specific force and proprioception. This led to the selection of a Quasi-Direct Drive transmission with a scissor linkage leg. Legged robots were generally designed around some known motion [1]. However, selecting suitable mechanical parameters for agile motions with a lack of relevant research was challenging. Trajectory optimisation methods were used to generate unique acceleration motions for bipedal models, aiding in the selection of several physical parameters. With this, a detailed design of Baleka was created, prioritising desirable characteristic for rapid motions. Through several design iterations, the outcome was a fully assembled light weight bipedal robot. All the supporting systems required to operate Baleka were designed and set up, including the Real-time control system, relevant sensors and a boom support to keep it planar. A known metric, vertical agility [2], was used to compare Baleka’s agility to existing robots. Furthermore, a Raibert Controller [3] was also tested on the platform to investigate the robustness of the design. Baleka was found to be the most agile bipedal robot, exceeding the agility of humans. It was able to hop higher than all other robots, verifying it’s suitability for rapid acceleration manoeuvres. However, from the repetitive hopping experiments and high impact forces, slight plastic deformation was witnessed in the gearbox drive shafts.
Heterogeneity of CD4+ T Cells

CD4+ T cells, which consist of T helper cells and T regulatory cells (Tregs) are indispensable for adaptive immunity. T helper cells are key positive regulators of both the humoral and cellular immune responses to infections, whereas Tregs attenuate immune responses and are important for tissue homeostasis. It has been known for over 30 years that CD4+ T cells are a heterogenous population that can be divided into several groups, which were largely defined in vitro according to their cytokine production profiles. First, we attempted to unravel the T cell heterogeneity in vivo at a single cell resolution. To this end, we performed single cell RNA-seq on colonic CD4+ T cells from healthy mice, as well as mice infected with pathogens that are known to skew the T cells towards particular cytokine responses. Upon infection, effector CD4+ T cells completely change and diversify their transcriptome. However, these transcriptional changes only partially fit with the classic T helper programs. Interestingly, Il17a-expressing cells from different conditions are transcriptionally more similar to Ifngexpressing cells from the same condition, suggesting that these are not entirely distinct cell subsets. Instead, we identified several overlapping gene modules that orchestrated a continuum of Ifng and Il17a-expressing cell states. Transcriptional profiling and ELISA of sorted populations from different “poles” of the continuum further validated these data. Moreover, we identified several new CD4+ effector T cells subpopulations, such as a population that
Acute Effects of Different Warm-up Protocols on Sports Performance in Elite Male Collegiate Handball Players

Abstract Chen, CH, Chang, CK, Tseng, WC, Chiu, CH, Dai, X, and Ye, X. Acute effects of different warm-up protocols on sports performance in elite male collegiate handball players. J Strength Cond Res 36(8): 2262–2267, 2022—This study aimed to examine the effects of 3 different warm-up protocols on subsequent sports performance in elite male collegiate handball players. Fifteen handball players (19.0 ± 2.4 years) completed 3 separated randomly sequenced experimental visits. During each visit, they started with different warm-up protocols (traditional warm-up [TRAD] vs. warm-up with core stability exercises [CORE] vs. warm-up with elastic band exercises [ELAS]) and completed with a series of randomly ordered sport-specific performance testing measurements: 30-m sprint, countermovement jump, medicine ball overhead forward throw, and standing and jump handball throw tests. Both CORE and ELAS protocols induced statistically significant differences (p < 0.05) on overall sports performance (sprint time, jump height, medicine ball throwing peak velocity and power, and handball throwing velocities), as compared to the TRAD. In addition, the ELAS protocol imposed small-to-medium effects (effect size range: 0.45–0.82), enhancing handball throwing velocity and medicine ball throwing performance comparing with the CORE. Sport-specific warm-up protocols that contain core stability or elastic band–based exercises likely induced subsequent performance enhancements (sprint, jump, and throw) in elite male collegiate handball players when compared with TRAD. Furthermore, including elastic band exercises in the warm-up protocol even induced superior upper-body performance enhancement (explosive power and handball throwing velocity) than other protocols. Therefore, preconditioning warm-up activities using elastic band–based exercises can be integrated into a traditional sport-specific warm-up protocol for elite collegiate handball players before competition or training.
EFFECT OF ECOFRIENDLY BIO-BASED SOLVENTS ON OIL EXTRACTION FROM GREEN COFFEE BEAN AND ITS INDUSTRIAL PRESS CAKE

- Oil recovery, retention index, and thermodynamic parameters of green coffee beans (GCB) and its press cake (PC) extraction using bio-based solvents were investigated. The extraction parameters investigated were temperature (35 to 55 °C), type of material (coffee beans and press cake), and type of solvent (ethanol, acetone, and ethyl acetate), at a fixed solvent to solid mass ratio (5:1) (w/w). The fatty acid profile of the ethanolic extract was assessed for both GCB and PC, and compared to the oil obtained from the mechanical pressing. It was observed that higher temperatures affected positively the extraction yields, especially when acetone and ethanol were employed, allowing a recovery up to 90% and 56.7% for GCB and PC, respectively. The solution retained in the raffinate phase from the GCB extraction was greater than that for the PC. For all operational levels, the ∆H and ∆S were positive. ∆G decreased with increasing temperature. Palmitic and linoleic acids were predominant in all types of oil. The oil obtained by pressing showed higher content of linoleic acid (45.32%), while the solvent-extracted oil from GCB had more palmitic acid (34.79%), and the PC oil presented intermediate levels of all the methyl esters.
Integrated framework of knowledge discovery and knowledge management for e-health in Saudi Arabia : supporting citizens with diabetes mellitus

Saudi Arabia experiences insufficient effort in terms of patients’ education in relation to a number of prevalent diseases, including diabetes mellitus, musculoskeletal disorders and upper respiratory tract infections. In addition, the number of studies related to e-health initiatives to support patients in the Kingdom are limited and only benefit patients of a few hospitals. This situation leads to deficient application of self-management and education strategies to empower patients to manage their diseases. Unfortunately, such a deficiency can affect the health status in the Kingdom negatively as diabetes mellitus is reported as the first cause of death in the Kingdom among all other prevalent diseases. Although knowledge management has been proven to be a valuable approach to sharing knowledge and educating users to manage their illnesses, it has not been implemented appropriately to support the increasing number of diabetic citizens in Saudi Arabia. In this research, knowledge management is integrated with knowledge discovery to support specific needs of the diabetic community in the Kingdom. Such an integration constitutes an e-health initiative to support diabetic citizens and healthcare professionals to manage this expanding illness in Saudi Arabia. Knowledge discovery is implemented through data mining to elicit useful knowledge related to specific diabetes complications encountered by diabetic citizens in the Kingdom. The integrated framework applies the SECI model to capture and disseminate useful diabetes self-management and educational expertise to support the management of diabetes complications. This integrated approach to knowledge management and knowledge discovery has provided a valuable tool implemented in terms of a web portal. This has facilitated the exchange and dissemination of tacit and explicit knowledge of the diabetic community in the forms of strategies, guidelines and best practices. It has also overcome the issues faced by the organisational and national cultures affecting knowledge management practice in Saudi Arabia.
Association of Dietary and Serum Cholesterol with Active Pulmonary Tuberculosis: A Hospital Based Study

More than 2 billion people, equal to one-third of the world’s population, are infected with Mycobacterium tuberculosis. Out of all the infected cases only 5-10 % develops symptoms and in the rest, the bacterium remains latent. TB accounts for over 2 million deaths per year worldwide, making it one of the leading infectious causes of death in the world (WHO TB Control Geneva 2010; Dye et al., 2010). Cholesterol is a vital molecule for maintaining the integrity of lipid rafts making it important for the appropriate International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 6 Number 12 (2017) pp. 4056-4073 Journal homepage: http://www.ijcmas. com
A Comparative Case Study on The Perceptions of Pre-School Teachers on Gender Roles and Practices

The aim of this study is to examine the perceptions of preschool teachers on gender roles and classroom practices in a comparative manner. Qualitative research method was used in this study. The participants of the study are preschool teachers working in Turkey and Turkish Republic of Northern Cyprus. In this study, convenience sampling method was used. The study group comprised 21 preschool teachers volunteering to participate and provided written consent. The data were collected through an interview schedule that comprised 9 semi structured questions. The results obtained from teachers in Turkey and Turkish Republic of Northern Cyprus showed teachers showed gender stereotypical behaviors in their classrooms in both countries. According to the teacher perceptions, women are passive, fragile and emotional while men are independent and powerful. It can be concluded that teachers in both countries have practices aimed to prevent the development of gender prejudices in children.
A Survey on Energy Management for Mobile and IoT Devices

Editor’s notes: Mobile and IoT devices have proliferated our daily lives. However, these miniaturized computing systems should be highly energy-efficient due to their ultrasmall form factor. Hence, energy management is of utmost importance for both mobile and IoT devices. This article presents a comprehensive survey on this topic. —Partha Pratim Pande, Washington State University
Real-Time Object Detection for AUVs Using Self-Cascaded Convolutional Neural Networks

This article presents an automatic real-time object detection method using sidescan sonar (SSS) and an onboard graphics processing unit (GPU). The detection method is based on a modified convolutional neural network (CNN), which is referred to as self-cascaded CNN (SC-CNN). The SC-CNN model segments SSS images into object-highlight, object-shadow, and seafloor areas, and it is robust to speckle noise and intensity inhomogeneity. Compared with typical CNN, SC-CNN utilizes crop layers which enable the network to use local and global features simultaneously without adding convolution parameters. Moreover, to take the local dependencies of class labels into consideration, the results of SC-CNN are postprocessed using Markov random field. Furthermore, the sea trial for real-time object detection via the presented method was implemented on our autonomous underwater vehicle (AUV) named SAILFISH via its GPU module at Jiaozhou Bay Bridge, Qingdao, China. The results show that the presented method for SSS image segmentation has obvious advantages when compared with the typical CNN and unsupervised segmentation methods, and is applicable in real-time object detection task.
Effect of land use/cover changes on runoff in the Min River watershed

Quantifying and interpreting the impacts that land use/cover change (LUCC) have on hydrology at basin scales are of great significance for the sustainable development of watershed ecosystems, water resources, and land management. The Soil and Water Assessment Tool was used to establish the regional model. The Min River watershed was divided into 236 sub‐basins, and simulations showed the spatial distribution of runoff in each sub‐basin with GIS‐based image displays. We set five scenarios to investigate the negative hydrological effects characterized by reductions in the water yield. From 1995 to 2004, the effect of simulated mean annual runoff caused by LUCC was −12.61 m3/s and the climate variability caused −67.61 m3/s. From 2005 to 2014, the hydrological effect caused by LUCC was −2.38 m3/s and the climate variability caused −58.53 m3/s. The elevation, Shannon's diversity index, largest patch index, and interspersion and juxtaposition index were all characterized by strong relationships with the sub‐basin outlet flows (adjusted R2 = 0.572) using multivariate stepwise regression analysis. Redundancy analysis further proved that the reduction in grassland has led to a decrease in vegetation dominance while large increase in cultivated and residential lands has led to a higher degree of landscape richness and fragmentation, which has caused the reduced water yield. The restoration of grassland vegetation, as well as urban and agricultural water usage should be the primary focus of flow recovery.
The Human Seroprevalence of Echinococcus Granulosus in Sulaimani Governorate

INTRODUCTION: Echinococcosis is a zoonotic disease that occurs throughout the world and causes economic losses and public health problems in many countries. Domestic intermediate hosts (sheep, goats, and cattle) are major reservoirs for the disease in humans (1) . Infection of humans occurs during the natural transmission of the parasite between the definitive hosts and domestic livestock intermediate host (2) . The disease is widespread globally. It causes a series of health problems for humans and animals in many countries in the world. Hydatidosis is one of the important and serious diseases in the world
Oxidative stress: development and progression of breast cancer:review article

the undisciplined growth of cells which inspires the development of tumors and initiates the progression of carcinogenesis. The im-portance of ROS on breast cancer development and etiology is being increasingly clarified. Nevertheless, fewer consideration has been given to the progress of redox system-targeted strategies for breast cancer treatment. Augmented oxidative stress caused by reactive species can diminish the body’s antioxidant defense against angiogenesis and metastasis in cancer cells. These processes are core factors in the development of cancer. Bimolecular reactions cause free radicals which create such compounds as malondialdehyde (MDA) and hydroxy-guanosine. These substances known as indicators of cancer. In this review, free radicals as oxidizing agents, antioxidants as the immune system, and the role of oxidative stress in cancer, particularly breast cancer, have been investigated by hope that better exploration of the factors involved in the occurrence and spread of cancer will improve the identification of treatment aims. o w l
Statistically Robust Evaluation of Stream-Based Recommender Systems

Online incremental models for recommendation are nowadays pervasive in both the industry and the academia. However, there is not yet a standard evaluation methodology for the algorithms that maintain such models. Moreover, online evaluation methodologies available in the literature generally fall short on the statistical validation of results, since this validation is not trivially applicable to stream-based algorithms. We propose a <inline-formula><tex-math notation="LaTeX">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href="vinagre-ieq1-2960216.gif"/></alternatives></inline-formula>-fold validation framework for the pairwise comparison of recommendation algorithms that learn from user feedback streams, using prequential evaluation. Our proposal enables continuous statistical testing on adaptive-size sliding windows over the outcome of the prequential process, allowing practitioners and researchers to make decisions in real time based on solid statistical evidence. We present a set of experiments to gain insights on the sensitivity and robustness of two statistical tests—McNemar’s and Wilcoxon signed rank—in a streaming data environment. Our results show that besides allowing a real-time, fine-grained online assessment, the online versions of the statistical tests are at least as robust as the batch versions, and definitely more robust than a simple prequential single-fold approach.
Impact of Smartphone Addiction on Students’ Academic Achievement in Higher Education Institute of Pakistan

The present study investigates the role of smartphone usage, self-regulation, general selfefficacy and cyber loafing on university student’s smartphone addiction and its impact on students’ academic achievements. The data has been collected from 453 students of a private sector higher education institute of Pakistan through an online questionnaire. The results of the study indicated that both smartphone usage and cyber loafing positively and significantly affects smartphone addiction. The effect of self-regulation was negative but significant on smartphone addiction and cyber loafing. Moreover, the effect of general selfefficacy on cyber loafing was positive and significant. However, smartphone addiction has no significant effect on student’s academic achievement. The findings conclude that smartphone addiction decreases academic performance of students as students lower their focus on academic learning and get addicted to smartphones for cyber loafing. Therefore, the universities should make policy regulations for students regarding the use of smartphones in the classroom. Also, students should be provided awareness about the negative impact of smartphone addiction on their personal and academic life, and also on their health through a variety of awareness seminars.