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Machine learning methods to predict and classify poverty.
No full textOne of the main objectives of the global endeavour to achieve sustainable development is the eradication of poverty. Poverty is still a major problem, with many people across the world continuing to live in poverty and suffering despite tremendous advancements over the years. Estimating and classifying poverty levels is crucial for developing sustainable development plans and efficient policies. Robust methods for deciphering complex socioeconomic data and identifying the underlying trends and factors that contribute to poverty are provided by machine learning techniques. This chapter examines several machine learning techniques used to forecast and classify poverty levels, with a focus on achieving Sustainable Development Goal 1: the worldwide eradication of poverty in all of its forms. The current developments in model selection, data pre-processing, and feature selection that are specialized for problems related to poverty prediction are also reviewed. We are also discussing the challenges of interpretability, scalability, and data quality that arise when using machine learning models for the categorization of poverty. Our objective is to construct a system that uses machine learning approaches to assist in the creation of a precise and scalable system that predicts and classifies poverty
COMPARATIVE ANALYSIS OF MFCC AND GTCC PERFORMANCE IN LARYNGEAL PATHOLOGY DETECTION BASED ON ELECTROGLOTTOGRAPHIC SIGNALS.
Get PDFIn the following paper, we analyse and compare the performance of Mel-Frequency Cepstral Coefficients (MFCC) and Gammatone Cepstral Coefficients (GTCC) in recognising the pathological patterns related to laryngeal disorders in electroglottographic signals. Furthermore, we investigate and compare the performance of two data types in laryngeal pathology detection; the bio-impedance measurements of sustained phonation and bio-impedance signals obtained during continuous speech. The ability of GTCC and MFCC to recognise pathological patterns in both types of bioimpedance signals is assessed using the designed CNN classifier. For both data types, the obtained results demonstrated that the GTCCs are superior in recognising pathological patterns in bioimpedance signals than MFCCs. Moreover, the speech data outperforms sustained phonation in detection of laryngeal pathologies. The achieved accuracy of the proposed CNN system with the application of the MFCCs derived from sustained phonation delivered 88.69% ±3.14 accuracy. In contrast, the proposed system fed GTCCs derived from speech delivered 95.95% ±1.25 accuracy
A Survey on AI-Driven Energy Optimization in Terrestrial Next Generation Radio Access Networks
Get PDFThis survey uncovers the tension between AI techniques designed for energy saving in
mobile networks and the energy demands those same techniques create. We compare modeling approaches
that estimate power usage cost of current commercial terrestrial next-generation radio access network
deployments. We then categorize emerging methods for reducing power usage by domain: time, frequency,
power, and spatial. Next, we conduct a timely review of studies that attempt to estimate the power usage
of the AI techniques themselves. We identify several gaps in the literature. Notably, real-world data for
the power consumption is difficult to source due to commercial sensitivity. Comparing methods to reduce
energy consumption is beyond challenging because of the diversity of system models and metrics. Crucially,
the energy cost of AI techniques is often overlooked, though some studies provide estimates of algorithmic
complexity or run-time. We find that extracting even rough estimates of the operational energy cost of AI
models and data processing pipelines is complex. Overall, we find the current literature hinders a meaningful
comparison between the energy savings from AI techniques and their associated energy costs. Finally,
we discuss future research opportunities to uncover the utility of AI for energy saving
Synergy Trap for Guardian Angels of DNA: Unraveling the Anticancer Potential of Phthalazinone -Thiosemicarbazone Hybrids through Dual PARP-1 and TOPO-I Inhibition
Get PDFTargeting DNA repair, like PARP-1 and TOPO-I, shows promise in cancer therapy. However, resistance to
single agents requires complex and costly combination strategies with significant side effects. Thus, there's an
urgent need for single agents with dual inhibition. Current dual inhibitors focusing on the C-4 position of the
phthalazinone core for PARP inhibition often have high molecular weights. Clinical use of PARP inhibitors is
limited by hematological and other toxicities from concurrent PARP-2 inhibition. They're mainly effective in
gynecological cancers, despite high PARP-1 and TOPO-I expression in various cancers. Moreover, their efficacy
is limited to BRCA1-expressing breast cancer. In this study, we synthesized 27 dual inhibitors for PARP-1 and
TOPO-I with molecular weights below 500 g/mol through hybridizing a phthalazinone core with a
thiosemicarbazone linker. Among these, 6c demonstrated exceptional broad spectrum and potency against the
NCI 60 cancer cell lines, with GI50 values from 1.65 to 5.63 µM. Notably, 6c exposed the highest PARP-1
inhibition (IC50 = 32.2 ± 3.26 nM) and a selectivity over PARP-2 (IC50 = 2844 ± 111 nM). Furthermore, 6c's
inhibition of TOPO-I (IC50 = 46.2 ± 3.3 nM) surpassed the control camptothecin by eleven-fold. Mechanistically,
6c disrupted the cell cycle at the S phase, induced apoptosis, and displayed a favorable safety profile against
normal cells. Compound 6c induced PARP trapping and synthetic lethality and showed high efficacy on BRCA1-
expressing cell lines. So, decreasing the likelihood of cancer cell resistance to chemotherapy. Drug-likeness
predictions and molecular modeling were also performed
Performance Mapping and Control; Enhanced Musical Connections and a Strategy to Optimise Flow-State
No full textThe technical act of routing and combining control signals from physical interfaces and mapping their parameters to a sound-generating device requires focus and attention to detail. This is at odds with the performative intention of achieving the state of flow described by Nakamura and Csikszentmihalyi (2014), which in improvisational performance and gaming vernacular is known as 'being in the zone' (Vyas, 2021). Parameter mapping occurs when a musician performs with a traditional MIDI keyboard, knobs or faders. Alternatively, a performance artist could use movement sensors, or a sound designer utilises a variety of controllers, or develops customised physical interfaces for performance control. The mappings define possibilities, dimensions, and limitations for creative interaction. This mapping process involves connecting tactile physical controls to specific and meaningful parameters within a given sound-generating construct. Parameter mapping both defines the interaction between humans and machines, and enables fluid and intentional performances. However, this logical mapping process is often tedious and time-consuming, and is incompatible with achieving and maintaining a creative flow state.
To better understand, and improve this technology, the researcher conducted interviews with practitioners using live MIDI control. After thematic analysis of the interviews, two key issues were revealed. First, practitioners typically deploy any control interface they possess or design, regardless of the quantity and style of physical controls and their direct compatibility with the target system. Second, practitioners do not want to reconfigure each new sound structure to provide compatibility with their performance apparatus. These interviews informed strategies to enhance the mapping flow between two different systems. The Kyma sound-design platform was used as a host to generate a dynamic set of sound structures that contain several varied control types. Max and a Node.js (JavaScript) server were used to map, combine, and route control signals to Kyma. These mappings could then be assigned, merged and swapped in real time without interrupting the sound processing or performance flow. This new system allowed performers and their directors to interact with the same sound structure, moving an offline logical configuration process toward a real-time reflexive, and creative act. This chapter demonstrates the emergent development of the system, and then extrapolates towards future possibilities of the system
Introduction
No full textThe Handbook of Sustainable Urban Tourism focuses on an important topic, sustainability in urban tourism destinations, an under-researched area of study that has recently started to receive more attention. This chapter highlights the role played by tourism in many urban destinations worldwide. As recognised by researchers and policy makers, tourism can contribute to an increase in local economic activities and tax revenues, job creation, improved standard of living for local people, better facilities, and infrastructure. If not well planned, however, it can lead to touristification of cities, overtourism, and tensions between residents and visitors, among other negative impacts associated with tourism development in cities. This is why scholars have highlighted the need for more research on sustainable tourism development in urban environments to help policy makers and the industry towards implementing better, more sustainable solutions. The Handbook thus responds to these calls and covers key challenges and issues in sustainable urban tourism, as well as contemporary debates related to research and practice in this field. Topics introduced in this chapter include urbanization and urban agglomerations, urban sustainability, city tourism and sustainable development, and several examples of best practice in sustainable tourism implementation in urban destinations. The chapter concludes by introducing the structure of the Handbook
Reflections on the Dramaturgy of a Foreigner
No full textIn this autoethnographic chapter, Filipina dramaturg and lecturer in the United Kingdom, Giselle Garcia, uses dramaturgy, a methodological tool in Theatre and Performance Studies, to understand and reflect on her experiences. Entering the United Kingdom as a Tier 4 visa student, she positions herself as an alien reader of its world. As she becomes enmeshed, she slowly becomes a character negotiating transition and transformation as an educator within its landscape
Starting GLP-1 therapy may induce impulse control disorders.
Get PDFGlucagon-like peptide 1 (GLP-1) agonists are being increasingly used globally. Clinical indications have expanded from treatment of diabetes and obesity with associated pathologies, to obese individuals without co-morbidities and more worryingly, are being used by non-obese media celebrities and “internet influencers” for rapid lifestyle weight loss.
Current warnings about GLP-1 agonists mainly relate to gut motility issues. Effects on cognition has received scant attention, with the few studies published focusing on longer term outcomes, rather than during the immediate phase of rapid weight loss.1 The authors of this article (a gastroenterologist and a psychiatrist) have become aware of individuals (not their patients) who have started on GLP-1 medication and made major life changing decisions regarding their domestic situation (such as divorce, house moves) within the first few months of starting treatment. Without knowing the details underlying these events, the rationale for some of them appears reckless. This led us to consider that starting GLP-1 agonists may result in cognitive changes in decision making through the combination of metabolic changes resulting from calorie deficit/rapid weight loss, in combination with direct effects of GLP-1 agonists on brain function
Numerical Investigation of Reinforced Concrete (RC) Columns Strengthened with Ultra-High-Performance Fiber-Reinforced Concrete (UHPFRC) Jackets
Get PDFThe strengthening of existing columns using additional reinforced concrete (RC) jackets is one of the most popular techniques for the enhancement of a column’s stiffness, load-bearing capacity and ductility. Important parameters affecting the effectiveness of this method are the strength of the additional concrete, concrete shrinkage and the connection between the old and the new concrete. In this study, the application of Ultra-High-Performance Fiber-Reinforced Concrete (UHPFRC) jackets for the structural upgrade of RC columns has been examined. Extensive numerical studies have been conducted to evaluate the effect of parameters such as the thickness of the jacket, concrete shrinkage and the addition of steel bars, and comparisons have been made with conventional RC jackets. The results of this study indicate that the use of UHPFRC can considerably improve the strength and the stiffness of existing reinforced concrete columns. The combination of UHPFRC and steel bars in the jacket leads to the most effective strengthening technique as a significant enhancement in the stiffness and the ultimate load capacity has been achieved
Surface Permittivity Estimation of Southern Utopia Planitia by High-Frequency RoPeR in Tianwen-1 Mars Exploration
Get PDFChina’s Tianwen-1 successfully landed in the southern Utopian Planitia of the Martian surface on 15 May 2021. The Zhurong Rover, equipped with a high-frequency full polarimetric Rover Penetrating Radar (RoPeR), traveled 1921 m to investigate the shallow geological structure and material composition of the Martian weathered layer. In this study, we propose a new processing strategy to estimate surface relative permittivity using the HH and VV reflections of the high-frequency RoPeR data. This new strategy is based on the induced field rotation (IFR) effect, which occurs when orthogonally polarized electromagnetic (EM) waves propagate into an uneven surface with incident angles. Three-dimensional time-domain finite-difference simulations were performed using random surfaces with various relative permittivities under the same geometry as the Zhurong Rover. Polarimetric alpha angle versus relative permittivity was then calculated based on the simulation results. At the same time, direct coupling (DC) removal, bandpass filtering, and channel calibration were performed on the real RoPeR data, and clear surface reflections were extracted. The surface reflection amplitudes of the HH and VV were then obtained and the polarimetric alpha angle was calculated. Finally, relative permittivity was estimated through the relationship obtained from the simulation results. The average value of the relative permittivity estimated by the proposed approach is 3.292, with a standard deviation of 0.235. This result is consistent with that obtained by orbiting radar systems and the low-frequency RoPeR system. This study will contribute to the further signal processing and accurate interpretation of real radar data captured by way of RoPeR
on Mars