Search results for: affective mechanisms index

Authors: Bianca Peterson, Tomasz J. Sańko, Carlos C. Bezuidenhout, Johnnie Van Den Berg

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Busseola fusca (Fuller) (Lepidoptera: Noctuidae), the maize stem borer, is a major pest in sub-Saharan Africa. It causes economic damage to maize and sorghum crops and has evolved non-recessive resistance to genetically modified (GM) maize expressing the Cry1Ab insecticidal toxin. Since B. fusca is a non-model organism, very little genomic information is publicly available, and is limited to some cytochrome c oxidase I, cytochrome b, and microsatellite data. The biology of B. fusca is well-described, but still poorly understood. This, in combination with its larval-specific behavior, may pose problems for limiting the spread of current resistant B. fusca populations or preventing resistance evolution in other susceptible populations. As part of on-going research into resistance evolution, B. fusca larvae were collected from Bt and non-Bt maize in South Africa, followed by RNA isolation (15 specimens) and sequencing on the Illumina HiSeq 2500 platform. Quality of reads was assessed with FastQC, after which Trimmomatic was used to trim adapters and remove low quality, short reads. Trinity was used for the de novo assembly, whereas TransRate was used for assembly quality assessment. Transcript identification employed BLAST (BLASTn, BLASTp, and tBLASTx comparisons), for which two libraries (nucleotide and protein) were created from 3.27 million lepidopteran sequences. Several transcripts that have previously been implicated in Cry toxin resistance was identified for B. fusca. These included aminopeptidase N, cadherin, alkaline phosphatase, ATP-binding cassette transporter proteins, and mitogen-activated protein kinase. MEGA7 was used to align these transcripts to reference sequences from Lepidoptera to detect mutations that might potentially be contributing to Cry toxin resistance in this pest. RSEM and Bioconductor were used to perform differential gene expression analysis on groups of B. fusca larvae challenged and unchallenged with the Cry1Ab toxin. Pairwise expression comparisons of transcripts that were at least 16-fold expressed at a false-discovery corrected statistical significance (p) ≤ 0.001 were extracted and visualized in a hierarchically clustered heatmap using R. A total of 329,194 transcripts with an N50 of 1,019 bp were generated from the over 167.5 million high-quality paired-end reads. Furthermore, 110 transcripts were over 10 kbp long, of which the largest one was 29,395 bp. BLAST comparisons resulted in identification of 157,099 (47.72%) transcripts, among which only 3,718 (2.37%) were identified as Cry toxin receptors from lepidopteran insects. According to transcript expression profiles, transcripts were grouped into three subclusters according to the similarity of their expression patterns. Several immune-related transcripts (pathogen recognition receptors, antimicrobial peptides, and inhibitors) were up-regulated in the larvae feeding on Bt maize, indicating an enhanced immune status in response to toxin exposure. Above all, extremely up-regulated arylphorin genes suggest that enhanced epithelial healing is one of the resistance mechanisms employed by B. fusca larvae against the Cry1Ab toxin. This study is the first to provide a resource base and some insights into a potential mechanism of Cry1Ab toxin resistance in B. fusca. Transcriptomic data generated in this study allows identification of genes that can be targeted by biotechnological improvements of GM crops.

Keywords: epithelial healing, Lepidoptera, resistance, transcriptome

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Authors: Kumalbeo Paul Kamani

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Marketing plays a very important role in the success of any firm since it represents the means through which a firm can reach its customers and also promotes its products and services. In fact, marketing aids the firm in identifying customers who the business can competitively serve, and tailoring product offerings, prices, distribution, promotional efforts, and services towards those customers. Unfortunately, in many firms, marketing has been reduced to merely advertisement. For effective marketing, firms must go beyond this often-limited function of advertisement. In the fashion industry in particular, marketing faces challenges due to its peculiar characteristics. Previous research for instance affirms the idiosyncrasy and peculiarities that differentiate the fashion industry from other industrial areas. It has been documented that the fashion industry is characterized seasonal intensity, short product life cycles, the difficulty of competitive differentiation, and long time for companies to reach financial stability. These factors are noted to pose obstacles to the fashion entrepreneur’s endeavours and can be the reasons that explain their low survival rates. In recent times, the fashion industry has been described as a market that is accessible market, has low entry barriers, both in terms of needed capital and skills which have all accounted for the burgeoning nature of startups. Yet as already stated, marketing is particularly challenging in the industry. In particular, areas such as marketing, branding, growth, project planning, financial and relationship management might represent challenges for the fashion entrepreneur but that have not been properly addressed by previous research. It is therefore important to assess marketing strategies of fashion firms and the factors influencing their success. This study generally sought to examine marketing strategies of fashion dealers in Ghana and their critical success factors. The study employed the quantitative survey research approach. A total of 120 fashion dealers were sampled. Questionnaires were used as instrument of data collection. Data collected was analysed using quantitative techniques including descriptive statistics and Relative Importance Index. The study revealed that the marketing strategies used by fashion apparels are text messages using mobile phones, referrals, social media marketing, and direct marketing. Results again show that the factors influencing fashion marketing effectiveness are strategic management, marketing mix (product, price, promotion etc), branding and business development. Policy implications are finally outlined. The study recommends among others that there is a need for the top management executive to craft and adopt marketing strategies that enable that are compatible with the fashion trends and the needs of the customers. This will improve customer satisfaction and hence boost market penetration. The study further recommends that the fashion industry in Ghana should seek to ensure that fashion apparels accommodate the diversity and the cultural setting of different customers to meet their unique needs.

Keywords: marketing, fashion, industry, success factors

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Authors: Ming Zhou, Taeho Park

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Early stage technologies have been particularly challenging to manage due to high degrees of their numerous uncertainties. Most research results directly out of a research lab tend to be at their early, if not the infant stage. A long while uncertain commercialization process awaits these lab results. The majority of such lab technologies go nowhere and never get commercialized due to various reasons. Any efforts or financial resources put into managing these technologies turn fruitless. High stake naturally calls for better results, which make a patenting decision harder to make. A good and well protected patent goes a long way for commercialization of the technology. Our preliminary research showed that there was not a simple yet productive procedure for such valuation. Most of the studies now have been theoretical and overly comprehensive where practical suggestions were non-existent. Hence, we attempted to develop a simple and highly implementable procedure for efficient and scalable valuation. We thoroughly reviewed existing research, interviewed practitioners in the Silicon Valley area, and surveyed university technology offices. Instead of presenting another theoretical and exhaustive research, we aimed at developing a practical guidance that a government agency and/or university office could easily deploy and get things moving to later steps of managing early stage technologies. We provided a procedure to thriftily value and make the patenting decision. A patenting index was developed using survey data and expert opinions. We identified the most important factors to be used in the patenting decision using survey ratings. The rating then assisted us in generating good relative weights for the later scoring and weighted averaging step. More importantly, we validated our procedure by testing it with our practitioner contacts. Their inputs produced a general yet highly practical cut schedule. Such schedule of realistic practices has yet to be witnessed our current research. Although a technology office may choose to deviate from our cuts, what we offered here at least provided a simple and meaningful starting point. This procedure was welcomed by practitioners in our expert panel and university officers in our interview group. This research contributed to our current understanding and practices of managing early stage technologies by instating a heuristically simple yet theoretical solid method for the patenting decision. Our findings generated top decision factors, decision processes and decision thresholds of key parameters. This research offered a more practical perspective which further completed our extant knowledge. Our results could be impacted by our sample size and even biased a bit by our focus on the Silicon Valley area. Future research, blessed with bigger data size and more insights, may want to further train and validate our parameter values in order to obtain more consistent results and analyze our decision factors for different industries.

Keywords: technology management, early stage technology, patent, decision

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Authors: V. Moser-Siegmeth, M. C. Gambal, M. Jelovcak, B. Prytek, I. Swietalsky, D. Würzl, C. Fida, V. Mühlegger

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Adaptability is the capacity to adjust without great difficulty to changing circumstances. Within our project, we aimed to detect whether older people living within a long-term care hospital lose the ability to adapt. Theoretical concepts are contradictory in their statements. There is also lack of evidence in the literature how the adaptability of older people changes over the time. Following research questions were generated: Are older residents of a long-term care facility able to adapt to changes within their daily routine? How long does it take for older people to adapt? The study was designed as a convergent parallel mixed method intervention study, carried out within a four-month period and took place within seven wards of a long-term care hospital. As a planned intervention, a change of meal-times was established. The inhabitants were surveyed with qualitative interviews and quantitative questionnaires and diaries before, during and after the intervention. In addition, a survey of the nursing staff was carried out in order to detect changes of the people they care for and how long it took them to adapt. Quantitative data was analysed with SPSS, qualitative data with a summarizing content analysis. The average age of the involved residents was 82 years, the average length of stay 45 months. The adaptation to new situations does not cause problems for older residents. 47% of the residents state that their everyday life has not changed by changing the meal times. 24% indicate ‘neither nor’ and only 18% respond that their daily life has changed considerably due to the changeover. The diaries of the residents, which were conducted over the entire period of investigation showed no changes with regard to increased or reduced activity. With regard to sleep quality, assessed with the Pittsburgh sleep quality index, there is little change in sleep behaviour compared to the two survey periods (pre-phase to follow-up phase) in the cross-table. The subjective sleep quality of the residents is not affected. The nursing staff points out that, with good information in advance, changes are not a problem. The ability to adapt to changes does not deteriorate with age or by moving into a long-term care facility. It only takes a few days to get used to new situations. This can be confirmed by the nursing staff. Although there are different determinants like the health status that might make an adjustment to new situations more difficult. In connection with the limitations, the small sample size of the quantitative data collection must be emphasized. Furthermore, the extent to which the quantitative and qualitative sample represents the total population, since only residents without cognitive impairments of selected units participated. The majority of the residents has cognitive impairments. It is important to discuss whether and how well the diary method is suitable for older people to examine their daily structure.

Keywords: adaptability, intervention study, mixed methods, nursing home residents

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Authors: Shayan Mohajer Hamidi

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Federated Learning (FL) has emerged as a promising paradigm for training machine learning models on distributed data without the need for centralized data aggregation. In the realm of wireless communications, FL has the potential to leverage the vast amounts of data generated by wireless devices to improve model performance and enable intelligent applications. However, the fairness aspect of FL in wireless communications remains largely unexplored. This abstract presents an idea for fair federated learning in wireless communications, addressing the challenges of imbalanced data distribution, privacy preservation, and resource allocation. Firstly, the proposed approach aims to tackle the issue of imbalanced data distribution in wireless networks. In typical FL scenarios, the distribution of data across wireless devices can be highly skewed, resulting in unfair model updates. To address this, we propose a weighted aggregation strategy that assigns higher importance to devices with fewer samples during the aggregation process. By incorporating fairness-aware weighting mechanisms, the proposed approach ensures that each participating device's contribution is proportional to its data distribution, thereby mitigating the impact of data imbalance on model performance. Secondly, privacy preservation is a critical concern in federated learning, especially in wireless communications where sensitive user data is involved. The proposed approach incorporates privacy-enhancing techniques, such as differential privacy, to protect user privacy during the model training process. By adding carefully calibrated noise to the gradient updates, the proposed approach ensures that the privacy of individual devices is preserved without compromising the overall model accuracy. Moreover, the approach considers the heterogeneity of devices in terms of computational capabilities and energy constraints, allowing devices to adaptively adjust the level of privacy preservation to strike a balance between privacy and utility. Thirdly, efficient resource allocation is crucial for federated learning in wireless communications, as devices operate under limited bandwidth, energy, and computational resources. The proposed approach leverages optimization techniques to allocate resources effectively among the participating devices, considering factors such as data quality, network conditions, and device capabilities. By intelligently distributing the computational load, communication bandwidth, and energy consumption, the proposed approach minimizes resource wastage and ensures a fair and efficient FL process in wireless networks. To evaluate the performance of the proposed fair federated learning approach, extensive simulations and experiments will be conducted. The experiments will involve a diverse set of wireless devices, ranging from smartphones to Internet of Things (IoT) devices, operating in various scenarios with different data distributions and network conditions. The evaluation metrics will include model accuracy, fairness measures, privacy preservation, and resource utilization. The expected outcomes of this research include improved model performance, fair allocation of resources, enhanced privacy preservation, and a better understanding of the challenges and solutions for fair federated learning in wireless communications. The proposed approach has the potential to revolutionize wireless communication systems by enabling intelligent applications while addressing fairness concerns and preserving user privacy.

Keywords: federated learning, wireless communications, fairness, imbalanced data, privacy preservation, resource allocation, differential privacy, optimization

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Authors: Athina Thanou, Eirini Eleni Tsiropoulou, Symeon Papavassiliou

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The problem of museum visitor experience and congestion management – in various forms - has come increasingly under the spotlight over the last few years, since overcrowding can significantly decrease the quality of visitors’ experience. Evidence suggests that on busy days the amount of time a visitor spends inside a crowded house museum can fall by up to 60% compared to a quiet mid-week day. In this paper we consider the aforementioned problem, by treating museums as evolving social systems that induce constraints. However, in a cultural heritage space, as opposed to the majority of social environments, the momentum of the experience is primarily controlled by the visitor himself. Visitors typically behave selfishly regarding the maximization of their own Quality of Experience (QoE) - commonly expressed through a utility function that takes several parameters into consideration, with crowd density and waiting/visiting time being among the key ones. In such a setting, congestion occurs when either the utility of one visitor decreases due to the behavior of other persons, or when costs of undertaking an activity rise due to the presence of other persons. We initially investigate how visitors’ behavioral risk attitudes, as captured and represented by prospect theory, affect their decisions in resource sharing settings, where visitors’ decisions and experiences are strongly interdependent. Different from the majority of existing studies and literature, we highlight that visitors are not risk neutral utility maximizers, but they demonstrate risk-aware behavior according to their personal risk characteristics. In our work, exhibits are organized into two groups: a) “safe exhibits” that correspond to less congested ones, where the visitors receive guaranteed satisfaction in accordance with the visiting time invested, and b) common pool of resources (CPR) exhibits, which are the most popular exhibits with possibly increased congestion and uncertain outcome in terms of visitor satisfaction. A key difference is that the visitor satisfaction due to CPR strongly depends not only on the invested time decision of a specific visitor, but also on that of the rest of the visitors. In the latter case, the over-investment in time, or equivalently the increased congestion potentially leads to “exhibit failure”, interpreted as the visitors gain no satisfaction from their observation of this exhibit due to high congestion. We present a framework where each visitor in a distributed manner determines his time investment in safe or CPR exhibits to optimize his QoE. Based on this framework, we analyze and evaluate how visitors, acting as prospect-theoretic decision-makers, respond and react to the various pricing policies imposed by the museum curators. Based on detailed evaluation results and experiments, we present interesting observations, regarding the impact of several parameters and characteristics such as visitor heterogeneity and use of alternative pricing policies, on scalability, user satisfaction, museum capacity, resource fragility, and operation point stability. Furthermore, we study and present the effectiveness of alternative pricing mechanisms, when used as implicit tools, to deal with the congestion management problem in the museums, and potentially decrease the exhibit failure probability (fragility), while considering the visitor risk preferences.

Keywords: museum resource and visitor management, congestion management, propsect theory, cyber physical social systems

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Authors: Bengan Simbarashe Manwere

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The entire African continent, comprising 55 countries, holds a 2% share of the global carbon market. The World Bank attributes the continent’s insignificant share and participation in the carbon market to the limited access to electricity. Approximately 800 million people spread across 47 African countries generate as much power as Spain, with a population of 45million. Only South Africa and North Africa have carbon-reduction investment opportunities on the continent and dominate the 2% market share of the global carbon market. On the back of the 2015 Paris Agreement, South Africa signed into law the Carbon Tax Act 15 of 2019 and the Customs and Excise Amendment Act 13 of 2019 (Gazette No. 4280) on 1 June 2019. By these laws, South Africa was ushered into the league of active global carbon market players. By increasing the cost of production by the rate of R120/tCO2e, the tax intentionally compels the internalization of pollution as a cost of production and, relatedly, stimulate investment in clean technologies. The first phase covered the 1 June 2019 – 31 December 2022 period during which the tax was meant to escalate at CPI + 2% for Scope 1 emitters. However, in the second phase, which stretches from 2023 to 2030, the tax will escalate at the inflation rate only as measured by the consumer price index (CPI). The Carbon Tax Act provides for carbon allowances as mitigation strategies to limit agents’ carbon tax liability by up to 95% for fugitive and process emissions. Although the June 2019 Carbon Tax Act explicitly makes provision for a carbon trading scheme (CTS), the carbon trading regulations thereof were only finalised in December 2020. This points to a delay in the establishment of a carbon trading scheme (CTS). Relatedly, emitters in South Africa are not able to benefit from the 95% reduction in effective carbon tax rate from R120/tCO2e to R6/tCO2e as the Johannesburg Stock Exchange (JSE) has not yet finalized the establishment of the market for trading carbon credits. Whereas most carbon trading schemes have been designed and constructed from the beginning as new tailor-made systems in countries the likes of France, Australia, Romania which treat carbon as a financial product, South Africa intends, on the contrary, to leverage existing trading infrastructure of the Johannesburg Stock Exchange (JSE) and the Clearing and Settlement platforms of Strate, among others, in the interest of the Paris Agreement timelines. Therefore the carbon trading scheme will not be constructed from scratch. At the same time, carbon will be treated as a commodity in order to align with the existing institutional and infrastructural capacity. This explains why the Carbon Tax Act is silent about the involvement of the Financial Sector Conduct Authority (FSCA).For South Africa, there is need to establish they equilibrium stability of the CTS. This is important as South Africa is an innovator in carbon trading and the successful trading of carbon credits on the JSE will lead to imitation by early adopters first, followed by the middle majority thereafter.

Keywords: carbon trading scheme (CTS), Johannesburg stock exchange (JSE), carbon tax act 15 of 2019, South Africa

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Authors: A. Newman-Tancredi, R. Depoortère, P. Gruca, E. Litwa, M. Lason, M. Papp

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The N-methyl-D-aspartic acid (NMDA) receptor antagonist, ketamine, can elicit rapid-acting antidepressant (RAAD) effects in treatment-resistant patients, but it requires parenteral co-administration with a classical antidepressant under medical supervision. In addition, ketamine can also produce serious side effects that limit its long-term use, and there is much interest in identifying RAADs based on ketamine’s mechanism of action but with safer profiles. Ketamine elicits GABAergic interneuron inhibition, glutamatergic neuron stimulation, and, notably, activation of serotonin 5-HT1A receptors in the prefrontal cortex (PFC). Direct activation of the latter receptor subpopulation with selective ‘biased agonists’ may therefore be a promising strategy to identify novel RAADs and, consistent with this hypothesis, the prototypical cortical biased agonist, NLX-101, exhibited robust RAAD-like activity in the chronic mild stress model of depression (CMS). The present study compared the effects of a novel, selective 5-HT1A receptor-biased agonist, NLX-204, with those of ketamine and NLX-101. Materials and methods: CMS procedure was conducted on Wistar rats; drugs were administered either intraperitoneally (i.p.) or by bilateral intracortical microinjection. Ketamine: 10 mg/kg i.p. or 10 µg/side in PFC; NLX-204 and NLX-101: 0.08 and 0.16 mg/kg i.p. or 16 µg/side in PFC. In addition, interaction studies were carried out with systemic NLX-204 or NLX-101 (each at 0.16 mg/kg i.p.) in combination with intracortical WAY-100635 (selective 5-HT1A receptor antagonist; 2 µg/side) or muscimol (GABA-A receptor agonist, 12.5 ng/side). Anhedonia was assessed by CMS-induced decrease in sucrose solution consumption; anxiety-like behavior was assessed using the Elevated Plus Maze (EPM), and cognitive impairment was assessed by the Novel Object Recognition (NOR) test. Results: A single administration of NLX-204 was sufficient to reverse the CMS-induced deficit in sucrose consumption, similarly to ketamine and NLX-101. NLX-204 also reduced CMS-induced anxiety in the EPM and abolished CMS-induced NOR deficits. These effects were maintained (EPM and NOR) or enhanced (sucrose consumption) over a subsequent 2-week period of treatment. The anti-anhedonic response of the drugs was also maintained for several weeks Following treatment discontinuation, suggesting that they had sustained effects on neuronal networks. A single PFC administration of NLX-204 reversed deficient sucrose consumption, similarly to ketamine and NLX-101. Moreover, the anti-anhedonic activities of systemic NLX-204 and NLX 101 were abolished by coadministration with intracortical WAY-100635 or muscimol. Conclusions: (i) The antidepressant-like activity of NLX-204 in the rat CMS model was as rapid as that of ketamine or NLX-101, supporting targeting cortical 5-HT1A receptors with selective, biased agonists to achieve RAAD effects. (ii)The anti-anhedonic activity of systemic NLX-204 was mimicked by local administration of the compound in the PFC, confirming the involvement of cortical circuits in its RAAD-like effects. (iii) Notably, the effects of systemic NLX-204 and NLX-101 were abolished by PFC administration of muscimol, indicating that they act by (indirectly) eliciting a reduction in cortical GABAergic neurotransmission. This is consistent with ketamine’s mechanism of action and suggests that there are converging NMDA and 5-HT1A receptor signaling cascades in PFC underlying the RAAD-like activities of ketamine and NLX-204. Acknowledgements: The study was financially supported by NCN grant no. 2019/35/B/NZ7/00787.

Keywords: depression, ketamine, serotonin, 5-HT1A receptor, chronic mild stress

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Authors: Kseniya Gladun

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Tactile stimulation of a dorsal side of the wrist can have a strong impact on our attitude toward physical objects such as pleasant and unpleasant impact. This study explored different aspects of tactile perception to investigate atypical touch sensitivity in children with autism spectrum disorder (ASD). This study included 40 children with ASD and 40 healthy children aged 5 to 9 years. We recorded rsEEG (sampling rate of 250 Hz) during 20 min using EEG amplifier “Encephalan” (Medicom MTD, Taganrog, Russian Federation) with 19 AgCl electrodes placed according to the International 10–20 System. The electrodes placed on the left, and right mastoids served as joint references under unipolar montage. The registration of EEG v19 assignments was carried out: frontal (Fp1-Fp2; F3-F4), temporal anterior (T3-T4), temporal posterior (T5-T6), parietal (P3-P4), occipital (O1-O2). Subjects were passively touched by 4 types of tactile stimuli on the left wrist. Our stimuli were presented with a velocity of about 3–5 cm per sec. The stimuli materials and procedure were chosen for being the most "pleasant," "rough," "prickly" and "recognizable". Type of tactile stimulation: Soft cosmetic brush - "pleasant" , Rough shoe brush - "rough", Wartenberg pin wheel roller - "prickly", and the cognitive tactile stimulation included letters by finger (most of the patient’s name ) "recognizable". To designate the moments of the stimuli onset-offset, we marked the moment when the moment of the touch began and ended; the stimulation was manual, and synchronization was not precise enough for event-related measures. EEG epochs were cleaned from eye movements by ICA-based algorithm in EEGLAB plugin for MatLab 7.11.0 (Mathwork Inc.). Muscle artifacts were cut out by manual data inspection. The response to tactile stimuli was significantly different in the group of children with ASD and healthy children, which was also depended on type of tactile stimuli and the severity of ASD. Amplitude of Alpha rhythm increased in parietal region to response for only pleasant stimulus, for another type of stimulus ("rough," "thorny", "recognizable") distinction of amplitude was not observed. Correlation dimension D2 was higher in healthy children compared to children with ASD (main effect ANOVA). In ASD group D2 was lower for pleasant and unpleasant compared to the background in the right parietal area. Hilbert transform changes in the frequency of the theta rhythm found only for a rough tactile stimulation compared with healthy participants only in the right parietal area. Children with autism spectrum disorders and healthy children were responded to tactile stimulation differently with specific frequency distribution alpha and theta band in the right parietal area. Thus, our data supports the hypothesis that rsEEG may serve as a sensitive index of altered neural activity caused by ASD. Children with autism have difficulty in distinguishing the emotional stimuli ("pleasant," "rough," "prickly" and "recognizable").

Keywords: autism, tactile stimulation, Hilbert transform, pediatric electroencephalography

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Authors: Mamta Jat

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Background: The increased longevity has resulted in the increase in the percentage of the global population aged 60 years or over. With this “demographic transition” towards ageing, “epidemiologic transition” is also taking place characterised by growing share of non-communicable diseases in the overall disease burden. So, many of the older adults are ageing with chronic disease and high levels of frailty which often results in lower levels of quality of life. Although frailty may be increasingly common in older adults, prevention or, at least, delay the onset of late-life adverse health outcomes and disability is necessary to maintain the health and functional status of the ageing population. This is an effort using SAGE data to assess levels of frailty and its socio-demographic correlates and its relation with quality of life in LMICs of India, China, Ghana, Mexico, Russia and South Africa in a comparative perspective. Methods: The data comes from multi-country Study on Global AGEing and Adult Health (SAGE), consists of nationally representative samples of older adults in six low and middle-income countries (LMICs): China, Ghana, India, Mexico, the Russian Federation and South Africa. For our study purpose, we will consider only 50+ year’s respondents. The logistic regression model has been used to assess the correlates of frailty. Multinomial logistic regression has been used to study the effect of frailty on QOL (quality of life), controlling for the effect of socio-economic and demographic correlates. Results: Among all the countries India is having highest mean frailty in males (0.22) and females (0.26) and China with the lowest mean frailty in males (0.12) and females (0.14). The odds of being frail are more likely with the increase in age across all the countries. In India, China and Russia the chances of frailty are more among rural older adults; whereas, in Ghana, South Africa and Mexico rural residence is protecting against frailty. Among all countries china has high percentage (71.46) of frail people in low QOL; whereas Mexico has lowest percentage (36.13) of frail people in low QOL.s The risk of having low and middle QOL is significantly (p<0.001) higher among frail elderly as compared to non–frail elderly across all countries with controlling socio-demographic correlates. Conclusion: Women and older age groups are having higher frailty levels than men and younger aged adults in LMICs. The mean frailty scores demonstrated a strong inverse relationship with education and income gradients, while lower levels of education and wealth are showing higher levels of frailty. These patterns are consistent across all LMICs. These data support a significant role of frailty with all other influences controlled, in having low QOL as measured by WHOQOL index. Future research needs to be built on this evolving concept of frailty in an effort to improve quality of life for frail elderly population, in LMICs setting.

Keywords: Keywords: Ageing, elderly, frailty, quality of life

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Authors: Rebecca Laycock

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Many Urban Agriculture (UA) initiatives, including community/allotment gardens, Community Supported Agriculture, and community/social farms, depend on volunteers. However, initiatives supported or run by volunteers are often faced with a high turnover of labour as a result of the involvement of episodic volunteers (a term describing ad hoc, one-time, and seasonal volunteers), leading to challenges with maintaining project continuity and retaining skills/knowledge within the initiative. This is a notable challenge given that food growing is a knowledge intensive activity where the fruits of labour appear months or sometimes years after investment. Participatory Action Research (PAR) is increasingly advocated for in the field of UA as a solution-oriented approach to research, providing concrete results in addition to advancing theory. PAR is a cyclical methodological approach involving researchers and stakeholders collaboratively 'identifying' and 'theorising' an issue, 'planning' an action to address said issue, 'taking action', and 'reflecting' on the process. Through iterative cycles and prolonged engagement, the theory is developed and actions become better tailored to the issue. The demand for PAR in UA research means that understanding how to use PAR with episodic volunteers is of critical importance. The aim of this paper is to explore (1) the challenges of doing PAR in UA initiatives with episodic volunteers, and (2) how PAR can be harnessed to advance sustainable development of UA through theoretically-informed action. A 2.5 year qualitative PAR study on three English case study student-led food growing initiatives took place between 2014 and 2016. University UA initiatives were chosen as exemplars because most of their volunteers were episodic. Data were collected through 13 interviews, 6 workshops, and a research diary. The results were thematically analysed through eclectic coding using Computer-Assisted Qualitative Data Analysis Software (NVivo). It was found that the challenges of doing PAR with transient participants were (1) a superficial understanding of issues by volunteers because of short term engagement, resulting in difficulties ‘identifying’/‘theorising’ issues to research; (2) difficulties implementing ‘actions’ given those involved in the ‘planning’ phase often left by the ‘action’ phase; (3) a lack of capacity of participants to engage in research given the ongoing challenge of maintaining participation; and (4) that the introduction of the researcher acted as an ‘intervention’. The involvement of a long-term stakeholder (the researcher) changed the group dynamics, prompted critical reflections that had not previously taken place, and improved continuity. This posed challenges for providing a genuine understanding the episodic volunteering PAR initiatives, and also challenged the notion of what constitutes an ‘intervention’ or ‘action’ in PAR. It is recommended that researchers working with episodic volunteers using PAR should (1) adopt a first-person approach by inquiring into the researcher’s own experience to enable depth in theoretical analysis to manage the potentially superficial understandings by short-term participants; and (2) establish safety mechanisms to address the potential for the research to impose artificial project continuity and knowledge retention that will end when the research does. Through these means, we can more effectively use PAR to conduct solution-oriented research about UA.

Keywords: community garden, continuity, first-person research, higher education, knowledge retention, project management, transience, university

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Authors: Camilo Cerda Sarabia, Fernanda Bravo Cornejo, Diego Santibanez Oyarce, Hugo Osses Prado, Esteban Gómez Terán, Belén Diaz Diaz, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

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Antimicrobial resistance (AMR) represents a significant and rapidly escalating global health threat. Projections estimate that by 2050, AMR infections could claim up to 10 million lives annually. Respiratory infections, in particular, pose a severe risk not only to individual patients but also to the broader public health system. Despite the alarming rise in resistant respiratory infections, AMR within the lung microbiome (microbial community) remains underexplored and poorly characterized. The lungs, as a complex and dynamic microbial environment, host diverse communities of microorganisms whose interactions and resistance mechanisms are not fully understood. Unlike studies that focus on individual genomes, analyzing the entire microbiome provides a comprehensive perspective on microbial interactions, resistance gene transfer, and community dynamics, which are crucial for understanding AMR. However, this holistic approach introduces significant computational challenges and exposes the limitations of traditional analytical methods such as the difficulty of identifying the AMR. Machine learning has emerged as a powerful tool to overcome these challenges, offering the ability to analyze complex genomic data and uncover novel insights into AMR that might be overlooked by conventional approaches. This study investigates microbial resistance within the lung microbiome using unsupervised machine learning approaches to uncover resistance patterns and potential clinical associations. it downloaded and selected lung microbiome data from HumanMetagenomeDB based on metadata characteristics such as relevant clinical information, patient demographics, environmental factors, and sample collection methods. The metadata was further complemented by details on antibiotic usage, disease status, and other relevant descriptions. The sequencing data underwent stringent quality control, followed by a functional profiling focus on identifying resistance genes through specialized databases like Antibiotic Resistance Database (CARD) which contains sequences of AMR gene sequence and resistance profiles. Subsequent analyses employed unsupervised machine learning techniques to unravel the structure and diversity of resistomes in the microbial community. Some of the methods employed were clustering methods such as K-Means and Hierarchical Clustering enabled the identification of sample groups based on their resistance gene profiles. The work was implemented in python, leveraging a range of libraries such as biopython for biological sequence manipulation, NumPy for numerical operations, Scikit-learn for machine learning, Matplotlib for data visualization and Pandas for data manipulation. The findings from this study provide insights into the distribution and dynamics of antimicrobial resistance within the lung microbiome. By leveraging unsupervised machine learning, we identified novel resistance patterns and potential drivers within the microbial community.

Keywords: antibiotic resistance, microbial community, unsupervised machine learning., sequences of AMR gene

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Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of the flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on the spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts, as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with an attention mechanism. In previous works on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work, with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on the presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: machine learning, classification and regression, gene circuit design, bidirectional transformers

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Authors: Vidhya Venugopal, Jeremiah Chinnadurai, Rebekah A. I. Lucas, Tord Kjellstrom, Bruno Lemke

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Introduction: The effects of climate change (CC) are largely discussed across the globe in terms of impacts on the environment and the general population, but the impacts on workers remain largely unexplored. The predicted rise in temperatures and heat events in the CC scenario have health implications on millions of workers in physically exerting jobs. The current health and productivity risks associated with heat exposures are characterized, future risk estimates as temperature rises and recommendations towards developing protective and preventive occupational health and safety guidelines for India are discussed. Methodology: Cross-sectional studies were conducted in several occupational sectors with workers engaged in moderate to heavy labor (n=1580). Quantitative data on heat exposures (WBGT°C), physiological heat strain indicators viz., Core temperature (CBT), Urine specific gravity (USG), Sweat rate (SwR) and qualitative data on heat-related health symptoms and productivity losses were collected. Data were analyzed for associations between heat exposures, health and productivity outcomes related to heat stress. Findings: Heat conditions exceeded the Threshold Limit Value (TLV) for safe manual work in 66% of the workers across several sectors (Avg.WBGT of 28.7°C±3.1°C). Widespread concerns about heat-related health outcomes (86%) were prevalent among workers exposed to high TLVs, with excessive sweating, fatigue and tiredness being commonly reported by workers. The heat stress indicators, core temperature (14%), Sweat rate (8%) and USG (9%), were above normal levels in the study population. A significant association was found between rise in Core Temperatures and WBGT exposures (p=0.000179) Elevated USG and SwR in the worker population indicate moderate dehydration, with potential risks of developing heat-related illnesses. In a steel industry with high heat exposures, an alarming 9% prevalence of kidney/urogenital anomalies was observed in a young workforce. Heat exposures above TLVs were associated with significantly increased odds of various adverse health outcomes (OR=2.43, 95% CI 1.88 to 3.13, p-value = <0.0001) and productivity losses (OR=1.79, 95% CI 1.32 to 2.4, p-value = 0.0002). Rough estimates for the number of workers who would be subjected to higher than TLV levels in the various RCP scenarios are RCP2.6 =79%, RCP4.5 & RCP6 = 81% and at RCP 8.5 = 85%. Rising temperatures due to CC has the capacity to further reduce already compromised health and productivity by subjecting the workers to increased heat exposures in the RCP scenarios are of concern for the country’s occupational health and economy. Conclusion: The findings of this study clearly identify that health protection from hot weather will become increasingly necessary in the Indian subcontinent and understanding the various adaptation techniques needs urgent attention. Further research with a multi-targeted approach to develop strategies for implementing interventions to protect the millions of workers is imperative. Approaches to include health aspects of climate change within sectoral and climate change specific policies should be encouraged, via a number of mechanisms, such as the “Health in All Policies” approach to avert adverse health and productivity consequences as climate change proceeds.

Keywords: heat stress, occupational health, productivity loss, heat strain, adverse health outcomes

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Authors: Amao Funmilayo Lanrewaju

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The study examined the socio-economic characteristics of the residents in selected urban fringes of Ibadan; identified and examined the housing and neighbourhood characteristics and evaluated housing quality in the study area. It analysed the relationship between the socio-economic characteristics of the residents, housing and neighbourhood characteristics as well as housing quality in the study area. This was with a view to providing information that would enhance the housing quality in urban fringes of Ibadan. Primary and secondary data were used for the study. A survey of eleven purposively selected communities from Oluyole and Egbeda local government areas in the urban fringes was conducted through a questionnaire administration and expert rating by five independent assessors (Qualified Architects) using penalty scoring within similar time-frames. The study employed a random sampling method to select a sample size of 480 houses representing 5% of the sampling frame of 9600 houses. Respondent in the first house was selected randomly and subsequently every 20th house in the streets involved was systematically selected for questionnaire administration, usually a household-head per building. The structured questionnaire elicited information on socio-economic characteristics of the residents, housing and neighbourhood characteristics, factors affecting housing quality and housing quality in the study area. Secondary data obtained for the study included the land-use plan of Ibadan from previous publications, housing demographics, population figures from relevant institutions and other published materials. The data collected were analysed using descriptive and inferential statistics such as frequency distribution, Cross tabulation, Correlation Analysis, Analysis of Variance (ANOVA) and Relative Importance Index (RII). The result of the survey revealed that respondents from the Yoruba ethnic group constituted the majority, comprising 439 (91.5%) of the 480 respondents from the two local government areas selected. It also revealed that the type of tenure status of majority of the respondents in the two local government areas was self-ownership (234, 48.8%), while 44.0% of the respondents acquired their houses through personal savings. Cross tabulation indicated that majority (67.1%, 322 out of 480) of the respondents were low-income earners. The study showed that both housing and neighbourhood services were not adequately provided across neighbourhoods in the study area. Correlation analysis indicated a significant relationship between respondents’ socio–economic status and their general housing quality (r=0.46; p-value of 0.01< 0.05). The ANOVA indicated that the relationship between socio-economic characteristics of the residents, housing and neighbourhood characteristics in the study area was significant (F=18.289, p=0.00; the coefficient of determination R2= 0.192). The findings from the study however revealed that there was no significant difference in the results obtained from users based evaluation and expert rating. The study concluded that housing quality in the urban fringes of Ibadan is generally poor and the socio-economic status of the residents significantly influenced the housing quality.

Keywords: housing quality, urban fringes, economic status, poverty

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Authors: Halima Sadia Qureshi, Urooj Sadiq, Noshi Eram Zaman

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The goal of this study was to see how cognitive behavior hypnotherapy affected nonsuicidal self-injury. DSM 5 invites the researchers to explore the newly added condition under the chapter of conditions under further study named Nonsuicidal self-injury disorder. To date, no empirical sound intervention has been proven effective for NSSI as given in DSM 5. Nonsuicidal self-injury is defined by DSM 5 as harming one's self physically, without suicidal intention. Around 7.6% of teenagers are expected to fulfill the NSSI disorder criteria. 3 Adolescents, particularly university students, account for around 87 percent of self-harm studies. Furthermore, one of the risks associated with NSSI is an increased chance of suicide attempts, and in most cases, the cycle repeats again. 6 The emotional and psychological components of the illness might lead to suicide, either intentionally or unintentionally. 7 According to a research done at a Pakistani military hospital, over 80% of participants had no intention of committing suicide. Furthermore, it has been determined that improvements in NSSI prevention and intervention are necessary as a stand-alone strategy. The quasi-experimental study took place in Islamabad and Rawalpindi, Pakistan, from May 2019 to April 2020 and included students aged 18 to 25 years old from several institutions and colleges in the twin cities. According to the Diagnostic and Statistical Manual of Mental Disorders 5th edition, the individuals were assessed for >2 episodes without suicidal intent using the intentional self-harm questionnaire. The Clinician Administered Nonsuicidal Self-Injury Disorder Index (CANDI) was used to assess the individual for NSSI condition. Symptom checklist-90 (SCL-90) was used to screen the participants for differential diagnosis. Mclean Screening Instrument for Borderline Personality Disorder (MSI-BPD) was used to rule out the BPD cases. The selected participants, n=106 from the screening sample of 600, were selected. They were further screened to meet the inclusion and exclusion criteria, and the total of n=71 were split into two groups: intervention and control. The intervention group received cognitive behavior hypnotherapy for the next three months, whereas the control group received no treatment. After the period of three months, both the groups went through the post assessment, and after the three months’ period, follow-up assessment was conducted. The groups were evaluated, and SPSS 25 was used to analyse the data. The results showed that each of the two groups had 30 (50 percent) of the 60 participants. There were 41 males (68 percent) and 19 girls (32 percent) in all. The bulk of the participants were between the ages of 21 and 23. (48 percent). Self-harm events were reported by 48 (80 percent) of the pupils, and suicide ideation was found in 6 (ten percent). In terms of pre- and post-intervention values (d=4.90), post-intervention and follow-up assessment values (d=0.32), and pre-intervention and follow-up values (d=5.42), the study's effect size was good. The comparison of treatment and no-treatment groups revealed that treatment was more successful than no-treatment, F (1, 58) = 53.16, p.001. The results reveal that the treatment manual of CBH is effective for Nonsuicidal self-injury disorder.

Keywords: NSSI, nonsuicidal self injury disorder, self-harm, self-injury, Cognitive behaviour hypnotherapy, CBH

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Authors: Jagmeet S. Kanwal, Julia F. Langley

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Music can heal the body, but a mechanistic understanding of this phenomenon is lacking. This study explores the effects of music presentation on neurologic and physiologic responses leading to metabolic changes in the human body. The mind and body co-exist in a corporeal entity and within this framework, sickness ensues when the mind-body balance goes awry. It is further hypothesized that music has the capacity to directly reset this balance. Two lines of inquiry taken together can provide a mechanistic understanding of this phenomenon 1) Empirical evidence for a sound-sensitive pressure sensor system in the body, and 2) The notion of a “healing center” within the brain that is activated by specific patterns of sounds. From an acoustics perspective, music is spatially distributed as pressure waves ranging from a few cm to several meters in wavelength. These waves interact and propagate in three-dimensions in unique ways, depending on the wavelength. Furthermore, music creates dynamically changing wave-fronts. Frequencies between 200 Hz and 1 kHz generate wavelengths that range from 5'6" to 1 foot. These dimensions are in the range of the body size of most people making it plausible that these pressure waves can geometrically interact with the body surface and create distinct patterns of pressure stimulation across the skin surface. For humans, short wavelength, high frequency (> 200 Hz) sounds are best received via cochlear receptors. For low frequency (< 200 Hz), long wavelength sound vibrations, however, the whole body may act as an ideal receiver. A vast array of highly sensitive pressure receptors (Pacinian corpuscles) is present just beneath the skin surface, as well as in the tendons, bones, several organs in the abdomen, and the sexual organs. Per the available empirical evidence, these receptors contribute to music perception by allowing the whole body to function as a sound receiver, and knowledge of how they function is essential to fully understanding the therapeutic effect of music. Neuroscientific studies have established that music stimulates the limbic system that can trigger states of anxiety, arousal, fear, and other emotions. These emotional states of brain activity play a crucial role in filtering top-down feedback from thoughts and bottom-up sensory inputs to the autonomic system, which automatically regulates bodily functions. Music likely exerts its pleasurable and healing effects by enhancing functional and effective connectivity and feedback mechanisms between brain regions that mediate reward, autonomic, and cognitive processing. Stimulation of pressure receptors under the skin by low-frequency music-induced sensations can activate multiple centers in the brain, including the amygdala, the cingulate cortex, and nucleus accumbens. Melodies in music in the low (< 600 Hz) frequency range may augment auditory inputs after convergence of the pressure-sensitive inputs from the vagus nerve onto emotive processing regions within the limbic system. The integration of music-generated auditory and somato-visceral inputs may lead to a synergistic input to the brain that promotes healing. Thus, music can literally heal humans through “touch” as it energizes the brain’s autonomic system for restoring homeostasis.

Keywords: acoustics, brain, music healing, pressure receptors

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Authors: Adriana Haulica

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Powered by Machine Learning, Precise medicine is tailored by now to use genetic and molecular profiling, with the aim of optimizing the therapeutic benefits for cohorts of patients. As the majority of Machine Language algorithms come from heuristics, the outputs have contextual validity. This is not very restrictive in the sense that medicine itself is not an exact science. Meanwhile, the progress made in Molecular Biology, Bioinformatics, Computational Biology, and Precise Medicine, correlated with the huge amount of human biology data and the increase in computational power, opens new healthcare challenges. A more accurate diagnosis is needed along with real-time treatments by processing as much as possible from the available information. The purpose of this paper is to present a deeper vision for the future of Artificial Intelligence in Precise medicine. In fact, actual Machine Learning algorithms use standard mathematical knowledge, mostly Euclidian metrics and standard computation rules. The loss of information arising from the classical methods prevents obtaining 100% evidence on the diagnosis process. To overcome these problems, we introduce MEDICOMPILLS, a new architectural concept tool of information processing in Precise medicine that delivers diagnosis and therapy advice. This tool processes poly-field digital resources: global knowledge related to biomedicine in a direct or indirect manner but also technical databases, Natural Language Processing algorithms, and strong class optimization functions. As the name suggests, the heart of this tool is a compiler. The approach is completely new, tailored for omics and clinical data. Firstly, the intrinsic biological intuition is different from the well-known “a needle in a haystack” approach usually used when Machine Learning algorithms have to process differential genomic or molecular data to find biomarkers. Also, even if the input is seized from various types of data, the working engine inside the MEDICOMPILLS does not search for patterns as an integrative tool. This approach deciphers the biological meaning of input data up to the metabolic and physiologic mechanisms, based on a compiler with grammars issued from bio-algebra-inspired mathematics. It translates input data into bio-semantic units with the help of contextual information iteratively until Bio-Logical operations can be performed on the base of the “common denominator “rule. The rigorousness of MEDICOMPILLS comes from the structure of the contextual information on functions, built to be analogous to mathematical “proofs”. The major impact of this architecture is expressed by the high accuracy of the diagnosis. Detected as a multiple conditions diagnostic, constituted by some main diseases along with unhealthy biological states, this format is highly suitable for therapy proposal and disease prevention. The use of MEDICOMPILLS architecture is highly beneficial for the healthcare industry. The expectation is to generate a strategic trend in Precise medicine, making medicine more like an exact science and reducing the considerable risk of errors in diagnostics and therapies. The tool can be used by pharmaceutical laboratories for the discovery of new cures. It will also contribute to better design of clinical trials and speed them up.

Keywords: bio-semantic units, multiple conditions diagnosis, NLP, omics

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Authors: Christine Böckmann, Julia Rosemann

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We present an inversion algorithm that is used in the European Aerosol Lidar Network for the inversion of data collected with multi-wavelength Raman lidar. These instruments measure backscatter coefficients at 355, 532, and 1064 nm, and extinction coefficients at 355 and 532 nm. The algorithm is based on manually controlled inversion of optical data which allows for detailed sensitivity studies and thus provides us with comparably high quality of the derived data products. The algorithm allows us to derive particle effective radius, volume, surface-area concentration with comparably high confidence. The retrieval of the real and imaginary parts of the complex refractive index still is a challenge in view of the accuracy required for these parameters in climate change studies in which light-absorption needs to be known with high accuracy. Single-scattering albedo (SSA) can be computed from the retrieve microphysical parameters and allows us to categorize aerosols into high and low absorbing aerosols. From mathematical point of view the algorithm is based on the concept of using truncated singular value decomposition as regularization method. This method was adapted to work for the retrieval of the particle size distribution function (PSD) and is called hybrid regularization technique since it is using a triple of regularization parameters. The inversion of an ill-posed problem, such as the retrieval of the PSD, is always a challenging task because very small measurement errors will be amplified most often hugely during the solution process unless an appropriate regularization method is used. Even using a regularization method is difficult since appropriate regularization parameters have to be determined. Therefore, in a next stage of our work we decided to use two regularization techniques in parallel for comparison purpose. The second method is an iterative regularization method based on Pade iteration. Here, the number of iteration steps serves as the regularization parameter. We successfully developed a semi-automated software for spherical particles which is able to run even on a parallel processor machine. From a mathematical point of view, it is also very important (as selection criteria for an appropriate regularization method) to investigate the degree of ill-posedness of the problem which we found is a moderate ill-posedness. We computed the optical data from mono-modal logarithmic PSD and investigated particles of spherical shape in our simulations. We considered particle radii as large as 6 nm which does not only cover the size range of particles in the fine-mode fraction of naturally occurring PSD but also covers a part of the coarse-mode fraction of PSD. We considered errors of 15% in the simulation studies. For the SSA, 100% of all cases achieve relative errors below 12%. In more detail, 87% of all cases for 355 nm and 88% of all cases for 532 nm are well below 6%. With respect to the absolute error for non- and weak-absorbing particles with real parts 1.5 and 1.6 in all modes the accuracy limit +/- 0.03 is achieved. In sum, 70% of all cases stay below +/-0.03 which is sufficient for climate change studies.

Keywords: aerosol particles, inverse problem, microphysical particle properties, regularization

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Authors: Atilola O. Abidemi-Iromini, Oluayo A. Bello-Olusoji, Immanuel A. Adebayo

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Ecological studies were carried out in Asejire Reservoir (AR) and Lagos Lagoon (LL), Southwest Nigeria from January 2012 to December 2013 to determine the health status of Chrysichthys nigrodigitatus (CN) and Oreochromis niloticus (ON). The fish species samples were collected every month, these were separated into sexes, and growth pattern {length, (cm); weight (g), Isometric index, condition factor} were measured. Heavy metals (lead (Pb), iron (Fe), zinc (Zn), copper (Cu), and chromium (Cr) in ppm concentrations were also determined while bacteria occurrence(s), (load and prevalence) on fish skins, gills and intestine in the two ecological zones were determined. The fish ratio collected is in range with normal aquatic (1: 1+) male: female ratio. Growth assessment determined revealed no significant difference in length and weight in O. niloticus between locations, but a significant difference in weight occurred in C. nigrodigitatus between locations, with a higher weight (196.06 ±0.16 g) from Lagos Lagoon. Highest condition factor (5.25) was recorded in Asejire Reservoir O. niloticus, (ARON); and lowest condition factor (1.64) was observed in Asejire Reservoir C. nigrodigitatus (ARCN); as this indicated a negative allometric value which is normal in Bagridae species because it increases more in Length to weight gain than for the Cichlidae growth status. Normal growth rate (K > 1) occurred between sexes, with the male species having higher K - factors than female species within locations, between locations, between species, and within species, except for female C. nigrodigitatus having higher condition factor (K = 1.75) than male C. nigrodigitatus (K = 1.54) in Asejire Reservoir. The highest isometric value (3.05) was recorded in Asejire Reservoir O. niloticus and lowest in Lagos Lagoon C. nigrodigitatus. Male O. niloticus from Asejire Reservoir had highest isometric value, and O. niloticus species had higher condition factor which ranged between isometric (b ≤ 3) and positive allometric (b > 3), hence, denoted robustness of fish to grow more in weight than in length; while C. nigrodigitatus fish has negative allometric (b < 3) indicating fish add more length than in weight on growth. The status of condition factors and isometric values obtained is species-specific, and environmental influence, food availability or reproduction factor may as well be contributing factors. The concentrations of heavy metals in fish flesh revealed that Zn (6.52 ±0.82) had the highest, while Cr (0.01±0.00) was ranked lowest; for O. niloticus in Asejire Reservoir. In Lagos Lagoon, heavy metals concentration level revealed that O. niloticus flesh had highest in Zn (4.71±0.25) and lowest in Pb (0.01±0.00). Lagos Lagoon C. nigrodigitatus heavy metal concentration level revealed Zn (9.56±0.96) had highest, while Cr (0.06±0.01) had lowest; and Asejire Reservoir C. nigrodigitatus heavy metal level revealed that Zn (8.26 ±0.74) had highest, and Cr (0.08±0.00) had lowest. In all, Zinc (Zn) was top-ranked in level among species.

Keywords: Oreochromis niloticus, growth status, Chrysichthys nigrodigitatus, environments, heavy metals

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Authors: Mustafa M. Donma, Orkide Donma

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Iron is physiologically essential. However, it also participates in the catalysis of free radical formation reactions. Its deficiency is associated with amplified health risks. This trace element establishes some links with another physiological process related to cell death, apoptosis. Both iron deficiency and iron overload are closely associated with apoptosis. Soluble tumor necrosis factor-like weak inducer of apoptosis (sTWEAK) has the ability to trigger apoptosis and plays a dual role in the physiological versus pathological inflammatory responses of tissues. The aim of this study was to investigate the status of these parameters as well as the associations among them in children with obesity, a low-grade inflammatory state. The study was performed on groups of children with normal body mass index (N-BMI) and obesity. Forty-three children were included in each group. Based upon age- and sex-adjusted BMI percentile tables prepared by World Health Organization, children whose values varied between 85 and 15 were included in N-BMI group. Children whose BMI percentile values were between 99 and 95 comprised obese (OB) group. Institutional ethical committee approval and informed consent forms were taken prior to the study. Anthropometric measurements (weight, height, waist circumference, hip circumference, head circumference, neck circumference) and blood pressure values (systolic blood pressure and diastolic blood pressure) were recorded. Routine biochemical analysis including serum iron, total iron binding capacity (TIBC), transferrin saturation percent (Tf Sat %), and ferritin were performed. Soluble tumor necrosis factor-like weak inducer of apoptosis levels were determined by enzyme-linked immunosorbent assay. Study data was evaluated using appropriate statistical tests performed by the statistical program SPSS. Serum iron levels were 91±34 mcrg/dl and 75±31 mcrg/dl in N-BMI and OB children, respectively. The corresponding values for TIBC, Tf Sat %, ferritin were 265 mcrg/dl vs 299 mcrg/dl, 37.2±19.1 % vs 26.7±14.6 %, and 41±25 ng/ml vs 44±26 ng/ml. in N-BMI and OB groups, sTWEAK concentrations were measured as 351 ng/L and 325 ng/L, respectively (p>0.05). Correlation analysis revealed significant associations between sTWEAK levels and iron related parameters (p<0.05) except ferritin. In conclusion, iron contributes to apoptosis. Children with iron deficiency have decreased apoptosis rate in comparison with that of healthy children. sTWEAK is inducer of apoptosis. Obese children had lower levels of both iron and sTWEAK. Low levels of sTWEAK are associated with several types of cancers and poor survival. Although iron deficiency state was not observed in this study, the correlations detected between decreased sTWEAK and decreased iron as well as Tf Sat % values were valuable findings, which point out decreased apoptosis. This may induce a proinflammatory state, potentially leading to malignancies in the future lives of obese children.

Keywords: apoptosis, children, iron-related parameters, obesity, soluble tumor necrosis factor-like weak inducer of apoptosis

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Authors: Andrew D. Henshaw

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The research examines the influence of familial and kinship based leadership on the resilience of politically violent organizations. Organizations of this type frequently fight in the same conflicts though are called 'terrorist' or 'insurgent' depending on political foci of the time, and thus different approaches are used to combat them. The research considers them correlated phenomena with significant overlap and identifies strengths and vulnerabilities in resilience processes. The research employs paired case studies to examine resilience in organizations under significant external pressure, and achieves this by measuring three variables. 1: Organizational robustness in terms of leadership and governance. 2. Bounce-back response efficiency to external pressures and adaptation to endogenous and exogenous shock. 3. Perpetuity of operational and attack capability, and political legitimacy. The research makes three hypotheses. First, familial/kinship leadership groups have a significant effect on organizational resilience in terms of informal operations. Second, non-familial/kinship organizations suffer in terms of heightened security transaction costs and social economics surrounding recruitment, retention, and replacement. Third, resilience in non-familial organizations likely stems from critical external supports like state sponsorship or powerful patrons, rather than organic resilience dynamics. The case studies pair familial organizations with non-familial organizations. Set 1: The Haqqani Network (HQN) - Pair: Lashkar-e-Toiba (LeT). Set 2: Jemaah Islamiyah (JI) - Pair: The Abu Sayyaf Group (ASG). Case studies were selected based on three requirements, being: contrasting governance types, exposure to significant external pressures and, geographical similarity. The case study sets were examined over 24 months following periods of significantly heightened operational activities. This enabled empirical measurement of the variables as substantial external pressures came into force. The rationale for the research is obvious. Nearly all organizations have some nexus of familial interconnectedness. Examining familial leadership networks does not provide further understanding of how terrorism and insurgency originate, however, the central focus of the research does address how they persist. The sparse attention to this in existing literature presents an unexplored yet important area of security studies. Furthermore, social capital in familial systems is largely automatic and organic, given at birth or through kinship. It reduces security vetting cost for recruits, fighters and supporters which lowers liabilities and entry costs, while raising organizational efficiency and exit costs. Better understanding of these process is needed to exploit strengths into weaknesses. Outcomes and implications of the research have critical relevance to future operational policy development. Increased clarity of internal trust dynamics, social capital and power flows are essential to fracturing and manipulating kinship nexus. This is highly valuable to external pressure mechanisms such as counter-terrorism, counterinsurgency, and strategic intelligence methods to penetrate, manipulate, degrade or destroy the resilience of politically violent organizations.

Keywords: Counterinsurgency (COIN), counter-terrorism, familial influence, insurgency, intelligence, kinship, resilience, terrorism

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Authors: Stacey Herzog, Mitchell McCleary, Istvan Kovacs

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Purpose: Maximal strength and maximal power are key athletic abilities in many sports disciplines. In recent years, velocity-based training (VBT) with a relatively high 75-85% 1RM resistance has been popularized in preparation for powerlifting and various other sports. The purpose of this study was to discover differences between beginner/intermediate and advanced lifters’ push/press performances after a heavy resistance-based BP training program. Methods: A six-week, three-workouts per week program was administered to 52 young, physically active adults (age: 22.4±5.1; 12 female). The majority of the participants (84.6%) had prior experience in bench pressing. Typical workouts began with BP using 75-95% 1RM in the 1-5 repetition range. The sets in the lower part of the range (75-80% 1RM) were performed with velocity-focus as well. The BP sets were followed by seated dumbbell presses and six additional upper-body assistance exercises. Pre- and post-tests were conducted on five test exercises: one-repetition maximum BP (1RM), calculated relative strength index: BP/BW (RSI), four-repetition maximal-effort dynamic BP for peak concentric velocity with 80% 1RM (4RV), 4-repetition ballistic pushups (BPU) for height (4PU), and seated medicine ball toss for distance (MBT). For analytic purposes, the participant group was divided into two subgroups: self-indicated beginner or intermediate initial resistance training status (BITS) [n=21, age: 21.9±3.6; 10 female] and advanced initial resistance training status (ATS) [n=31, age: 22.7±5.9; 2 female]. Pre- and post-test results were compared within subgroups. Results: Paired-sample t-tests indicated significant within-group improvements in all five test exercises in both groups (p < 0.05). BITS improved 18.1 lbs. (13.0%) in 1RM, 0.099 (12.8%) in RSI, 0.133 m/s (23.3%) in 4RV, 1.55 in. (27.1%) in BPU, and 1.00 ft. (5.8%) in MBT, while the ATS group improved 13.2 lbs. (5.7%) in 1RM, 0.071 (5.8%) in RSI, 0.051 m/s (9.1%) in 4RV, 1.20 in. (13.7%) in BPU, and 1.15 ft. (5.5%) in MBT. Conclusion: While the two training groups had different initial resistance training backgrounds, both showed significant improvements in all test exercises. As expected, the beginner/intermediate group displayed better relative improvements in four of the five test exercises. However, the medicine ball toss, which had the lightest resistance among the tests, showed similar relative improvements between the two groups. These findings relate to two important training principles: specificity and transfer. The ATS group had more specific experiences with heavy-resistance BP. Therefore, fewer improvements were detected in their test performances with heavy resistances. On the other hand, while the heavy resistance-based training transferred to increased power outcomes in light-resistance power exercises, the difference in the rate of improvement between the two groups disappeared. Practical applications: Based on initial training status, S&C coaches should expect different performance gains in maximal strength training-specific test exercises. However, the transfer from maximal strength to a non-training-specific performance category along the F-v curve continuum (i.e., light resistance and high velocity) might not depend on initial training status.

Keywords: exercise, power, resistance training, strength

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Authors: Terryann Clark, Kabir Dasgupta, Sonia Lewycka, Gail Pacheco, Alexander Plum

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This paper focused on two main research aims using data from the Growing Up in New Zealand (GUINZ) birth cohort: 1. To examine ethnic differences in life-course trajectories in the use and experience of healthcare services in early childhood years (namely immunisation, dental checks and use of General Practitioners (GPs)) 2. To quantify the contribution of relevant explanatory factors to ethnic differences. Current policy in New Zealand indicates there should be, in terms of associated direct costs, equitable access by ethnicity for healthcare services. However, empirical evidence points to persistent ethnic gaps in several domains. For example, the data highlighted that Māori have the lowest immunisation rates, across a number of time points in early childhood – despite having a higher antenatal intention to immunise relative to NZ European. Further to that, NZ European are much more likely to have their first-choice lead maternity caregiver (LMC) and use child dental services compared to all ethnicities. Method: This research explored the underlying mechanisms behind ethnic differences in the use and experience of child healthcare services. First, a multivariate regression analysis was used to adjust raw ethnic gaps in child health care utilisation by relevant covariates. This included a range of factors, encompassing mobility, socio-economic status, mother and child characteristics, household characteristics and other social aspects. Second, a decomposition analysis was used to assess the proportion of each ethnic gap that can be explained, as well as the main drivers behind the explained component. The analysis for both econometric approaches was repeated for each data time point available, which included antenatal, 9 months, 2 years and 4 years post-birth. Results: The following findings emerged: There is consistent evidence that Asian and Pacific peoples have a higher likelihood of child immunisation relative to NZ Europeans and Māori. This was evident at all time points except one. Pacific peoples had a lower rate relative to NZ European for receiving all first-year immunisations on time. For a number of potential individual and household predictors of healthcare service utilisation, the association is time-variant across early childhood. For example, socio-economic status appears highly relevant for timely immunisations in a child’s first year, but is then insignificant for the 15 month immunisations and those at age 4. Social factors play a key role. This included discouragement or encouragement regarding child immunisation. When broken down by source, discouragement by family has the largest marginal effect, followed by health professionals; whereas for encouragement, medical professionals have the largest positive influence. Perceived ethnically motivated discrimination by a health professional was significant with respect to both reducing the likelihood of achieving first choice LMC, and also satisfaction levels with child’s GP. Some ethnic gaps were largely unexplained, despite the wealth of factors employed as independent variables in our analysis. This included understanding why Pacific mothers are much less likely to achieve their first choice LMC compared to NZ Europeans; and also the ethnic gaps for both Māori and Pacific peoples relative to NZ Europeans concerning dental service use.

Keywords: child health, cohort analysis, ethnic disparities, primary healthcare

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Authors: Shenlun Chen, Leonard Wee

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Tumor grading is an essential reference for colorectal cancer (CRC) staging and survival prognostication. The widely used World Health Organization (WHO) grading system defines histological grade of CRC adenocarcinoma based on the density of glandular formation on whole slide images (WSI). Tumors are classified as well-, moderately-, poorly- or un-differentiated depending on the percentage of the tumor that is gland forming; >95%, 50-95%, 5-50% and <5%, respectively. However, manually grading WSIs is a time-consuming process and can cause observer error due to subjective judgment and unnoticed regions. Furthermore, pathologists’ grading is usually coarse while a finer and continuous differentiation grade may help to stratifying CRC patients better. In this study, a deep learning based automatic differentiation grading algorithm was developed and evaluated by survival analysis. Firstly, a gland segmentation model was developed for segmenting gland structures. Gland regions of WSIs were delineated and used for differentiation annotating. Tumor regions were annotated by experienced pathologists into high-, medium-, low-differentiation and normal tissue, which correspond to tumor with clear-, unclear-, no-gland structure and non-tumor, respectively. Then a differentiation prediction model was developed on these human annotations. Finally, all enrolled WSIs were processed by gland segmentation model and differentiation prediction model. The differentiation grade can be calculated by deep learning models’ prediction of tumor regions and tumor differentiation status according to WHO’s defines. If multiple WSIs were possessed by a patient, the highest differentiation grade was chosen. Additionally, the differentiation grade was normalized into scale between 0 to 1. The Cancer Genome Atlas, project COAD (TCGA-COAD) project was enrolled into this study. For the gland segmentation model, receiver operating characteristic (ROC) reached 0.981 and accuracy reached 0.932 in validation set. For the differentiation prediction model, ROC reached 0.983, 0.963, 0.963, 0.981 and accuracy reached 0.880, 0.923, 0.668, 0.881 for groups of low-, medium-, high-differentiation and normal tissue in validation set. Four hundred and one patients were selected after removing WSIs without gland regions and patients without follow up data. The concordance index reached to 0.609. Optimized cut off point of 51% was found by “Maxstat” method which was almost the same as WHO system’s cut off point of 50%. Both WHO system’s cut off point and optimized cut off point performed impressively in Kaplan-Meier curves and both p value of logrank test were below 0.005. In this study, gland structure of WSIs and differentiation status of tumor regions were proven to be predictable through deep leaning method. A finer and continuous differentiation grade can also be automatically calculated through above models. The differentiation grade was proven to stratify CAC patients well in survival analysis, whose optimized cut off point was almost the same as WHO tumor grading system. The tool of automatically calculating differentiation grade may show potential in field of therapy decision making and personalized treatment.

Keywords: colorectal cancer, differentiation, survival analysis, tumor grading

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Authors: Ivana Cabarkapa, Zorica Tomicic, Olivera Duragic

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Antimicrobial resistance represents one of the major challenges facing humanity in the last decades. Increasing antibiotic-resistant pathogens indicates the need for the development of alternative antibacterial drugs and new treatment strategies. One of the innovative emerging treatments in overcoming multidrug-resistant pathogens certainly represents the inhibition anti-quorum sensing system. For most of the food-borne pathogens, the expression of the virulence depends on their capability communication with other members of the population by means of quorum sensing (QS). QS represents a specific way of bacterial intercellular communication, which enabled owing to their ability to detect and to respond to cell population density by gene regulation. QS mechanisms are responsible for controls the pathogenesis, virulence luminescence, motility, sporulation and biofilm formation of many organisms by regulating gene expression. Therefore, research in this field is being an attractive target for the development of new natural antibacterial agents. Anti-QS compounds are known to have the ability to prohibit bacterial pathogenicity. Considering the importance of quorum sensing during bacterial pathogenesis, this research has been focused on evaluation anti - QS properties of four essential oils (EOs) Origanum heracleoticum, Origanum vulgare, Thymus vulgare, and Thymus serpyllum, using biomonitor strain of Chromobacterium violaceum CV026. Tests conducted on Luria Bertani agar supplemented with N hexanol DL homoserine lacton (HHL) 10µl/50ml of agar. The anti-QS potential of the EOs was assayed in a range of concentrations of 200 – 0.39 µl/ml using the disc diffusion method. EOs of Th. vulgaris and T. serpyllum were exhibited anti-QS activity indicated by a non- pigmented ring with a dilution-dependent manner. The lowest dilution of EOs T. vulgaris and T. serpyllum in which they exhibited visually detectable inhibition of violacein synthesis was 6.25 µl/ml for both tested EOs. EOs of O. heracleoticum and O. vulgare were displayed different active principles, i.e., antimicrobial activity indicated by the inner clear ring and anti-QS activity indicated by the outer non-pigmented ring, in a concentration-dependent manner. The lowest dilution of EOs of O. heracleoticum and O. vulgare in which exhibited visually detectable inhibition of violacein synthesis was 1.56 and 3.25 µl/ml, respectively. Considering that, the main constituents of the tested EOs represented by monoterpenes (carvacrol, thymol, γ-terpinene, and p-cymene), anti - QS properties of tested EOs can be mainly attributed to their activity. In particular, from the scientific literature, carvacrol and thymol show a sub-inhibitory effect against foodborne pathogens. Previous studies indicated that sub-lethal concentrations of carvacrol reduced the mobility of bacteria due to the ability of interference using QS mechanism between the bacterial cells, and thereby reducing the ability of biofilm formation The precise mechanism by which carvacrol inhibits biofilm formation is still not fully understood. Our results indicated that EOs displayed different active principles, i.e., antimicrobial activity indicated by the inner clear ring and anti-QS activity indicated by an outer non- pigmented ring with visually detectable inhibition of violacein. Preliminary results suggest that EOs represent a promising alternative for effective control of the emergence and spread of resistant pathogens.

Keywords: anti-quorum sensing activity, Chromobacterium violaceum, essential oils, violacein

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Authors: Manel Hammami, Gabriele Grandi

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In recent years, multilevel inverters have become more attractive for single-phase photovoltaic (PV) systems, due to their known advantages over conventional H-bridge pulse width-modulated (PWM) inverters. They offer improved output waveforms, smaller filter size, lower total harmonic distortion (THD), higher output voltages and others. The most common multilevel converter topologies, presented in literature, are the neutral-point-clamped (NPC), flying capacitor (FC) and Cascaded H-Bridge (CHB) converters. In both NPC and FC configurations, the number of components drastically increases with the number of levels what leads to complexity of the control strategy, high volume, and cost. Whereas, increasing the number of levels in case of the cascaded H-bridge configuration is a flexible solution. However, it needs isolated power sources for each stage, and it can be applied to PV systems only in case of PV sub-fields. In order to improve the ratio between the number of output voltage levels and the number of components, several hybrids and asymmetric topologies of multilevel inverters have been proposed in the literature such as the FC asymmetric H-bridge (FCAH) and the NPC asymmetric H-bridge (NPCAH) topologies. Another asymmetric multilevel inverter configuration that could have interesting applications is the cascaded asymmetric H-bridge (CAH), which is based on a modular half-bridge (two switches and one capacitor, also called level doubling network, LDN) cascaded to a full H-bridge in order to double the output voltage level. This solution has the same number of switches as the above mentioned AH configurations (i.e., six), and just one capacitor (as the FCAH). CAH is becoming popular, due to its simple, modular and reliable structure, and it can be considered as a retrofit which can be added in series to an existing H-Bridge configuration in order to double the output voltage levels. In this paper, an original and effective method for the analysis of the DC-link voltage ripple is given for single-phase asymmetric H-bridge multilevel inverters based on level doubling network (LDN). Different possible configurations of the asymmetric H-Bridge multilevel inverters have been considered and the analysis of input voltage and current are analytically determined and numerically verified by Matlab/Simulink for the case of cascaded asymmetric H-bridge multilevel inverters. A comparison between FCAH and the CAH configurations is done on the basis of the analysis of the DC and voltage ripple for the DC source (i.e., the PV system). The peak-to-peak DC and voltage ripple amplitudes are analytically calculated over the fundamental period as a function of the modulation index. On the basis of the maximum peak-to-peak values of low frequency and switching ripple voltage components, the DC capacitors can be designed. Reference is made to unity output power factor, as in case of most of the grid-connected PV generation systems. Simulation results will be presented in the full paper in order to prove the effectiveness of the proposed developments in all the operating conditions.

Keywords: asymmetric inverters, dc-link voltage, level doubling network, single-phase multilevel inverter

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Authors: Thais O. de Paula, Marjorie R. A. Sarmiento, Francis M. Borges, Alessandra B. Ferreira-Machado, Juliana A. Resende, Dioneia E. Cesar, Vania L. Silva, Claudio G. Diniz

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Obesity is currently a worldwide public health threat, being considered a pandemic multifactorial disease related to the human gut microbiota (GM). Add to that GM is considered an important reservoir of antimicrobial resistance genes (ARG) and little is known on GM and ARG in obesity, considering the altered physiology and xenobiotics intake. As regional and social behavior may play important roles in GM modulation, and most of the studies are based on small sample size and various methodological approaches resulting in difficulties for data comparisons, this study was focused on the investigation of GM bacterial diversity in obese (OB), overweight (OW) and eutrophic individuals (ET) considering their nutritional, clinical and social characteristics; and comparative screening of AGR related to their physiology and xenobiotics intake. Microbial community was accessed by FISH considering phyla as a taxonomic level, and PCR-DGGE followed by dendrograms evaluation (UPGMA method) from fecal metagenome of 72 volunteers classified according to their body mass index (BMI). Nutritional, clinical, social parameters and xenobiotics intake were recorded for correlation analysis. The fecal metagenome was also used as template for PCR targeting 59 different ARG. Overall, 62% of OB were hypertensive, and 12% or 4% were, regarding the OW and ET individuals. Most of the OB were rated as low income (80%). Lower relative bacterial densities were observed in the OB compared to ET for almost all studied taxa (p < 0.05) with Firmicutes/Bacteroidetes ratio increased in the OB group. OW individuals showed a bacterial density representative of GM more likely to the OB. All the participants were clustered in 3 different groups based on the PCR-DGGE fingerprint patterns (C1, C2, C3), being OB mostly grouped in C1 (83.3%) and ET mostly grouped in C3 (50%). The cluster C2 showed to be transitional. Among 27 ARG detected, a cluster of 17 was observed in all groups suggesting a common core. In general, ARG were observed mostly within OB individuals followed by OW and ET. The ratio between ARG and bacterial groups may suggest that AGR were more related to enterobacteria. Positive correlations were observed between ARG and BMI, calories and xenobiotics intake (especially use of sweeteners). As with nutritional and clinical characteristics, our data may suggest that GM of OW individuals behave in a heterogeneous pattern, occasionally more likely to the OB or to the ET. Regardless the regional and social behaviors of our population, the methodological approaches in this study were complementary and confirmatory. The imbalance of GM over the health-disease interface in obesity is a matter of fact, but its influence in host's physiology is still to be clearly elucidated to help understanding the multifactorial etiology of obesity. Although the results are in agreement with observations that GM is altered in obesity, the altered physiology in OB individuals seems to be also associated to the increased xenobiotics intake and may interfere with GM towards antimicrobial resistance, as observed by the fecal metagenome and ARG screening. Support: FAPEMIG, CNPQ, CAPES, PPGCBIO/UFJF.

Keywords: antimicrobial resistance, bacterial diversity, gut microbiota, obesity

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Authors: K. C. Apil, Keshab Sharma, Bigul Pokharel

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Kathmandu Valley, capital city of Nepal houses numerous historical monuments as well as religious structures which are as old as from the 4th century A.D. The city alone is home to seven UNESCO’s world heritage sites including various public squares and religious sanctums which are often regarded as living heritages by various historians and archeological explorers. Recently on April 25, 2015, the capital city including other nearby locations was struck with Gorkha earthquake of moment magnitude (Mw) 7.8, followed by the strongest aftershock of moment magnitude (Mw) 7.3 on May 12. This study reports structural failures and collapse of heritage structures in Kathmandu Valley during the earthquake and presents preliminary findings as to the causes of failures and collapses. Field reconnaissance was carried immediately after the main shock and the aftershock, in major heritage sites: UNESCO world heritage sites, a number of temples and historic buildings in Kathmandu Durbar Square, Patan Durbar Square, and Bhaktapur Durbar Square. Despite such catastrophe, a significant number of heritage structures stood high, performing very well during the earthquake. Preliminary reports from archeological department suggest that 721 of such structures were severely affected, whereas numbers within the valley only were 444 including 76 structures which were completely collapsed. This study presents recorded accelerograms and geology of Kathmandu Valley. Structural typology and architecture of the heritage structures in Kathmandu Valley are briefly described. Case histories of damaged heritage structures, the patterns, and the failure mechanisms are also discussed in this paper. It was observed that performance of heritage structures was influenced by the multiple factors such as structural and architecture typology, configuration, and structural deficiency, local ground site effects and ground motion characteristics, age and maintenance level, material quality etc. Most of such heritage structures are of masonry type using bricks and earth-mortar as a bonding agent. The walls' resistance is mainly compressive, thus capable of withstanding vertical static gravitational load but not horizontal dynamic seismic load. There was no definitive pattern of damage to heritage structures as most of them behaved as a composite structure. Some structures were extensively damaged in some locations, while structures with similar configuration at nearby location had little or no damage. Out of major heritage structures, Dome, Pagoda (2, 3 or 5 tiered temples) and Shikhara structures were studied with similar variables. Studying varying degrees of damages in such structures, it was found that Shikhara structures were most vulnerable one where Dome structures were found to be the most stable one, followed by Pagoda structures. The seismic performance of the masonry-timber and stone masonry structures were slightly better than that of the masonry structures. Regular maintenance and periodic seismic retrofitting seems to have played pivotal role in strengthening seismic performance of the structure. The study also recommends some key functions to strengthen the seismic performance of such structures through study based on structural analysis, building material behavior and retrofitting details. The result also recognises the importance of documentation of traditional knowledge and its revised transformation in modern technology.

Keywords: Gorkha earthquake, field observation, heritage structure, seismic performance, masonry building

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Authors: Suzanne Zazycki, Bamidele Osamika, Heather Craska, Kaelyn Conaway, Reena Murphy, Stephanie Spence

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Invasive Plant Species (IPS) are an important component of effective preservation and conservation of natural lands management. IPS are non-native plants which can aggressively encroach upon native species and pose a significant threat to the ecology, public health, and social welfare of a community. The presence of IPS in U.S. nature preserves has caused economic costs, which has estimated to exceed $26 billion a year. While different methods have been identified to control IPS, few methods have been recognized for early detection of IPS. This study examined identified methods for early detection of IPS in Hueston Woods State Nature Preserve. Mixed methods research design was adopted in this four-phased study. The first phase entailed data gathering, the phase described the characteristics and qualities of IPS and the importance of early detection (ED). The second phase explored ED methods, Geographic Information Systems (GIS) and Citizen Science were discovered as ED methods for IPS. The third phase of the study involved the creation of hotspot maps to identify likely areas for IPS growth. While the fourth phase involved testing and evaluating mobile applications that can support the efforts of citizen scientists in IPS detection. Literature reviews were conducted on IPS and ED methods, and four regional experts from ODNR and Miami University were interviewed. A questionnaire was used to gather information about ED methods used across the state. The findings revealed that geospatial methods, including Unmanned Aerial Vehicles (UAVs), Multispectral Satellites (MSS), and Normalized Difference Vegetation Index (NDVI), are not feasible for early detection of IPS, as they require GIS expertise, are still an emerging technology, and are not suitable for every habitat for the ED of IPS. Therefore, Other ED methods options were explored, which include predicting areas where IPS will grow, which can be done through monitoring areas that are like the species’ native habitat. Through literature review and interviews, IPS are known to grow in frequently disturbed areas such as along trails, shorelines, and streambanks. The research team called these areas “hotspots” and created maps of these hotspots specifically for HW NP to support and narrow the efforts of citizen scientists and staff in the ED of IPS. The results further showed that utilizing citizen scientists in the ED of IPS is feasible, especially through single day events or passive monitoring challenges. The study concluded that the creation of hotspot maps to direct the efforts of citizen scientists are effective for the early detection of IPS. Several recommendations were made, among which is the creation of hotspot maps to narrow the ED efforts as citizen scientists continues to work in the preserves and utilize citizen science volunteers to identify and record emerging IPS.

Keywords: early detection, hueston woods state nature preserve, invasive plant species, hotspots

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