Search results for: Black Lives Matter

Authors: Adeline Meriaux, Claire Gaiani, Jennifer Burgain, Frantz Fournier, Lionel Muniglia, Jérémy Petit

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Spray-drying process is widely used for the production of dairy powders for food and pharmaceuticals industries. It involves the atomization of a liquid feed into fine droplets, which are subsequently dried through contact with a hot air flow. The resulting powders permit transportation cost reduction and shelf life increase but can also exhibit various interesting functionalities (flowability, solubility, protein modification or acid gelation), depending on operating conditions and milk composition. Indeed, particles porosity, surface composition, lactose crystallization, protein denaturation, protein association or crust formation may change. Links between spray-drying conditions and physicochemical and functional properties of powders were investigated by a design of experiment methodology and analyzed by principal component analysis. Quadratic models were developed, and multicriteria optimization was carried out by the use of genetic algorithm. At the time of abstract submission, verification spray-drying trials are ongoing. To perform experiments, milk from dairy farm was collected, skimmed, froze and spray-dried at different air pressure (between 1 and 3 bars) and outlet temperature (between 75 and 95 °C). Dry matter, minerals content and proteins content were determined by standard method. Solubility index, absorption index and hygroscopicity were determined by method found in literature. Particle size distribution were obtained by laser diffraction granulometry. Location of the powder color in the Cielab color space and water activity were characterized by a colorimeter and an aw-value meter, respectively. Flow properties were characterized with FT4 powder rheometer; in particular, compressibility and shearing test were performed. Air pressure and outlet temperature are key factors that directly impact the drying kinetics and powder characteristics during spray-drying process. It was shown that the air pressure affects the particle size distribution by impacting the size of droplet exiting the nozzle. Moreover, small particles lead to more cohesive powder and less saturated color of powders. Higher outlet temperature results in lower moisture level particles which are less sticky and can explain a spray-drying yield increase and the higher cohesiveness; it also leads to particle with low water activity because of the intense evaporation rate. However, it induces a high hygroscopicity, thus, powders tend to get wet rapidly if they are not well stored. On the other hand, high temperature provokes a decrease of native serum proteins, which is positively correlated to gelation properties (gel point and firmness). Partial denaturation of serum proteins can improve functional properties of powder. The control of air pressure and outlet temperature during the spray-drying process significantly affects the physicochemical and functional properties of powder. This study permitted to better understand the links between physicochemical and functional properties of powder to identify correlations between air pressure and outlet temperature. Therefore, mathematical models have been developed, and the use of genetic algorithm will allow the optimization of powder functionalities.

Keywords: dairy powders, spray-drying, powders functionalities, design of experiment

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Authors: Sofia Quaglia, Carmine Di Martino, Brendan Tierney

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Artificial Intelligence (A.I.) constitutes various aspects of modern life, from the Machine Learning algorithms predicting the stocks on Wall streets to the killing of belligerents and innocents alike on the battlefield. Moreover, the end goal is to create autonomous A.I.; this means that the presence of humans in the decision-making process will be absent. The question comes naturally: when an A.I. does something wrong when its behavior is harmful to the community and its actions go against the law, which is to be held responsible? This research’s subject matter in A.I. and Robot Ethics focuses mainly on Robot Rights and its ultimate objective is to answer the questions: (i) What is the function of rights? (ii) Who is a right holder, what is personhood and the requirements needed to be a moral agent (therefore, accountable for responsibility)? (iii) Can an A.I. be a moral agent? (ontological requirements) and finally (iv) if it ought to be one (ethical implications). With the direction to answer this question, this research project was done via a collaboration between the School of Computer Science in the Technical University of Dublin that oversaw the technical aspects of this work, as well as the Department of Philosophy in the University of Milan, who supervised the philosophical framework and argumentation of the project. Firstly, it was found that all rights are positive and based on consensus; they change with time based on circumstances. Their function is to protect the social fabric and avoid dangerous situations. The same goes for the requirements considered necessary to be a moral agent: those are not absolute; in fact, they are constantly redesigned. Hence, the next logical step was to identify what requirements are regarded as fundamental in real-world judicial systems, comparing them to that of ones used in philosophy. Autonomy, free will, intentionality, consciousness and responsibility were identified as the requirements to be considered a moral agent. The work went on to build a symmetrical system between personhood and A.I. to enable the emergence of the ontological differences between the two. Each requirement is introduced, explained in the most relevant theories of contemporary philosophy, and observed in its manifestation in A.I. Finally, after completing the philosophical and technical analysis, conclusions were drawn. As underlined in the research questions, there are two issues regarding the assignment of moral agency to artificial agent: the first being that all the ontological requirements must be present and secondly being present or not, whether an A.I. ought to be considered as an artificial moral agent. From an ontological point of view, it is very hard to prove that an A.I. could be autonomous, free, intentional, conscious, and responsible. The philosophical accounts are often very theoretical and inconclusive, making it difficult to fully detect these requirements on an experimental level of demonstration. However, from an ethical point of view it makes sense to consider some A.I. as artificial moral agents, hence responsible for their own actions. When considering artificial agents as responsible, there can be applied already existing norms in our judicial system such as removing them from society, and re-educating them, in order to re-introduced them to society. This is in line with how the highest profile correctional facilities ought to work. Noticeably, this is a provisional conclusion and research must continue further. Nevertheless, the strength of the presented argument lies in its immediate applicability to real world scenarios. To refer to the aforementioned incidents, involving the murderer of innocents, when this thesis is applied it is possible to hold an A.I. accountable and responsible for its actions. This infers removing it from society by virtue of its un-usability, re-programming it and, only when properly functioning, re-introducing it successfully

Keywords: artificial agency, correctional system, ethics, natural agency, responsibility

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Authors: Mario Tauzene Afonso Matangue, Ivan Andres Sanchez Ortiz

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The Metropolitan area of Maputo (Mozambique Capital City) is located in semi-arid zone (800 mm annual rainfall) with 1101170 million inhabitants. On the west side, there are the flatlands of Infulene where the Mulauze River flows towards to the Indian Ocean, receiving at this site, the storm water contaminated with sanitary sewage from Maputo, transported through a concrete open channel. In Infulene, local communities grow salads crops such as tomato, onion, garlic, lettuce, and cabbage, which are then commercialized and consumed in several markets in Maputo City. Lettuce is the most daily consumed salad crop in different meals, generally in fast-foods, breakfasts, lunches, and dinners. However, the risk of infection by several pathogens due to the consumption of lettuce, using the Quantitative Microbial Risk Assessment (QMRA) tools, is still unknown since there are few studies or publications concerning to this matter in Mozambique. This work is aimed at determining the annual risk arising from the consumption of lettuce grown in Infulene valley, in Maputo, using QMRA tools. The exposure model was constructed upon the volume of contaminated water remaining in the lettuce leaves, the empirical relations between the number of pathogens and the indicator of microorganisms (E. coli), the consumption of lettuce (g) and reduction of pathogens (days). The reference pathogens were Vibrio cholerae, Cryptosporidium, norovirus, and Ascaris. The water quality samples (E. coli) were collected in the storm water channel from January 2016 to December 2018, comprising 65 samples, and the urban lettuce consumption data were collected through inquiry in Maputo Metropolis covering 350 persons. A non-parametric bootstrap was performed involving 10,000 iterations over the collected dataset, namely, water quality (E. coli) and lettuce consumption. The dose-response models were: Exponential for Cryptosporidium, Kummer Confluent hypergeomtric function (1F1) for Vibrio and Ascaris Gaussian hypergeometric function (2F1-(a,b;c;z) for norovirus. The annual infection risk estimates were performed using R 3.6.0 (CoreTeam) software by Monte Carlo (Latin hypercubes), a sampling technique involving 10,000 iterations. The annual infection risks values expressed by Median and the 95th percentile, per person per year (pppy) arising from the consumption of lettuce are as follows: Vibrio cholerae (1.00, 1.00), Cryptosporidium (3.91x10⁻³, 9.72x 10⁻³), nororvirus (5.22x10⁻¹, 9.99x10⁻¹) and Ascaris (2.59x10⁻¹, 9.65x10⁻¹). Thus, the consumption of the lettuce would result in greater risks than the tolerable levels ( < 10⁻³ pppy or 10⁻⁶ DALY) for all pathogens, and the Vibrio cholerae is the most virulent pathogens, according to the hit-single models followed by the Ascaris lumbricoides and norovirus. The sensitivity analysis carried out in this work pointed out that in the whole QMRA, the most important input variable was the reduction of pathogens (Spearman rank value was 0.69) between harvest and consumption followed by water quality (Spearman rank value was 0.69). The decision-makers (Mozambique Government) must strengthen the prevention measures related to pathogens reduction in lettuce (i.e., washing) and engage in wastewater treatment engineering.

Keywords: annual infections risk, lettuce, non-parametric bootstrapping, quantitative microbial risk assessment tools

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Authors: Sergio Celaschi, Henrique Canavarro de Alencar, Claaudecir Biazoli

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Effluent quality is of the highest priority for compliance with the permit limits of environmental protection agencies and ensures the protection of their local water system. Of the pollutants monitored, the biochemical oxygen demand (BOD) posed one of the greatest challenges. This work presents a solution for wastewater treatment plants - WWTP’s ability to react to different situations and meet treatment goals. Delayed BOD5 results from the lab take 7 to 8 analysis days, hindered the WWTP’s ability to react to different situations and meet treatment goals. Reducing BOD turnaround time from days to hours is our quest. Such a solution is based on a system of two BOD bioreactors associated with Digital Twin (DT) and Machine Learning (ML) methodologies via an Internet of Things (IoT) platform to monitor and control a WWTP to support decision making. DT is a virtual and dynamic replica of a production process. DT requires the ability to collect and store real-time sensor data related to the operating environment. Furthermore, it integrates and organizes the data on a digital platform and applies analytical models allowing a deeper understanding of the real process to catch sooner anomalies. In our system of continuous time monitoring of the BOD suppressed by the effluent treatment process, the DT algorithm for analyzing the data uses ML on a chemical kinetic parameterized model. The continuous BOD monitoring system, capable of providing results in a fraction of the time required by BOD5 analysis, is composed of two thermally isolated batch bioreactors. Each bioreactor contains input/output access to wastewater sample (influent and effluent), hydraulic conduction tubes, pumps, and valves for batch sample and dilution water, air supply for dissolved oxygen (DO) saturation, cooler/heater for sample thermal stability, optical ODO sensor based on fluorescence quenching, pH, ORP, temperature, and atmospheric pressure sensors, local PLC/CPU for TCP/IP data transmission interface. The dynamic BOD system monitoring range covers 2 mg/L < BOD < 2,000 mg/L. In addition to the BOD monitoring system, there are many other operational WWTP sensors. The CPU data is transmitted/received to/from the digital platform, which in turn performs analyses at periodic intervals, aiming to feed the learning process. BOD bulletins and their credibility intervals are made available in 12-hour intervals to web users. The chemical kinetics ML algorithm is composed of a coupled system of four first-order ordinary differential equations for the molar masses of DO, organic material present in the sample, biomass, and products (CO₂ and H₂O) of the reaction. This system is solved numerically linked to its initial conditions: DO (saturated) and initial products of the kinetic oxidation process; CO₂ = H₂0 = 0. The initial values for organic matter and biomass are estimated by the method of minimization of the mean square deviations. A real case of continuous monitoring of BOD wastewater effluent quality is being conducted by deploying an IoT application on a large wastewater purification system located in S. Paulo, Brazil.

Keywords: effluent treatment, biochemical oxygen demand, continuous monitoring, IoT, machine learning

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Authors: Aleksandras Velykis, Antanas Satkus

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Clay loam and clay soils are typical for northern Lithuania. These soils are susceptible to physical degradation in the case of intensive use of heavy machinery for field operations. However, clayey soils having poor physical properties by origin require more intensive tillage to maintain proper physical condition for grown crops. Therefore not only choice of suitable tillage system is very important for these soils in the region, but also additional search of other measures is essential for good soil physical state maintenance. Research objective: To evaluate the long-term effects of different intensity tillage as well as its combinations with supplementary agronomic practices on improvement of soil physical conditions and environmental sustainability. The experiment examined the influence of deep and shallow ploughing, ploughless tillage, combinations of ploughless tillage with incorporation of lime sludge and cover crop for green manure and application of the same cover crop for mulch without autumn tillage under spring and winter crop growing conditions on clay loam (27% clay, 50% silt, 23% sand) Endocalcaric Endogleyic Cambisol. Methods: The indicators characterizing the impact of investigated measures were determined using the following methods and devices: Soil dry bulk density – by Eijkelkamp cylinder (100 cm3), soil water content – by weighing, soil structure – by Retsch sieve shaker, aggregate stability – by Eijkelkamp wet sieving apparatus, soil mineral nitrogen – in 1 N KCL extract using colorimetric method. Results: Clay loam soil physical state (dry bulk density, structure, aggregate stability, water content) depends on tillage system and its combination with additional practices used. Application of cover crop winter mulch without tillage in autumn, ploughless tillage and shallow ploughing causes the compaction of bottom (15-25 cm) topsoil layer. However, due to ploughless tillage the soil dry bulk density in subsoil (25-35 cm) layer is less compared to deep ploughing. Soil structure in the upper (0-15 cm) topsoil layer and in the seedbed (0-5 cm), prepared for spring crops is usually worse when applying the ploughless tillage or cover crop mulch without autumn tillage. Application of lime sludge under ploughless tillage conditions helped to avoid the compaction and structure worsening in upper topsoil layer, as well as increase aggregate stability. Application of reduced tillage increased soil water content at upper topsoil layer directly after spring crop sowing. However, due to reduced tillage the water content in all topsoil markedly decreased when droughty periods lasted for a long time. Combination of reduced tillage with cover crop for green manure and winter mulch is significant for preserving the environment. Such application of cover crops reduces the leaching of mineral nitrogen into the deeper soil layers and environmental pollution. This work was supported by the National Science Program ‘The effect of long-term, different-intensity management of resources on the soils of different genesis and on other components of the agro-ecosystems’ [grant number SIT-9/2015] funded by the Research Council of Lithuania.

Keywords: clay loam, endocalcaric endogleyic cambisol, mineral nitrogen, physical state

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Authors: Andrew D. Henshaw, James M. Austin

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Introduction: Human trafficking is an increasingly serious transnational criminal enterprise and social security issue. Despite ongoing efforts to mitigate the phenomenon and a significant expansion of security scrutiny over past decades, it is not receding. This is true for many nations in Southeast Asia, widely recognized as the global hub for trafficked persons, including men, women, and children. Clearly, human trafficking is difficult to address because there are numerous drivers, causes, and motivators for it to persist, such as non-military and non-traditional security challenges, i.e., climate change, global warming displacement, and natural disasters. These make displaced persons and refugees particularly vulnerable. The issue is so large conservative estimates put a dollar value at around $150 billion-plus per year (Niethammer, 2020) spanning sexual slavery and exploitation, forced labor, construction, mining and in conflict roles, and forced marriages of girls and women. Coupled with corruption throughout military, police, and civil authorities around the world, and the active hands of powerful transnational criminal organizations, it is likely that such figures are grossly underestimated as human trafficking is misreported, under-detected, and deliberately obfuscated to protect those profiting from it. For example, the 2022 UN report on human trafficking shows a 56% reduction in convictions in that year alone (UNODC, 2022). Our Approach: To better understand this, our research utilizes a bespoke methodology. Applying a JAM (Juxtaposition Assessment Matrix), which we previously developed to detect flows of dark money around the globe (Henshaw, A & Austin, J, 2021), we now focus on the human trafficking paradigm. Indeed, utilizing a JAM methodology has identified key indicators of human trafficking not previously explored in depth. Being a set of structured analytical techniques that provide panoramic interpretations of the subject matter, this iteration of the JAM further incorporates behavioral and driver indicators, including the employment of Open-Source Artificial Intelligence (OS-AI) across multiple collection points. The extracted behavioral data was then applied to identify non-traditional indicators as they contribute to human trafficking. Furthermore, as the JAM OS-AI analyses data from the inverted position, i.e., the viewpoint of the traffickers, it examines the behavioral and physical traits required to succeed. This transposed examination of the requirements of success delivers potential leverage points for exploitation in the fight against human trafficking in a new and novel way. Findings: Our approach identified new innovative datasets that have previously been overlooked or, at best, undervalued. For example, the JAM OS-AI approach identified critical 'dark agent' lynchpins within human trafficking that are difficult to detect and harder to connect to actors and agents within a network. Our preliminary data suggests this is in part due to the fact that ‘dark agents’ in extant research have been difficult to detect and potentially much harder to directly connect to the actors and organizations in human trafficking networks. Our research demonstrates that using new investigative techniques such as OS-AI-aided JAM introduces a powerful toolset to increase understanding of human trafficking and transnational crime and illuminate networks that, to date, avoid global law enforcement scrutiny.

Keywords: human trafficking, open-source intelligence, transnational crime, human security, international human rights, intelligence analysis, JAM OS-AI, Dark Money

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Authors: Sanaz Alizadeh, Yves Comeau, Arshath Abdul Rahim, Sunhasis Ghoshal

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The application of silver nanoparticles (AgNPs) in personal care products, various household and industrial products has resulted in an inevitable environmental exposure of such engineered nanoparticles (ENPs). Ag ENPs, released via household and industrial wastes, reach water resource recovery facilities (WRRFs), yet the fate and transport of ENPs in WRRFs and their potential risk in the biological wastewater processes are poorly understood. Accordingly, our main objective was to elucidate the impact of long-term continuous exposure to AgNPs on biological activity of aerobic wastewater biofilm. The fate, transport and toxicity of 10 μg.L-1and 100 μg.L-1 PVP-stabilized AgNPs (50 nm) were evaluated in an attached growth biological treatment process, using lab-scale moving bed bioreactors (MBBRs). Two MBBR systems for organic matter removal were fed with a synthetic influent and operated at a hydraulic retention time (HRT) of 180 min and 60% volumetric filling ratio of Anox-K5 carriers with specific surface area of 800 m2/m3. Both reactors were operated for 85 days after reaching steady state conditions to develop a mature biofilm. The impact of AgNPs on the biological performance of the MBBRs was characterized over a period of 64 days in terms of the filtered biodegradable COD (SCOD) removal efficiency, the biofilm viability and key enzymatic activities (α-glucosidase and protease). The AgNPs were quantitatively characterized using single-particle inductively coupled plasma mass spectroscopy (spICP-MS), determining simultaneously the particle size distribution, particle concentration and dissolved silver content in influent, bioreactor and effluent samples. The generation of reactive oxygen species and the oxidative stress were assessed as the proposed toxicity mechanism of AgNPs. Results indicated that a low concentration of AgNPs (10 μg.L-1) did not significantly affect the SCOD removal efficiency whereas a significant reduction in treatment efficiency (37%) was observed at 100 μg.L-1AgNPs. Neither the viability nor the enzymatic activities of biofilm were affected at 10 μg.L-1AgNPs but a higher concentration of AgNPs induced cell membrane integrity damage resulting in 31% loss of viability and reduced α-glucosidase and protease enzymatic activities by 31% and 29%, respectively, over the 64-day exposure period. The elevated intercellular ROS in biofilm at a higher AgNPs concentration over time was consistent with a reduced biological biofilm performance, confirming the occurrence of a nanoparticle-induced oxidative stress in the heterotrophic biofilm. The spICP-MS analysis demonstrated a decrease in the nanoparticles concentration over the first 25 days, indicating a significant partitioning of AgNPs into the biofilm matrix in both reactors. The concentration of nanoparticles increased in effluent of both reactors after 25 days, however, indicating a decreased retention capacity of AgNPs in biofilm. The observed significant detachment of biofilm also contributed to a higher release of nanoparticles due to cell-wall destabilizing properties of AgNPs as an antimicrobial agent. The removal efficiency of PVP-AgNPs and the biofilm biological responses were a function of nanoparticle concentration and exposure time. This study contributes to a better understanding of the fate and behavior of AgNPs in biological wastewater processes, providing key information that can be used to predict the environmental risks of ENPs in aquatic ecosystems.

Keywords: biofilm, silver nanoparticle, single particle ICP-MS, toxicity, wastewater

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Authors: Kartik Gupta, Virendra Kumar, Sanjeev Sinha, N. Jagannathan

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Introduction: A significant number of patients having human immunodeficiency virus (HIV) infection show a neurocognitive decline (NCD) ranging from minor cognitive impairment to severe dementia. The possible causes of NCD in HIV-infected patients include brain injury by HIV before cART, neurotoxic viral proteins and metabolic abnormalities. In the present study, we compared the level of NCD in asymptomatic HIV-infected patients with changes in brain metabolites measured by using magnetic resonance spectroscopy (MRS). Methods: 43 HIV-positive patients (30 males and 13 females) coming to ART center of the hospital and HIV-seronegative healthy subjects were recruited for the study. All the participants completed MRI and MRS examination, detailed clinical assessments and a battery of neuropsychological tests. All the MR investigations were carried out at 3.0T MRI scanner (Ingenia/Achieva, Philips, Netherlands). MRI examination protocol included the acquisition of T2-weighted imaging in axial, coronal and sagittal planes, T1-weighted, FLAIR, and DWI images in the axial plane. Patients who showed any apparent lesion on MRI were excluded from the study. T2-weighted images in three orthogonal planes were used to localize the voxel in left frontal lobe white matter (FWM) and left basal ganglia (BG) for single voxel MRS. Single voxel MRS spectra were acquired with a point resolved spectroscopy (PRESS) localization pulse sequence at an echo time (TE) of 35 ms and a repetition time (TR) of 2000 ms with 64 or 128 scans. Automated preprocessing and determination of absolute concentrations of metabolites were estimated using LCModel by water scaling method and the Cramer-Rao lower bounds for all metabolites analyzed in the study were below 15\%. Levels of total N-acetyl aspartate (tNAA), total choline (tCho), glutamate + glutamine (Glx), total creatine (tCr), were measured. Cognition was tested using a battery of tests validated for Indian population. The cognitive domains tested were the memory, attention-information processing, abstraction-executive, simple and complex perceptual motor skills. Z-scores normalized according to age, sex and education standard were used to calculate dysfunction in these individual domains. The NCD was defined as dysfunction with Z-score ≤ 2 in at least two domains. One-way ANOVA was used to compare the difference in brain metabolites between the patients and healthy subjects. Results: NCD was found in 23 (53%) patients. There was no significant difference in age, CD4 count and viral load between the two groups. Maximum impairment was found in the domains of memory and simple motor skills i.e., 19/43 (44%). The prevalence of deficit in attention-information processing, complex perceptual motor skills and abstraction-executive function was 37%, 35%, 33% respectively. Subjects with NCD had a higher level of Glutamate in the Frontal region (8.03 ± 2.30 v/s. 10.26 ± 5.24, p-value 0.001). Conclusion: Among newly diagnosed, ART-naïve retroviral disease patients from India, cognitive decline was found in 53\% patients using tests validated for this population. Those with neurocognitive decline had a significantly higher level of Glutamate in the left frontal region. There was no significant difference in age, CD4 count and viral load at initiation of ART between the two groups.

Keywords: HIV, neurocognitive decline, neurometabolites, magnetic resonance spectroscopy

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Authors: Robert E. Kenney, Efrain Antunez, Samuel Nodal, Ameer Malik, Richard B. Aguilar

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Physician burnout has gained much attention during the COVID pandemic. After-hours workload, HCC coding, HEDIS metrics, and clinical documentation negatively impact career satisfaction. These and other influences have increased the rate of physicians leaving the workforce. In addition, roughly 1% of the entire physician workforce will be retiring earlier than expected based on pre-pandemic trends. The two Medical Specialties with the highest rates of burnout are Family Medicine and Primary Care. With a predicted shortage of primary care physicians looming, the need to address physician burnout is crucial. Commonly reported issues leading to clinician burnout are clerical documentation requirements, increased time working on Electronic Health Records (EHR) after hours, and a decrease in work-life balance. Clinicians experiencing burnout with physical and emotional exhaustion are at an increased likelihood of providing lower quality and less efficient patient care. This may include a lack of suitable clinical documentation, medication reconciliation, clinical assessment, and treatment plans. While the annual baseline turnover rates of physicians hover around 6-7%, the COVID pandemic profoundly disrupted the delivery of healthcare. A report found that 43% of physicians switched jobs during the initial two years of the COVID pandemic (2020 and 2021), tripling the expected average annual rate to 21.5 %/yr. During this same time, an average of 4% and 1.5% of physicians retired or left the workforce for a non-clinical career, respectively. The report notes that 35.2% made career changes for a better work-life balance and another 35% reported the reason as being unhappy with their administration’s response to the pandemic. A physician-led primary care-focused health organization, Cano Health (CH), based out of Florida, sought to preemptively address this problem by implementing several supportive measures. Working with >120 clinics and >280 PCPs from Miami to Tampa and Orlando, managing nearly 120,000 Medicare Advantage lives, CH implemented a number of changes to assist with the clinician’s workload. Supportive services such as after hour and home visits by APRNs, in-clinic care managers, and patient educators were implemented. In 2021, assistive Artificial Intelligence Software (AIS) was integrated into the EHR platform. This AIS converts free text within PDF files into a usable (copy-paste) format facilitating documentation. The software also systematically and chronologically organizes clinical data, including labs, medical records, consultations, diagnostic images, medications, etc., into an easy-to-use organ system or chronic disease state format. This reduced the excess time and documentation burden required to meet payor and CMS guidelines. A clinician Documentation Support team was employed to improve the billing/coding performance. The effects of these newly designed workflow interventions were measured via analysis of clinician turnover from CH’s hiring and termination reporting software. CH’s annualized average clinician turnover rate in 2020 and 2021 were 17.7% and 12.6%, respectively. This represents a 30% relative reduction in turnover rate compared to the reported national average of 21.5%. Retirement rates during both years were 0.1%, demonstrating a relative reduction of >95% compared to the national average (4%). This model successfully promoted the retention of clinicians in a Value-Based Care setting.

Keywords: clinician burnout, COVID-19, value-based care, burnout, clinician retirement

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Authors: Ayesha Selwyn, Annapoorni Chandrashekar, Kumar Ashwarya, Nishant Baghel

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Project-based learning (PBL) activities are typically implemented in technology-enabled schools by highly trained teachers. In rural India, students have limited access to technology and quality education. Implementing typical PBL activities is challenging. This study details how Pratham Education Foundation’s Hybrid Learning model was used to implement two PBL activities related to music in 900 remote Indian villages with 46,000 students aged 10-14. The activities were completed by 69% of groups that submitted a total of 15,000 videos (completed projects). Pratham’s H-Learning model reaches 100,000 students aged 3-14 in 900 Indian villages. The community-driven model engages students in 20,000 self-organized groups outside of school. The students are guided by 6,000 youth volunteers and 100 facilitators. The students partake in learning activities across subjects with the support of community stakeholders and offline digital content on shared Android tablets. A training and implementation toolkit for PBL activities is designed by subject experts. This toolkit is essential in ensuring efficient implementation of activities as facilitators aren’t highly skilled and have limited access to training resources. The toolkit details the activity at three levels of student engagement - enrollment, participation, and completion. The subject experts train project leaders and facilitators who train youth volunteers. Volunteers need to be trained on how to execute the activity and guide students. The training is focused on building the volunteers’ capacity to enable students to solve problems, rather than developing the volunteers’ subject-related knowledge. This structure ensures that continuous intervention of subject matter experts isn’t required, and the onus of judging creativity skills is put on community members. 46,000 students in the H-Learning program were engaged in two PBL activities related to Music from April-June 2019. For one activity, students had to conduct a “musical survey” in their village by designing a survey and shooting and editing a video. This activity aimed to develop students’ information retrieval, data gathering, teamwork, communication, project management, and creativity skills. It also aimed to identify talent and document local folk music. The second activity, “Pratham Idol”, was a singing competition. Students participated in performing, producing, and editing videos. This activity aimed to develop students’ teamwork and creative skills and give students a creative outlet. Students showcased their completed projects at village fairs wherein a panel of community members evaluated the videos. The shortlisted videos from all villages were further evaluated by experts who identified students and adults to participate in advanced music workshops. The H-Learning framework enables students in low resource settings to engage in PBL and develop relevant skills by leveraging community support and using video creation as a tool. In rural India, students do not have access to high-quality education or infrastructure. Therefore designing activities that can be implemented by community members after limited training is essential. The subject experts have minimal intervention once the activity is initiated, which significantly reduces the cost of implementation and allows the activity to be implemented at a massive scale.

Keywords: community supported learning, project-based learning, self-organized learning, education technology

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Authors: T. Schilirò, S. Bonetta, S. Bonetta, E. Ceretti, D. Feretti, I. Zerbini, V. Romanazzi, S. Levorato, T. Salvatori, S. Vannini, M. Verani, C. Pignata, F. Bagordo, G. Gilli, S. Bonizzoni, A. Bonetti, E. Carraro, U. Gelatti

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Air pollution is one of the most important worldwide health concern. In the last years, in both the US and Europe, new directives and regulations supporting more restrictive pollution limits were published. However, the early effects of air pollution occur, especially for the urban population. Several epidemiological and toxicological studies have documented the remarkable effect of particulate matter (PM) in increasing morbidity and mortality for cardiovascular disease, lung cancer and natural cause mortality. The finest fractions of PM (PM with aerodynamic diameter <2.5 µm and less) play a major role in causing chronic diseases. The International Agency for Research on Cancer (IARC) has recently classified air pollution and fine PM as carcinogenic to human (1 Group). The structure and composition of PM influence the biological properties of particles. The chemical composition varies with season and region of sampling, photochemical-meteorological conditions and sources of emissions. The aim of the MAPEC (Monitoring Air Pollution Effects on Children for supporting public health policy) study is to evaluate the associations between air pollution and biomarkers of early biological effects in oral mucosa cells of 6-8 year old children recruited from first grade schools. The study was performed in five Italian towns (Brescia, Torino, Lecce, Perugia and Pisa) characterized by different levels of airborne PM (PM10 annual average from 44 µg/m3 measured in Torino to 20 µg/m3 measured in Lecce). Two to five schools for each town were chosen to evaluate the variability of pollution within the same town. Child exposure to urban air pollution was evaluated by collecting ultrafine PM (PM0.5) in the school area, on the same day of biological sampling. PM samples were collected for 72h using a high-volume gravimetric air sampler and glass fiber filters in two different seasons (winter and spring). Gravimetric analysis of the collected filters was performed; PM0.5 organic extracts were chemically analyzed (PAH, Nitro-PAH) and tested on A549 by the Comet assay and Micronucleus test and on Salmonella strains (TA100, TA98, TA98NR and YG1021) by Ames test. Results showed that PM0.5 represents a high variable PM10 percentage (range 19.6-63%). PM10 concentration were generally lower than 50µg/m3 (EU daily limit). All PM0.5 extracts showed a mutagenic effect with TA98 strain (net revertant/m3 range 0.3-1.5) and suggested the presence of indirect mutagens, while lower effect was observed with TA100 strain. The results with the TA98NR and YG1021 strains showed the presence of nitroaromatic compounds as confirmed by the chemical analysis. No genotoxic or oxidative effect of PM0.5 extracts was observed using the comet assay (with/without Fpg enzyme) and micronucleus test except for some sporadic samples. The low biological effect observed could be related to the low level of air pollution observed in this winter sampling associated to a high atmospheric instability. For a greater understanding of the relationship between PM size, composition and biological effects the results obtained in this study suggest to investigate the biological effect of the other PM fractions and in particular of the PM0.5-1 fraction.

Keywords: airborne PM, ames test, comet assay, micronucleus test

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Authors: Tatiana Rizova

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The migrant crisis, which peaked in 2015-2016, posed an unprecedented challenge to the European Union’s (EU) newest member states, including Bulgaria and Hungary. Their governments had to formulate sound migration policies with expediency and sensitivity to the needs of millions of people fleeing violent conflicts in the Middle East and failed states in North Africa. Political leaders in post-communist countries had to carefully coordinate with other EU member states on joint policies and solutions while minimizing the risk of alienating their increasingly anti-migrant domestic constituents. Post-communist member states’ governments chose distinct policy responses to the crisis, which were dictated by factors such as their governments’ partisan stances on migration, their views of the European Union, and the decision to frame the crisis as a security or a humanitarian issue. This paper explores how two Bulgarian governments (Boyko Borisov’s second and third government formed during the 43rd and 44th Bulgarian National Assembly, respectively) navigated the processes of EU migration policy making and managing the expectations of their electorates. Based on a comparative analysis of refugee policies in Bulgaria and Hungary during the height of the crisis (2015-2016) and a temporal analysis of refugee policies in Bulgaria (2015-2018), the paper advances the following conclusions. Drawing on insights of the Copenhagen school of security studies, the paper argues that cultural concerns dominated domestic debates in both Bulgaria and Hungary; both governments framed the issue predominantly as a matter of security rather than humanitarian disaster. Regardless of the similarities in issue framing, however, the two governments sought different paths of tackling the crisis. While the Bulgarian government demonstrated its willingness to comply with EU decisions (such as the proposal for mandatory quotas for refugee relocation), the Hungarian government defied EU directives and became a leading voice of dissent inside the EU. The current Bulgarian government (April 2017 - present) appears to be committed to complying with EU decisions and accepts the strategy of EU burden-sharing, while the Hungarian government has continually snubbed the EU’s appeals for cooperation despite the risk of hefty financial penalties. Hungary’s refugee policies have been influenced by the parliamentary representation of the far right-wing party Movement for a Better Hungary (Jobbik), which has encouraged the majority party (FIDESZ) to adopt harsher anti-migrant rhetoric and more hostile policies toward refugees. Bulgaria’s current government is a coalition of the center-right Citizens for a European Development of Bulgaria (GERB) and its far right-wing junior partners – the United Patriots (comprised of three nationalist political parties). The parliamentary presence of Jobbik in Hungary’s parliament has magnified the anti-migrant stance, rhetoric, and policies of Mr. Orbán’s Civic Alliance; we have yet to observe a substantial increase in the anti-migrant rhetoric and policies in Bulgaria’s case. Analyzing responses to the migrant/refugee crisis is a critical opportunity to understand how issues of cultural identity and belonging, inclusion and exclusion, regional integration and disintegration are debated and molded into policy in Europe’s youngest member states in the broader EU context.

Keywords: Copenhagen School, migrant crisis, refugees, security

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Authors: Jonas Volungevicius, Kristina Amaleviciute, Rimantas Vaisvalavicius, Alvyra Slepetiene, Darijus Veteikis

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Lithuanian territory is characterized by landscape with prevailing morain hills and clayey lowlands. The largest part of it has endured agrogenization of various degrees which was the cause of changes both in the structure of landscape and soil cover, transformations of soil profile and degradation of natural background soils. These changes influence negatively geoecological potential of landscape and soil and contribute to the weakening of the sustainability of agroecosystems. Research objective: to reveal the landscape agrogenization induced alterations of catenae and their appendant soil profiles in Lithuanian morain hills and clayey lowlands. Methods: Soil cover analysis and catenae charting was conducted using landscape profiling; soil morphology detected and soil type identified following WRB 2014. Granulometric composition of soil profiles was obtained by laser diffraction method (lazer diffractometer Mastersizer 2000). pH was measured in H2O extraction using potentiometric titration; SOC was determined by the Tyurin method modified by Nikitin, measuring with spectrometer Cary 50 (VARIAN) in 590 nm wavelength using glucose standards. Results: analysis showed that the decrease of forest vegetation and the other natural landscape components following the agrogenization of the research area influenced differently but significantly the structural alterations in soil cover and vertical soil profile. The research detected that due to landscape agrogenization, the suppression of zone-specific processes and the intensification of inter-zone processes determined by agrogenic factors take place in Lithuanian agroecosystems. In forested hills historically prevailing Retisols and Histosols territorial complex is transforming into the territorial complex of Regosols, Deluvial soils and drained Histosols. Processes taking place are simplification of vertical profile structure, intensive rejuvenation of profile, disappearance of the features of zone-specific soil-forming processes (podzolization, lessivage, gley formation). Erosion and deluvial processes manifest more intensively and weakly accumulating organic material more intensively spread in a vertical soil profile. The territorial soil complex of Gleyic Luvisols and Gleysols dominating in forested clayey lowlands subjected to agrogenization is transformed into the catena of drained Luvisols and pseudo Cambisols. The best expressed are their changes in moisture regime (morphological features of gley and stagnic properties are on decline) together with alterations of pH and distribution and intensity of accumulation of organic matter in profile. A specific horizon, antraquic, uncharacteristic to natural soil formation is appearing. Important to note that due to deep ploughing and other agrotechnical measures, the natural vertical differentiation of clay particles in a soil profile is destroyed which leads not only to alterations of physical qualities of soil, but also encumbers the identification of Luvisols by creating presumptions to misidentify them as Cambisols. The latter have never developed in these ecosystems under the present climatic conditions. Acknowledgements: This work was supported by the National Science Program: The effect of long-term, different-intensity management of resources on the soils of different genesis and on other components of the agro-ecosystems [grant number SIT-9/2015] funded by the Research Council of Lithuania.

Keywords: agroecosystems, landscape agrogenization, luvisols, retisols, transformation of soil profile

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Authors: Shatarupa Thakurta Roy

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Along the limelight of mainstream academic practices in Indian art, exist a significant lot of habitual art practices that are mutually susceptible in their contemporary forms. Narrative folk paintings of regional India has successfully dispersed to its audience social messages through pulsating pictures and orations. The paper consists of images from narrative scroll paintings on ‘Ramayana’ theme from various neighboring states as well as districts in India, describing their subtle differences in style of execution, method, and use of material. Despite sharing commonness in the choice of subject matter, habitual and ceremonial Indian folk art in its formative phase thrived within isolated locations to yield in remarkable variety in the art styles. The differences in style took place district wise, cast wise and even gender wise. An open flow is only evident in the contemporary expressions as a result of substantial changes in social structures, mode of communicative devices, cross-cultural exposures and multimedia interactivities. To decipher the complex nature of popular cultural taste of contemporary India it is important to categorically identify its root in vernacular symbolism. The realization of modernity through European primitivism was rather elevated as a perplexed identity in Indian cultural margin in the light of nationalist and postcolonial ideology. To trace the guiding factor that has still managed to obtain ‘Indianness’ in today’s Indian art, researchers need evidences from the past that are yet to be listed in most instances. They are commonly created on ephemeral foundations. The artworks are also found in endangered state and hence, not counted much friendly for frequent handling. The museums are in dearth of proper technological guidelines to preserve them. Even though restoration activities are emerging in the country, the existing withered and damaged artworks are in threat to perish. An immediacy of digital achieving is therefore envisioned as an alternative to save this cultural legacy. The method of this study is, two folded. It primarily justifies the richness of the evidences by conducting categorical aesthetic analysis. The study is supported by comments on the stylistic variants, thematic aspects, and iconographic identities alongside its anthropological and anthropomorphic significance. Further, it explores the possible ways of cultural preservation to ensure cultural sustainability that includes technological intervention in the form of digital transformation as an altered paradigm for better accessibility to the available recourses. The study duly emphasizes on visual description in order to culturally interpret and judge the rare visual evidences following Feldman’s four-stepped method of formal analysis combined with thematic explanation. A habitual design that emerges and thrives within complex social circumstances may experience change placing its principle philosophy at risk by shuffling and altering with time. A tradition that respires in the modern setup struggles to maintain timeless values that operate its creative flow. Thus, the paper hypothesizes the survival and further growth of this practice within the dynamics of time and concludes in realization of the urgency to transform the implicitness of its knowledge into explicit records.

Keywords: aesthetic, identity, implicitness, paradigm

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Authors: Mary Isobelle Mullaney

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The maxim "an unexamined life is not worth living," attributed to Socrates, prompts a contemplative reflection spanning over 32 years as a teacher educator in the Republic of Ireland. Taking time to contemplate the changes that have occurred and the current landscape provides valuable insights into the dynamic terrain of teacher preparation. The reflective journey traverses the impacts of global and societal shifts, responding to challenges, embracing advancements, and navigating the delicate balance between responsiveness to the world and the active shaping of it. The transformative events of the COVID-19 pandemic spotlighted the indispensable role of teachers in Ireland, reinforcing the critical nature of education for the well-being of pupils. Research solidifies the understanding that teachers matter and so it is worth exploring the pivotal role of the teacher educator. This reflective piece examines the changes in teacher education and explores the juxtapositions that have emerged in response to three decades of profound change. The attractiveness of teaching as a career is juxtaposed against the reality of the demands of the job, with conditions for public servants in Ireland undergoing a shift. High-level strategic discussions about increasing teacher numbers now contrast with a previous oversupply. The delicate balance between the imperative to increase enrolment (getting "bums on seats") and the gatekeeper role of teacher educators is explored, raising questions about maintaining high standards amid changing student profiles. Another poignant dichotomy involves the high demand for teachers versus the hurdles candidates face in becoming teachers. The rising cost and duration of teacher education courses raise concerns about attracting quality candidates. The perceived attractiveness of teaching as a career contends with the reality of increased demands on educators. One notable juxtaposition centres around the rapid evolution of Irish initial teacher education versus the potential risk of change overload. The Teaching Council of Ireland has spearheaded considerable changes, raising questions about the timing and evaluation of these changes. This reflection contemplates the vision of a professional teaching council versus its evolving reality and the challenges posed by the value placed on school placement in teacher preparation. The juxtapositions extend to the classroom, where theory may not seamlessly align with the lived experience. Inconsistencies between college expectations and the classroom reality prompt reflection on the effectiveness of teacher preparation programs. Addressing the changing demographic landscape of society and schools, there is a persistent incongruity between the diversity of Irish society and the profile of second-level teachers. As education undergoes a digital revolution, the enduring philosophies of education confront technological advances. This reflection highlights the tension between established practices and contemporary demands, acknowledging the irreplaceable value of face-to-face interaction while integrating technology into teacher training programs. In conclusion, this reflective journey encapsulates the intricate web of juxtapositions in Irish Initial Teacher Education. It emphasises the enduring commitment to fostering education, recognising the profound influence educators wield, and acknowledging the challenges and gratifications inherent in shaping the minds and futures of generations to come.

Keywords: Irish post primary teaching, juxtapositions, reflection, teacher education

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Authors: Abbas Ahmadi, Nasser Aliasgharzad, Ali Asghar Jafarzadeh

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Nowadays, drying of the Urmia Lake as a largest saline lake in the world and emerging its saline bed from water has caused the risk of salty dune storms, which threats the health of human society and also plants and animal communities living in the region. Biological soil crusts (BSCs) as a dust stabilizer attracted the attention of Soil conservation experts in recent years. Although the presence of water by the impenetrable lake bed and endorheic basin can be an advantage to create BSCs, but the extraordinary of the lake bed salinity is a factor for prevention of its establishment in the region. Therefore, the present research work has been carried out to investigate the effects of inoculating the Cyanobacteria, algae and their combination to create BSCs for dust control. In this study, an algae attributed to Chlamydomonas sp and a cyanobacteria attributed to Anabaena sp isolated from the soils of Urmia Lake margin were used to create BSC in four soil samples which collected from 0-10 cm of the current margin (A), the previous bed (B), affected lands by lake (C) and Quomtappe sand dune (D). The main characteristics of the A, B and C soil samples are their highly salinity (their ECe are 108, 140 and 118 dS/m, respectively) and sodicity. Also, texture class of the soil A was loamy sand, and other two soils had clay textures. Soil D was Non-saline, but it was sodic with a sandy texture class. This study was conducted separately in each soil in a completely randomized design under four inoculation treatments of non-inoculated (T0), Algae (T1), cyanobacteria (T2) and equal mixture of algae and cyanobacteria (T3) with three replications. In the experiment, the soil was placed into wind tunnel trays, and a suspension containing microorganisms mixed with the trays surface soil. During the experiment, water was sprayed to the trays at the morning and evening of every day. After passing the incubation period (30 days), some characteristics of samples such as pH, EC, cold water extractable carbohydrate (CWEC), hot water extractable carbohydrate (HWEC), sulfuric acid extractable carbohydrate (SAEC), organic matter, crust thickness, penetration resistance, wind erosion threshold velocity and soil loss in the wind tunnel were measured, and Correlation between the measured characteristics was obtained through the SPSS software. Analysis of variance and so comparison between the means of treatments were analyzed with MSTATC software. In this research, Chlorophyll, an amount, was used as an indicator of the microorganism's population in the samples. Based on obtained results, the amount of Chlorophyll a in the T2 treatment of soil A and all treatments of soil D was significantly increased in comparison to the control and crust thickness showed increase in all treatments by microorganism’s inoculation. But effect of the treatments was significant in soils A and D. At all treatment’s inoculation of microorganisms in soil A caused to increase %46, %34 and %55 of the wind erosion threshold velocity in T1, T2 and T3 treatments in comparison to the control, respectively, and in soil D all treatments caused wind erosion threshold velocity became two times more than control. However, soil loss in the wind tunnel experiments was significant in T2 and T3 treatments of these soils and T1 treatment had no effect in reducing soil loss. Correlation between Chlorophyll a and salinity shows the important role of salinity in microbial growth prevention and formation of BSCs in the studied samples. In general, according to the obtained results, it can be concluded that salinity reduces the growth of microorganisms in saline soils of the region, and in soils with fine textures, salinity role in prevention of the microbial growth is clear. Also, using the mix of algae and cyanobacteria together caused the synergistic growth of them and consequently, better protection of the soil against wind erosion was provided.

Keywords: wind erosion, algae, cyanobacteria, carbohydrate

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Authors: Jessica Ho

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AI has helped government, businesses and industries transform the way they do things. AI is used in automating tasks to improve decision-making and efficiency. AI is embedded in sensors and used in automation to help save time and eliminate human errors in repetitive tasks. Today, we saw the growth in AI using the collection of vast amounts of data to forecast with greater accuracy, inform decision-making, adapt to changing market conditions and offer more personalised service based on consumer habits and preferences. Government around the world share the opportunity to leverage these disruptive technologies to improve productivity while reducing costs. In addition, these intelligent solutions can also help streamline government processes to deliver more seamless and intuitive user experiences for employees and citizens. This is a critical challenge for NSW Government as we are unable to determine the risk that is brought by the unprecedented pace of adoption of AI solutions in government. Government agencies must ensure that their use of AI complies with relevant laws and regulatory requirements, including those related to data privacy and security. Furthermore, there will always be ethical concerns surrounding the use of AI, such as the potential for bias, intellectual property rights and its impact on job security. Within NSW’s public sector, agencies are already testing AI for crowd control, infrastructure management, fraud compliance, public safety, transport, and police surveillance. Citizens are also attracted to the ease of use and accessibility of AI solutions without requiring specialised technical skills. This increased accessibility also comes with balancing a higher risk and exposure to the health and safety of citizens. On the other side, public agencies struggle with keeping up with this pace while minimising risks, but the low entry cost and open-source nature of generative AI led to a rapid increase in the development of AI powered apps organically – “There is an AI for That” in Government. Other challenges include the fact that there appeared to be no legislative provisions that expressly authorise the NSW Government to use an AI to make decision. On the global stage, there were too many actors in the regulatory space, and a sovereign response is needed to minimise multiplicity and regulatory burden. Therefore, traditional corporate risk and governance framework and regulation and legislation frameworks will need to be evaluated for AI unique challenges due to their rapidly evolving nature, ethical considerations, and heightened regulatory scrutiny impacting the safety of consumers and increased risks for Government. Creating an effective, efficient NSW Government’s governance regime, adapted to the range of different approaches to the applications of AI, is not a mere matter of overcoming technical challenges. Technologies have a wide range of social effects on our surroundings and behaviours. There is compelling evidence to show that Australia's sustained social and economic advancement depends on AI's ability to spur economic growth, boost productivity, and address a wide range of societal and political issues. AI may also inflict significant damage. If such harm is not addressed, the public's confidence in this kind of innovation will be weakened. This paper suggests several AI regulatory approaches for consideration that is forward-looking and agile while simultaneously fostering innovation and human rights. The anticipated outcome is to ensure that NSW Government matches the rising levels of innovation in AI technologies with the appropriate and balanced innovation in AI governance.

Keywords: artificial inteligence, machine learning, rules, governance, government

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Authors: Mireille Elhajj, Washington Ochieng, Deeph Chana

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The challenges of the rapid growth in the demand for transport has traditionally been seen within the context of the problems of congestion, air quality, climate change, safety, and affordability. However, there are increasing threats including those related to crime such as cyber-attacks that threaten the security of the transport of people and goods. To the best of the authors’ knowledge, this paper presents for the first time, a comprehensive framework for the assessment of the current and future security issues of multi-modal transport systems. The approach or method proposed is based on a structured framework starting with a detailed specification of the transport asset map (transport system architecture), followed by the identification of vulnerabilities. The asset map and vulnerabilities are used to identify the various approaches for exploitation of the vulnerabilities, leading to the creation of a set of threat scenarios. The threat scenarios are then transformed into risks and their categories, and include insights for their mitigation. The consideration of the mitigation space is holistic and includes the formulation of appropriate policies and tactics and/or technical interventions. The quality of the framework is ensured through a structured and logical process that identifies the stakeholders, reviews the relevant documents including policies and identifies gaps, incorporates targeted surveys to augment the reviews, and uses subject matter experts for validation. The approach to categorising security risks is an extension of the current methods that are typically employed. Specifically, the partitioning of risks into either physical or cyber categories is too limited for developing mitigation policies and tactics/interventions for transport systems where an interplay between physical and cyber processes is very often the norm. This interplay is rapidly taking on increasing significance for security as the emergence of cyber-physical technologies, are shaping the future of all transport modes. Examples include: Connected Autonomous Vehicles (CAVs) in road transport; the European Rail Traffic Management System (ERTMS) in rail transport; Automatic Identification System (AIS) in maritime transport; advanced Communications, Navigation and Surveillance (CNS) technologies in air transport; and the Internet of Things (IoT). The framework adopts a risk categorisation scheme that considers risks as falling within the following threat→impact relationships: Physical→Physical, Cyber→Cyber, Cyber→Physical, and Physical→Cyber). Thus the framework enables a more complete risk picture to be developed for today’s transport systems and, more importantly, is readily extendable to account for emerging trends in the sector that will define future transport systems. The framework facilitates the audit and retro-fitting of mitigations in current transport operations and the analysis of security management options for the next generation of Transport enabling strategic aspirations such as systems with security-by-design and co-design of safety and security to be achieved. An initial application of the framework to transport systems has shown that intra-modal consideration of security measures is sub-optimal and that a holistic and multi-modal approach that also addresses the intersections/transition points of such networks is required as their vulnerability is high. This is in-line with traveler-centric transport service provision, widely accepted as the future of mobility services. In summary, a risk-based framework is proposed for use by the stakeholders to comprehensively and holistically assess the security of transport systems. It requires a detailed understanding of the transport architecture to enable a detailed vulnerabilities analysis to be undertaken, creates threat scenarios and transforms them into risks which form the basis for the formulation of interventions.

Keywords: mitigations, risk, transport, security, vulnerabilities

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Authors: Thaveesha Dheerasekera, Dileeka Sandamali Alwis

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The escalating prevalence of mental health issues, such as depression and suicidal ideation, is a matter of significant global concern. It is plausible that a variety of factors, such as life events, social isolation, and preexisting physiological or psychological health conditions, could instigate or exacerbate these conditions. Traditional approaches to diagnosing depression entail a considerable amount of time and necessitate the involvement of adept practitioners. This underscores the necessity for automated systems capable of promptly detecting and diagnosing symptoms of depression. The PsyVBot system employs sophisticated natural language processing and machine learning methodologies, including the use of the NLTK toolkit for dataset preprocessing and the utilization of a Long Short-Term Memory (LSTM) model. The PsyVBot exhibits a remarkable ability to diagnose depression with a 94% accuracy rate through the analysis of user input. Consequently, this resource proves to be efficacious for individuals, particularly those enrolled in academic institutions, who may encounter challenges pertaining to their psychological well-being. The PsyVBot employs a Long Short-Term Memory (LSTM) model that comprises a total of three layers, namely an embedding layer, an LSTM layer, and a dense layer. The stratification of these layers facilitates a precise examination of linguistic patterns that are associated with the condition of depression. The PsyVBot has the capability to accurately assess an individual's level of depression through the identification of linguistic and contextual cues. The task is achieved via a rigorous training regimen, which is executed by utilizing a dataset comprising information sourced from the subreddit r/SuicideWatch. The diverse data present in the dataset ensures precise and delicate identification of symptoms linked with depression, thereby guaranteeing accuracy. PsyVBot not only possesses diagnostic capabilities but also enhances the user experience through the utilization of audio outputs. This feature enables users to engage in more captivating and interactive interactions. The PsyVBot platform offers individuals the opportunity to conveniently diagnose mental health challenges through a confidential and user-friendly interface. Regarding the advancement of PsyVBot, maintaining user confidentiality and upholding ethical principles are of paramount significance. It is imperative to note that diligent efforts are undertaken to adhere to ethical standards, thereby safeguarding the confidentiality of user information and ensuring its security. Moreover, the chatbot fosters a conducive atmosphere that is supportive and compassionate, thereby promoting psychological welfare. In brief, PsyVBot is an automated conversational agent that utilizes an LSTM model to assess the level of depression in accordance with the input provided by the user. The demonstrated accuracy rate of 94% serves as a promising indication of the potential efficacy of employing natural language processing and machine learning techniques in tackling challenges associated with mental health. The reliability of PsyVBot is further improved by the fact that it makes use of the Reddit dataset and incorporates Natural Language Toolkit (NLTK) for preprocessing. PsyVBot represents a pioneering and user-centric solution that furnishes an easily accessible and confidential medium for seeking assistance. The present platform is offered as a modality to tackle the pervasive issue of depression and the contemplation of suicide.

Keywords: chatbot, depression diagnosis, LSTM model, natural language process

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Authors: Medha Iyer, Anshul Paul, Aunnesha Bhowmick, Anahita Banerjee, Sana Prasad, Anoushka Singal, Lauren Sinopoli, Pooja Bapat, Shivi Jain

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In Himachal Pradesh, India, a majority of the population lives in rural villages spread throughout its hilly regions; many of these households rely on subsistence farming as their main source of livelihood. The student-run non-profit organization affiliated with this study, Project RISHI (Rural India Social and Health Improvement), works to promote sustainable development practices in Bharog Baneri, a gram panchayat, or union, of villages in Himachal Pradesh. In 2017, an established rainwater harvesting (RWH) project group within Project RISHI had surveyed many families, finding that the most common issue regarding food and water access was a lack of accessible water sources for agricultural use in the dry season. After a prototype build in 2018, the group built 6 systems for eligible residents that demonstrated need in 2019. Subsequently, the project went through an evaluation period, including self-evaluation of project goals and post-impact surveying of system recipients. The group used the social impact assessment model to optimize the implementation of domestic RWH systems in Bharog Baneri. Assessing implementation after in-person builds produced three pillars of focus — system design, equitable recipient selection, and community involvement. After two years of remote involvement during COVID-19, the group prepared to visit Bharog Baneri to build 10 new systems in the Summer 2022. First, the group created a more durable and cost-effective design that could withstand debris and heavy rains to prevent gutter failure. The domestic system design is a rooftop RWH catchment system with two tanks attached, an overflow pipe, debris filtration, and a spigot for accessibility. The group also developed a needs-based eligibility methodology with assistance from village leaders and surveying in Bharog Baneri and set up the groundwork for a future community board. COVID-19 has strengthened remote work, telecommunications, and other organizational support systems. As sustainable development evolves to encompass these practices in a post-pandemic world, the potential for new RWH system design and implementation processes has emerged as well. This raises the question: how can a social impact assessment of rural RWH projects inform an integrated approach to post-pandemic RWH system practices? The objective of this exploratory study is to investigate and evaluate a novel remote build infrastructure that brings access to reliable and sustainable sources of water for agricultural use. To construct the remote build approach, the group identified and assigned a point of contact who was experienced with previous RWH system builds. The recipients were selected based on demonstrated need and ease of building. The contact visited each of the houses and coordinated supplier relations and transportation of the materials in accordance with the participatory approach to sustainable development. Over the course of two months, the group completed four system builds with the resulting infrastructure. The infrastructure adhered to the social impact assessment model by centering supplier relations, material transportation, and construction logistics within the community. The conclusion of this exploration is that post-pandemic rural RWH practices should be rooted in strengthening villager communication and utilizing local assets. Through this, non-profit organizations can incorporate remote build strategies into their long-term goals.

Keywords: capturing run-off from rooftops, domestic rainwater harvesting, Implementation approaches and strategies, rainwater harvesting and management in rural sectors

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Authors: Stephan Treuke

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The paper analyses the neighbourhood effects on the economic mobility of the inhabitants of three segregated communities of Salvador (Brazil), in other words, the socio-economic advantages and disadvantages affecting the lives of poor people due to their embeddedness in specific socio-residential contexts. Recent studies performed in Brazilian metropolis have concentrated on the structural dimensions of negative externalities in order to explain neighbourhood-level variations in a field of different phenomena (delinquency, violence, access to the labour market and education) in spatial isolated and socially homogeneous slum areas (favelas). However, major disagreement remains whether the contiguity between residents of poor neighbourhoods and higher-class condominio-dwellers provides structures of opportunities or whether it fosters socio-spatial stigmatization. Based on a set of interviews, investigating the variability of interpersonal networks and their activation in the struggle for economic inclusion, the study confirms that the proximity of Nordeste de Amaralina to middle-/upper-class communities affects positively the access to labour opportunities. Nevertheless, residential stigmatization, as well as structures of social segmentation, annihilate these potentials. The lack of exposition to individuals and groups extrapolating from the favela’s social, educational and cultural context restricts the structures of opportunities to local level. Therefore, residents´ interpersonal networks reveal a high degree of redundancy and localism, based on bonding ties connecting family and neighbourhood members. The resilience of segregational structures in Plataforma contributes to the naturalization of social distance patters. It’s embeddedness in a socially homogeneous residential area (Subúrbio Ferroviário), growing informally and beyond official urban politics, encourages the construction of isotopic patterns of sociability, sharing the same values, social preferences, perspectives and behaviour models. Whereas it’s spatial isolation correlates with the scarcity of economic opportunities, the social heterogeneity of Fazenda Grande II interviewees and the socialising effects of public institutions mitigate the negative repercussions of segregation. The networks’ composition admits a higher degree of heterophilia and a greater proportion of bridging ties accounting for the access to broader information actives and facilitating economic mobility. The variability observed within the three different scenarios urges to reflect about the responsability of urban politics when it comes to the prevention or consolidation of the social segregation process in Salvador. Instead of promoting the local development of the favela Plataforma, public housing programs priorize technocratic habitational solutions without providing the residents’ socio-economic integration. The impact of negative externalities related to the homogeneously poor neighbourhood is potencialized in peripheral areas, turning its’ inhabitants socially invisible, thus being isolated from other social groups. The example of Nordeste de Amaralina portrays the failing interest of urban politics to bridge the social distances structuring the brazilian society’s rigid stratification model, founded on mecanisms of segmentation (unequal access to labour market and education system, public transport, social security and law protection) and generating permanent conflicts between the two socioeconomically distant groups living in geographic contiguity. Finally, in the case of Fazenda Grande II, the public investments in both housing projects and complementary infrastructure (e.g. schools, hospitals, community center, police stations, recreation areas) contributes to the residents’ socio-economic inclusion.

Keywords: economic mobility, neighborhood effects, Salvador, segregation

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Authors: Doriane Delafosse, Dominique Fontvieille

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Background: Wastewater treatment plants (WWTPs) generally display significant efficacy in virus retention yet, are sometimes highly variable, partly in relation to large fluctuating loads at the head of the plant and partly because of episodic dysfunctions in some treatment processes. The problem is especially sensitive when human enteric viruses, such as human Noroviruses Genogroup I or Adenoviruses, are in concern: their release downstream WWTP, in environments often interconnected to recreational areas, may be very harmful to human communities even at low concentrations. It points out the importance of WWTP permanent monitoring from which their internal treatment processes could be adjusted. One way to adjust primary treatments is to add coagulants and flocculants to sewage ahead settling tanks to improve decantation. In this work, sludge produced by three coagulants (two organics, one mineral), four flocculants (three cationic, one anionic), and their combinations were studied for their efficacy in human enteric virus retention. Sewage samples were coming from a WWTP in the vicinity of the laboratory. All experiments were performed three times and in triplicates in laboratory pilots, using Murine Norovirus (MNV-1), a surrogate of human Norovirus, as an internal control (spiking). Viruses were quantified by (RT-)qPCR after nucleic acid extraction from both treated water and sediment. Results: Low values of sludge virus retention (from 4 to 8% of the initial sewage concentration) were observed with each cationic organic flocculant added to wastewater and no coagulant. The largest part of the virus load was detected in the treated water (48 to 90%). However, it was not counterbalancing the amount of the introduced virus (MNV-1). The results pertained to two types of cationic flocculants, branched and linear, and in the last case, to two percentages of cations. Results were quite similar to the association of a linear cationic organic coagulant and an anionic flocculant, though suggesting that differences between water and sludges would sometimes be related to virus size or virus origins (autochthonous/allochthonous). FeCl₃, as a mineral coagulant associated with an anionic flocculant, significantly increased both auto- and allochthonous virus retention in the sediments (15 to 34%). Accordingly, virus load in treated water was lower (14 to 48%) but with a total that still does not reach the amount of the introduced virus (MNV-1). It also appeared that the virus retrieval in a bare 0.1M NaCl suspension varied rather strongly according to the FeCl₃ concentration, suggesting an inhibiting effect on the molecular analysis used to detect the virus. Finally, no viruses were detected in both phases (sediment and water) with the combination branched cationic coagulant-linear anionic flocculant, which was later demonstrated as an effect, here also, of polymers on the virus detection-molecular analysis. Conclusions: The combination of FeCl₃-anionic flocculant gave its highest performance to the decantation-based virus removal process. However, large unbalanced values in spiking experiments were observed, suggesting that polymers cast additional obstacles to both elution buffer and lysis buffer on their way to reach the virus. The situation was probably even worse with autochthonous viruses already embedded into sewage's particulate matter. Polymers and FeCl₃ also appeared to interfere in some steps of molecular analyses. More attention should be paid to such impediments wherever chemical additives are considered to be used to enhance WWTP processes. Acknowledgments: This research was supported by the ABIOLAB laboratory (Montbonnot Saint-Martin, France) and by the ASPOSAN association. Field experiments were possible thanks to the Grand Chambéry WWTP authorities (Chambéry, France).

Keywords: flocculants-coagulants, polymers, enteric viruses, wastewater sedimentation treatment plant

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Authors: S. Fadda, M. Fiori, C. Matzuzzi

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Mineralized formations in the bottom sediments of a Miocene transgression have been discovered in Sardinia. The mineral assemblage consists of copper sulphides and oxidates suggesting fluctuations of redox conditions in neutral to high-pH restricted shallow-water coastal basins. Azurite/malachite has been observed as authigenic and occurs as loose spheroidal crystalline particles associated with the transitional-littoral horizon forming the bottom of the marine transgression. Many field observations are consistent with a supergenic circulation of metals involving terrestrial groundwater-seawater mixing. Both clastic materials and metals come from Tertiary volcanic edifices while the main precipitating anions, carbonates, and sulphides species are of both continental and marine origin. Formation of Cu carbonates as a supergene secondary 'oxide' assemblage, does not agree with field evidences, petrographic observations along with textural evidences in the host-rock types. Samples were collected along the sedimentary sequence for different analyses: the majority of elements were determined by X-ray fluorescence and plasma-atomic emission spectroscopy. Mineral identification was obtained by X-ray diffractometry and scanning electron microprobe. Thin sections of the samples were examined in microscopy while porosity measurements were made using a mercury intrusion porosimeter. Cu-carbonates deposited at a temperature below 100 C° which is consistent with the clay minerals in the matrix of the host rock dominated by illite and montmorillonite. Azurite nodules grew during the early diagenetic stage through reaction of cupriferous solutions with CO₂ imported from the overlying groundwater and circulating through the sandstones during shallow burial. Decomposition of organic matter in the bottom anoxic waters released additional carbon dioxide to pore fluids for azurite stability. In this manner localized reducing environments were also generated in which Cu was fixed as Cu-sulphide and sulphosalts. Microscopic examinations of textural features of azurite nodules give evidence of primary malachite/azurite deposition rather than supergene oxidation in place of primary sulfides. Photomicrographs show nuclei of azurite and malachite surrounded by newly formed microcrystalline carbonates which constitute the matrix. The typical pleochroism of crystals can be observed also when this mineral fills microscopic fissures or cracks. Sedimentological evidence of transgression and regression indicates that the pore water would have been a variable mixture of marine water and groundwaters with a possible meteoric component in an alternatively exposed and subaqueous environment owing to water-level fluctuation. Salinity data of the pore fluids, assessed at random intervals along the mineralised strata confirmed the values between about 7000 and 30,000 ppm measured in coeval sediments at the base of Miocene falling in the range of a more or less diluted sea water. This suggests a variation in mean pore-fluids pH between 5.5 and 8.5, compatible with the oxidized and reduced mineral paragenesis described in this work. The results of stable isotopes studies reflect the marine transgressive-regressive cyclicity of events and are compatibile with carbon derivation from sea water. During the last oxidative stage of diagenesis, under surface conditions of higher activity of H₂O and O₂, CO₂ partial pressure decreased, and malachite becomes the stable Cu mineral. The potential for these small but high grade deposits does exist.

Keywords: sedimentary, Cu-carbonates, authigenic, tertiary, Sardinia

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Authors: Christian J. Kennett, Mark A. Baldwin

Abstract:

As several companies are working towards returning American astronauts back to space on US-made spacecraft, NASA developed a human flight certification-by-test and analysis approach due to the cost-prohibitive nature of extensive testing. This process relies heavily on the quality of analytical models to accurately predict crew injury potential specific to each spacecraft and under dynamic environments not tested. As the prime contractor on the Orion spacecraft, Lockheed Martin was tasked with quantifying the correlation of analytical anthropometric test devices (ATDs), also known as crash test dummies, against test measurements under representative impact conditions. Multiple dynamic impact sled tests were conducted to characterize Hybrid III 5th ATD lumbar, head, and neck responses with and without a modified shuttle-era advanced crew escape suit (ACES) under simulated Orion landing and abort conditions. Each ATD was restrained via a 5-point harness in a mockup Orion seat fixed to a dynamic impact sled at the Wright Patterson Air Force Base (WPAFB) Biodynamics Laboratory in the horizontal impact accelerator (HIA). ATDs were subject to multiple impact magnitudes, half-sine pulse rise times, and XZ - ‘eyeballs out/down’ or Z-axis ‘eyeballs down’ orientations for landing or an X-axis ‘eyeballs in’ orientation for abort. Several helmet constraint devices were evaluated during suited testing. Unique finite element models (FEMs) were developed of the unsuited and suited sled test configurations using an analytical 5th ATD model developed by LSTC (Livermore, CA) and deformable representations of the seat, suit, helmet constraint countermeasures, and body restraints. Explicit FE analyses were conducted using the non-linear solver LS-DYNA. Head linear and rotational acceleration, head rotational velocity, upper neck force and moment, and lumbar force time histories were compared between test and analysis using the enhanced error assessment of response time histories (EEARTH) composite score index. The EEARTH rating paired with the correlation and analysis (CORA) corridor rating provided a composite ISO score that was used to asses model correlation accuracy. NASA occupant protection subject matter experts established an ISO score of 0.5 or greater as the minimum expectation for correlating analytical and experimental ATD responses. Unsuited 5th ATD head X, Z, and resultant linear accelerations, head Y rotational accelerations and velocities, neck X and Z forces, and lumbar Z forces all showed consistent ISO scores above 0.5 in the XZ impact orientation, regardless of peak g-level or rise time. Upper neck Y moments were near or above the 0.5 score for most of the XZ cases. Similar trends were found in the XZ and Z-axis suited tests despite the addition of several different countermeasures for restraining the helmet. For the X-axis ‘eyeballs in’ loading direction, only resultant head linear acceleration and lumbar Z-axis force produced ISO scores above 0.5 whether unsuited or suited. The analytical LSTC 5th ATD model showed good correlation across multiple head, neck, and lumbar responses in both the unsuited and suited configurations when loaded in the XZ ‘eyeballs out/down’ direction. Upper neck moments were consistently the most difficult to predict, regardless of impact direction or test configuration.

Keywords: impact biomechanics, manned spaceflight, model correlation, multi-axial loading

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Authors: Chiu-Yin Leung

Abstract:

This research investigates a complex assemblage among indigenous identities, socio-political organization and national apparatus in the border landscape of post-colonial Hong Kong. This former British colony had designated a transient mode of governance in its New Territories and particularly the northernmost borderland in 1951-2012. With a discriminated system of land provisions for the indigenous villagers, the place has been inherited with distinctive village-based culture, historic monuments and agrarian practices until its sovereignty return into the People’s Republic of China. In its latest development imperatives by the national strategic planning, the frontier area of Hong Kong has been identified as a strategy site for regional economic integration in South China, with cross-border projects of innovation and technology zones, mega-transport infrastructure and inter-jurisdictional arrangement. Contemporary literature theorizes borders as the material and discursive production of territoriality, which manifest in state apparatus and the daily lives of its citizens and condense in the contested articulations of power, security and citizenship. Drawing on the concept of assemblage, this paper attempts to tract how the border regime and infrastructure in Hong Kong as a city are deeply ingrained in the everyday lived spaces of the local communities but also the changing urban and regional strategies across different longitudinal moments. Through an intensive ethnographic fieldwork among the borderland villages since 2008 and the extensive analysis of colonial archives, new development plans and spatial planning frameworks, the author navigates the genealogy of the border landscape in Ta Kwu Ling frontier area and its implications as the milieu for new state space, covering heterogeneous fields particularly in indigenous rights, heritage preservation, rural sustainability and regional economy. Empirical evidence suggests an apparent bias towards indigenous power and colonial representation in classifying landscape values and conserving historical monuments. Squatter and farm tenants are often deprived of property rights, statutory participation and livelihood option in the planning process. The postcolonial bureaucracies have great difficulties in mobilizing resources to catch up with the swift, political-first approach of the mainland counterparts. Meanwhile, the cultural heritage, lineage network and memory landscape are not protected altogether with any holistic view or collaborative effort across the border. The enactment of land resumption and compensation scheme is furthermore disturbed by lineage-based customary law, technocratic bureaucracy, intra-community conflicts and multi-scalar political mobilization. As many traces of colonial misfortune and tyranny have been whitewashed without proper management, the author argues that postcolonial justice is yet reconciled in this fragmented border landscape. The assemblage of border in mainstream representation has tended to oversimplify local struggles as a collective mist and setup a wider production of schizophrenia experiences in the discussion of further economic integration among Hong Kong and other mainland cities in the Pearl River Delta Region. The research is expected to shed new light on the theorizing of border regions and postcolonialism beyond Eurocentric perspectives. In reassembling the borderland experiences with other arrays in state governance, village organization and indigenous identities, the author also suggests an alternative epistemology in reconciling socio-spatial differences and opening up imaginaries for positive interventions.

Keywords: heritage conservation, indigenous communities, post-colonial borderland, regional development, rural sustainability

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Authors: Priyanka Botny Srinath, Alessandro Suglia, Mel McKendrick

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Background: Organizational cultural studies integrate sociology and anthropology, portraying man as a creator of symbols, languages, beliefs, and ideologies -essentially, a creator and manager of meaning. In our research, we leverage analytical measures to discern whether an organization embodies a singular culture or a myriad of subcultures. Fast-forward to 2023, our research thesis focuses on digitally measuring culture, coining it as the "Work Culture Quotient." This entails conceptually mapping common experiential patterns to provide executives insights into the digital organization journey, aiding in understanding their current position and identifying future steps. Objectives: Finding the new age skills that help in defining the culture; understand the implications of post-COVID effects; derive a digital framework for measuring skillsets. Method: We conducted two comprehensive Delphi studies to distill essential insights. Delphi 1: Through a thematic analysis of interviews with 20 high-level leaders representing companies across diverse regions -India, Japan, the US, Canada, Morocco, and Uganda- we identified 20 key skills critical for cultivating a robust organizational culture. The skills are -influence, self-confidence, optimism, empathy, leadership, collaboration and cooperation, developing others, commitment, innovativeness, leveraging diversity, change management, team capabilities, self-control, digital communication, emotional awareness, team bonding, communication, problem solving, adaptability, and trustworthiness. Delphi 2: Subject matter experts were asked to complete a questionnaire derived from the thematic analysis in stage 1 to formalise themes and draw consensus amongst experts on the most important workplace skills. Results: The thematic analysis resulted in 20 workplace employee skills being identified. These skills were all included in the Delphi round 2 questionnaire. From the outputs, we analysed the data using R Studio for arriving at agreement and consensus, we also used sum of squares method to compare various agreements to extract various themes with a threshold of 80% agreements. This yielded three themes at over 80% agreement (leadership, collaboration and cooperation, communication) and three further themes at over 60% agreement (commitment, empathy, trustworthiness). From this, we selected five questionnaires to be included in the primary data collection phase, and these will be paired with the digital footprints to provide a workplace culture quotient. Implications: The findings from these studies bear profound implications for decision-makers, revolutionizing their comprehension of organizational culture. Tackling the challenge of mapping the digital organization journey involves innovative methodologies that probe not only external landscapes but also internal cultural dynamics. This holistic approach furnishes decision-makers with a nuanced understanding of their organizational culture and visualizes pivotal skills for employee growth. This clarity enables informed choices resonating with the organization's unique cultural fabric. Anticipated outcomes transcend mere individual cultural measurements, aligning with organizational goals to unveil a comprehensive view of culture, exposing artifacts and depth. Armed with this profound understanding, decision-makers gain tangible evidence for informed decision-making, strategically leveraging cultural strengths to cultivate an environment conducive to growth, innovation, and enduring success, ultimately leading to measurable outcomes.

Keywords: leadership, cooperation, collaboration, teamwork, work culture

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Authors: Marcela Davalos Lopez

Abstract:

The history of the circulation of hygienic knowledge and the consolidation of public health in Latin American cities towards the end of the 19th century is well known. Among them, Mexico City was inserted in international politics, strengthened institutions, medical knowledge, applied parameters of modernity and built sanitary engineering works. Despite the power that this hygienist system achieved, its scope was relative: it cannot be generalized to all cities. From a comparative and contextual analysis, it will be shown that conclusions derived from modern urban historiography present, from our contemporary observations, fractures. Between 1890 and 1930, the small cities and areas surrounding the Mexican capital adapted in their own way the international and federal public health regulations. This will be shown for neighborhoods located around Mexico City and in a medium city, close to the Mexican capital (about 80 km), called Cuernavaca. While the inhabitants of the neighborhoods kept awaiting the evolutionary process and the forms that public hygiene policies were taking (because they were witnesses and affected in their territories), in Cuernavaca, the dictates came as an echo. While the capital was drained, large roads were opened, roundabouts were erected, residents were expelled, and drains, sewers, drinking water pipes, etc., were built; Cuernavaca was sheltered in other times and practices. What was this due to? Undoubtedly, the time and energy that it took politicians and the group of "scientists" to carry out these enormous works in the Mexican capital took them away from addressing the issue in remote villages. It was not until the 20th century that the federal hygiene policy began to be strengthened. Despite this, there are other factors that emphasize the particularities of each site. I would like to draw attention here to the different receptions that each town prepared on public hygiene. We will see that Cuernavaca responded to its own semi-rural culture, history, orography and functions, prolonging for much longer, for example, the use of its deep ravines as sewers. For their part, the neighborhoods surrounding the capital, although affected and excluded from hygienist policies, chose to move away from them and solve the deficiencies with their own resources (they resorted to the waste that was left from the dried lake of Mexico to continue their lake practices). All of this points to a paradox that shapes our contemporary concerns: on the one hand, the benefits derived from medical knowledge and its technological applications (in this work referring particularly to the urban health system) and, on the other, the alteration it caused in environmental settings. Places like Cuernavaca (classified by the nineteenth-century and hygienists of the first decades of the twentieth century as backward), as well as landscapes such as neighborhoods, affected by advances in sanitary engineering, keep in their memory buried practices that we observe today as possible ways to reestablish environmental balances: alternative uses of water; recycling of organic materials; local uses of fauna; various systems for breaking down excreta, and so on. In sum, what the nineteenth and first half of the twentieth centuries graduated as levels of backwardness or progress, turn out to be key information to rethink the routes of environmental conservation. When we return to the observations of the scientists, politicians and lawyers of that period, we find historically rejected cultural alterity. Populations such as Cuernavaca that, due to their history, orography and/or insufficiency of federal policies, kept different relationships with the environment, today give us clues to reorient basic elements of cities: alternative uses of water, waste of raw materials, organic or consumption of local products, among others. It is, therefore, a matter of unearthing the rejected that cries out to emerge to the surface.

Keywords: sanitary hygiene, Mexico city, cultural alterity, environmental conservation, environmental history

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Authors: Richard Ren

Abstract:

Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 97