Search results for: Chandan Deep Singh

Authors: Jeremy Jenrette, Z. Y. C. Liu, Pranav Chimote, Edward Fox, Trevor Hastie, Francesco Ferretti

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Suitable shark conservation depends on well-informed population assessments. Direct methods such as scientific surveys and fisheries monitoring are adequate for defining population statuses, but species-specific indices of abundance and distribution coming from these sources are rare for most shark species. We can rapidly fill these information gaps by boosting media-based remote monitoring efforts with machine learning and automation. We created a database of shark images by sourcing 24,546 images covering 219 species of sharks from the web application spark pulse and the social network Instagram. We used object detection to extract shark features and inflate this database to 53,345 images. We packaged object-detection and image classification models into a Shark Detector bundle. We developed the Shark Detector to recognize and classify sharks from videos and images using transfer learning and convolutional neural networks (CNNs). We applied these models to common data-generation approaches of sharks: boosting training datasets, processing baited remote camera footage and online videos, and data-mining Instagram. We examined the accuracy of each model and tested genus and species prediction correctness as a result of training data quantity. The Shark Detector located sharks in baited remote footage and YouTube videos with an average accuracy of 89\%, and classified located subjects to the species level with 69\% accuracy (n =\ eight species). The Shark Detector sorted heterogeneous datasets of images sourced from Instagram with 91\% accuracy and classified species with 70\% accuracy (n =\ 17 species). Data-mining Instagram can inflate training datasets and increase the Shark Detector’s accuracy as well as facilitate archiving of historical and novel shark observations. Base accuracy of genus prediction was 68\% across 25 genera. The average base accuracy of species prediction within each genus class was 85\%. The Shark Detector can classify 45 species. All data-generation methods were processed without manual interaction. As media-based remote monitoring strives to dominate methods for observing sharks in nature, we developed an open-source Shark Detector to facilitate common identification applications. Prediction accuracy of the software pipeline increases as more images are added to the training dataset. We provide public access to the software on our GitHub page.

Keywords: classification, data mining, Instagram, remote monitoring, sharks

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Authors: Vincent Andrew Cappellano

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In the early phases of critical infrastructure system design, translating distributed computing requirements to an architecture has risk given the multitude of approaches (e.g., cloud, edge, fog). In many systems, a single requirement for system uptime / availability is used to encompass the system’s intended operations. However, when architected systems may perform to those availability requirements only during normal operations and not during component failure, or during outages caused by adversary attacks on critical infrastructure (e.g., physical, cyber). System designers lack a structured method to evaluate availability requirements against candidate system architectures through deep degradation scenarios (i.e., normal ops all the way down to significant damage of communications or physical nodes). This increases risk of poor selection of a candidate architecture due to the absence of insight into true performance for systems that must operate as a piece of critical infrastructure. This research effort proposes a process to analyze critical infrastructure system availability requirements and a candidate set of systems architectures, producing a metric assessing these architectures over a spectrum of degradations to aid in selecting appropriate resilient architectures. To accomplish this effort, a set of simulation and evaluation efforts are undertaken that will process, in an automated way, a set of sample requirements into a set of potential architectures where system functions and capabilities are distributed across nodes. Nodes and links will have specific characteristics and based on sampled requirements, contribute to the overall system functionality, such that as they are impacted/degraded, the impacted functional availability of a system can be determined. A machine learning reinforcement-based agent will structurally impact the nodes, links, and characteristics (e.g., bandwidth, latency) of a given architecture to provide an assessment of system functional uptime/availability under these scenarios. By varying the intensity of the attack and related aspects, we can create a structured method of evaluating the performance of candidate architectures against each other to create a metric rating its resilience to these attack types/strategies. Through multiple simulation iterations, sufficient data will exist to compare this availability metric, and an architectural recommendation against the baseline requirements, in comparison to existing multi-factor computing architectural selection processes. It is intended that this additional data will create an improvement in the matching of resilient critical infrastructure system requirements to the correct architectures and implementations that will support improved operation during times of system degradation due to failures and infrastructure attacks.

Keywords: architecture, resiliency, availability, cyber-attack

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Authors: Anudeep Appe, Bhanu Poluparthi, Lakshmi Kasivajjula, Udai Mv, Sobha Bagadi, Punya Modi, Aditya Singh, Hemanth Gunupudi, Spenser Troiano, Jeff Paul, Justin Stovall, Justin Yamamoto

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The necessity of data-driven decisions in healthcare strategy formulation is rapidly increasing. A reliable framework which helps identify factors impacting a healthcare provider facility or a hospital (from here on termed as facility) market share is of key importance. This pilot study aims at developing a data-driven machine learning-regression framework which aids strategists in formulating key decisions to improve the facility’s market share which in turn impacts in improving the quality of healthcare services. The US (United States) healthcare business is chosen for the study, and the data spanning 60 key facilities in Washington State and about 3 years of historical data is considered. In the current analysis, market share is termed as the ratio of the facility’s encounters to the total encounters among the group of potential competitor facilities. The current study proposes a two-pronged approach of competitor identification and regression approach to evaluate and predict market share, respectively. Leveraged model agnostic technique, SHAP, to quantify the relative importance of features impacting the market share. Typical techniques in literature to quantify the degree of competitiveness among facilities use an empirical method to calculate a competitive factor to interpret the severity of competition. The proposed method identifies a pool of competitors, develops Directed Acyclic Graphs (DAGs) and feature level word vectors, and evaluates the key connected components at the facility level. This technique is robust since its data-driven, which minimizes the bias from empirical techniques. The DAGs factor in partial correlations at various segregations and key demographics of facilities along with a placeholder to factor in various business rules (for ex. quantifying the patient exchanges, provider references, and sister facilities). Identified are the multiple groups of competitors among facilities. Leveraging the competitors' identified developed and fine-tuned Random Forest Regression model to predict the market share. To identify key drivers of market share at an overall level, permutation feature importance of the attributes was calculated. For relative quantification of features at a facility level, incorporated SHAP (SHapley Additive exPlanations), a model agnostic explainer. This helped to identify and rank the attributes at each facility which impacts the market share. This approach proposes an amalgamation of the two popular and efficient modeling practices, viz., machine learning with graphs and tree-based regression techniques to reduce the bias. With these, we helped to drive strategic business decisions.

Keywords: competition, DAGs, facility, healthcare, machine learning, market share, random forest, SHAP

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Authors: Till Gramberg

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In the dynamic world of machine and plant engineering, stagnation in the growth of new product sales compels companies to reconsider their business models. The increasing shift toward service orientation, known as "servitization," along with challenges posed by digitalization and sustainability, necessitates an adaptation of product portfolio management (PPM). Against this backdrop, this study investigates the current challenges and requirements of PPM in this industrial context and develops a framework for the application of generative artificial intelligence (AI) to enhance agility and efficiency in PPM processes. The research approach of this study is based on a mixed-method design. Initially, qualitative interviews with industry experts were conducted to gain a deep understanding of the specific challenges and requirements in PPM. These interviews were analyzed using the Gioia method, painting a detailed picture of the existing issues and needs within the sector. This was complemented by a quantitative online survey. The combination of qualitative and quantitative research enabled a comprehensive understanding of the current challenges in the practical application of machine and plant engineering PPM. Based on these insights, a specific framework for the application of generative AI in PPM was developed. This framework aims to assist companies in implementing faster and more agile processes, systematically integrating dynamic requirements from trends such as digitalization and sustainability into their PPM process. Utilizing generative AI technologies, companies can more quickly identify and respond to trends and market changes, allowing for a more efficient and targeted adaptation of the product portfolio. The study emphasizes the importance of an agile and reactive approach to PPM in a rapidly changing environment. It demonstrates how generative AI can serve as a powerful tool to manage the complexity of a diversified and continually evolving product portfolio. The developed framework offers practical guidelines and strategies for companies to improve their PPM processes by leveraging the latest technological advancements while maintaining ecological and social responsibility. This paper significantly contributes to deepening the understanding of the application of generative AI in PPM and provides a framework for companies to manage their product portfolios more effectively and adapt to changing market conditions. The findings underscore the relevance of continuous adaptation and innovation in PPM strategies and demonstrate the potential of generative AI for proactive and future-oriented business management.

Keywords: servitization, product portfolio management, generative AI, disruptive innovation, machine and plant engineering

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Authors: Alan Ruiz-Padilla, Brando Villalobos-Villalobos, Yeniley Ruiz-Noa, Claudia Mendoza-Macías, Claudia Palafox-Sánchez, Miguel Marín-Rosales, Álvaro Cruz, Rubén Rangel-Salazar

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Introduction: In patients with rheumatoid arthritis, resistance or poor response to disease modifying antirheumatic drugs (DMARD) may be a reflection of the increase in g-P. The expression of g-P may be important in mediating the effluence of DMARD from the cell. In addition, P-glycoprotein is involved in the transport of cytokines, IL-1, IL-2 and IL-4, from normal lymphocytes activated to the surrounding extracellular matrix, thus influencing the activity of RA. The involvement of P-glycoprotein in the transmembrane transport of cytokines can serve as a modulator of the efficacy of DMARD. It was shown that a number of lymphocytes with glycoprotein P activity is increased in patients with RA; therefore, P-glycoprotein expression could be related to the activity of RA and could be a predictor of poor response to therapy. Objective: To evaluate in RA patients, if the G2677T/A MDR1 polymorphisms is associated with differences in the rate of therapeutic response to disease-modifying antirheumatic agents in patients with rheumatoid arthritis. Material and Methods: A prospective cohort study was conducted. Fifty seven patients with RA were included. They had an active disease according to DAS-28 (score >3.2). We excluded patients receiving biological agents. All the patients were followed during 6 months in order to identify the rate of therapeutic response according to the American College of Rheumatology (ACR) criteria. At the baseline peripheral blood samples were taken in order to identify the G2677T/A MDR1 polymorphisms using PCR- Specific allele. The fragment was identified by electrophoresis in polyacrylamide gels stained with ethidium bromide. For statistical analysis, the genotypic and allelic frequencies of MDR1 gene polymorphism between responders and non-responders were determined. Chi-square tests as well as, relative risks with 95% confidence intervals (95%CI) were computed to identify differences in the risk for achieving therapeutic response. Results: RA patients had a mean age of 47.33 ± 12.52 years, 87.7% were women with a mean for DAS-28 score of 6.45 ± 1.12. At the 6 months, the rate of therapeutic response was 68.7 %. The observed genotype frequencies were: for G/G 40%, T/T 32%, A/A 19%, G/T 7% and for A/A genotype 2%. Patients with G allele developed at 6 months of treatment, higher rate for therapeutic response assessed by ACR20 compared to patients with others alleles (p=0.039). Conclusions: Patients with G allele of the - G2677T/A MDR1 polymorphisms had a higher rate of therapeutic response at 6 months with DMARD. These preliminary data support the requirement for a deep evaluation of these and other genotypes as factors that may influence the therapeutic response in RA.

Keywords: pharmacogenetics, MDR1, P-glycoprotein, therapeutic response, rheumatoid arthritis

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Authors: Rao Singh Priyanka, Jayangondaperumal R.

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The Himalayan active fault has the potential to generate great earthquakes in the future, posing a biggest existential threat to humans in the Himalayan and adjacent region. Quantitative evaluation of accumulated and released interseismic strain is crucial to assess the magnitude and spatio-temporal variability of future great earthquakes along the Himalayan arc. To mitigate the destruction and hazards associated with such earthquakes, it is important to understand their recurrence cycle. The eastern Himalayan and Indo-Burman plate boundary systems offers an oblique convergence across two orthogonal plate boundaries, resulting in a zone of distributed deformation both within and away from the plate boundary and clockwise rotation of fault-bounded blocks. This seismically active region has poorly documented historical archive of the past large earthquakes. Thus, paleoseismologicalstudies confirm the surface rupture evidences of the great continental earthquakes (Mw ≥ 8) along the Himalayan Frontal Thrust (HFT), which along with the Geodetic studies, collectively provide the crucial information to understand and assess the seismic potential. These investigations reveal the rupture of 3/4th of the HFT during great events since medieval time but with debatable opinions for the timing of events due to unclear evidences, ignorance of transverse segment boundaries, and lack of detail studies. Recent paleoseismological investigations in the eastern Himalaya and Mishmi ranges confirms the primary surface ruptures of the 1950 C.E. great earthquake (M>8). However, a seismic gap exists between the 1714 C.E. and 1950 C.E. Assam earthquakes that did not slip since 1697 C.E. event. Unlike the latest large blind 2015 Gorkha earthquake (Mw 7.8), the 1950 C.E. event is not triggered by a large event of 1947 C.E. that occurred near the western edge of the great upper Assam event. Moreover, the western segment of the eastern Himalayadid not witness any surface breaking earthquake along the HFT for over the past 300 yr. The frontal fault excavations reveal that during the 1950 earthquake, ~3.1-m-high scarp along the HFT was formed due to the co-seismic slip of 5.5 ± 0.7 m at Pasighat in the Eastern Himalaya and a 10-m-high-scarp at a Kamlang Nagar along the Mishmi Thrust in the Eastern Himalayan Syntaxis is an outcome of a dip-slip displacement of 24.6 ± 4.6 m along a 25 ± 5°E dipping fault. This event has ruptured along the two orthogonal fault systems in the form of oblique thrust fault mechanism. Approx. 130 km west of Pasighat site, the Himebasti village has witnessed two earthquakes, the historical 1697 Sadiya earthquake, and the 1950 event, with a cumulative dip-slip displacement of 15.32 ± 4.69 m. At Niglok site, Arunachal Pradesh, a cumulative slip of ~12.82 m during at least three events since pre 19585 B.P. has produced ~6.2-m high scarp while the youngest scarp of ~2.4-m height has been produced during 1697 C.E. The site preserves two deformational events along the eastern HFT, providing an idea of last serial ruptures at an interval of ~850 yearswhile the successive surface rupturing earthquakes lacks in the Mishmi Range to estimate the recurrence cycle.

Keywords: paleoseismology, surface rupture, recurrence interval, Eastern Himalaya

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Authors: Dial Tassadit Rania, Figueiredo De Oliveira Gabriel

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In this paper, we investigate the relationship between ports and their hinterland and foreland environments and the competitive relationship between the ports themselves. These two environments are changing, evolving and introducing new challenges for commercial and economic development at the regional, national and international levels. Because of the rise of the containerization phenomenon, shipping costs and port handling costs have considerably decreased due to economies of scale. The volume of maritime trade has increased substantially and the markets served by the ports have expanded. On these bases, overlapping hinterlands can give rise to the phenomenon of competition between ports. Our main contribution comparing to the existing literature on this issue, is to build a set of hinterland, foreland and competition indicators. Using these indicators? we investigate the effect of hinterland accessibility, foreland connectivity and inter-ports competition on containerized traffic of Europeans ports. For this, we have a 10-year panel database from 2004 to 2014. Our hinterland indicators are given by two indicators of accessibility; they describe the market potential of a port and are calculated using information on population and wealth (GDP). We then calculate population and wealth for different neighborhoods within a distance from a port ranging from 100 to 1000km. For the foreland, we produce two indicators: port connectivity and number of partners for each port. Finally, we compute the two indicators of inter-port competition and a market concentration indicator (Hirshmann-Herfindhal) for different neighborhood-distances around the port. We then apply a fixed-effect model to test the relationship above. Again, with a fixed effects model, we do a sensitivity analysis for each of these indicators to support the results obtained. The econometric results of the general model given by the regression of the accessibility indicators, the LSCI for port i, and the inter-port competition indicator on the containerized traffic of European ports show a positive and significant effect for accessibility to wealth and not to the population. The results are positive and significant for the two indicators of connectivity and competition as well. One of the main results of this research is that the port development given here by the increase of its containerized traffic is strongly related to the development of its hinterland and foreland environment. In addition, it is the market potential, given by the wealth of the hinterland that has an impact on the containerized traffic of a port. However, accessibility to a large population pool is not important for understanding the dynamics of containerized port traffic. Furthermore, in order to continue to develop, a port must penetrate its hinterland at a deep level exceeding 100 km around the port and seek markets beyond this perimeter. The port authorities could focus their marketing efforts on the immediate hinterland, which can, as the results shows, not be captive and thus engage new approaches of port governance to make it more attractive.

Keywords: accessibility, connectivity, European containerization, European hinterland and foreland, inter-port competition

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Authors: Allaire Eric, Hauet Pascal, Floresco Jean, Beley Sebastien, Sussman Helene, Virag Ronald

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Background: Caverno-venous leakage (CVL) is devastating, although barely known disease, the first cause of major physical impairment in men under 25, and responsible for 50% of resistances to phosphodiesterase 5-inhibitors (PDE5-I), affecting 30 to 40% of users in this medication class. In this condition, too early blood drainage from corpora cavernosa prevents penile rigidity and penetration during sexual intercourse. The role of conservative surgery in this disease remains controversial. Aim: Assess complications and results of combined open surgery and embolization for CVL. Method: Between June 2016 and September 2021, 133 consecutive patients underwent surgery in our institution for CVL, causing severe erectile dysfunction (ED) resistance to oral medical treatment. Procedures combined vein embolization and ligation with microsurgical techniques. We performed a pre-and post-operative clinical (Erection Harness Scale: EHS) hemodynamic evaluation by duplex sonography in all patients. Before surgery, the CVL network was visualized by computed tomography cavernography. Penile EMG was performed in case of diabetes or suspected other neurological conditions. All patients were optimized for hormonal status—data we prospectively recorded. Results: Clinical signs suggesting CVL were ED since age lower than 25, loss of erection when changing position, penile rigidity varying according to the position. Main complications were minor pulmonary embolism in 2 patients, one after airline travel, one with Factor V Leiden heterozygote mutation, one infection and three hematomas requiring reoperation, one decreased gland sensitivity lasting for more than one year. Mean pre-operative pharmacologic EHS was 2.37+/-0.64, mean pharmacologic post-operative EHS was 3.21+/-0.60, p<0.0001 (paired t-test). The mean EHS variation was 0.87+/-0.74. After surgery, 81.5% of patients had a pharmacologic EHS equal to or over 3, allowing for intercourse with penetration. Three patients (2.2%) experienced lower post-operative EHS. The main cause of failure was leakage from the deep dorsal aspect of the corpus cavernosa. In a 14 months follow-up, 83.2% of patients had a clinical EHS equal to or over 3, allowing for sexual intercourse with penetration, one-third of them without any medication. 5 patients had a penile implant after unsuccessful conservative surgery. Conclusion: Open surgery combined with embolization for CVL is an efficient approach to CVL causing severe erectile dysfunction.

Keywords: erectile dysfunction, cavernovenous leakage, surgery, embolization, treatment, result, complications, penile duplex sonography

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Authors: Rideci Farias, Haroldo Paranhos

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The present work deals with the use of drainage geo-composite as a deep drainage and geogrid element to reinforce the base of the body of the landfill destined to the road pavement on geological faults in the stretch of the TO-342 Highway, between the cities of Miracema and Miranorte, in the State of Tocantins / TO, Brazil, which for many years was the main link between TO-010 and BR-153, after the city of Palmas, also in the state of Tocantins / TO, Brazil. For this application, geotechnical and geological studies were carried out by means of SPT percussion drilling, drilling and rotary drilling, to understand the problem, identifying the type of faults, filling material and the definition of the water table. According to the geological and geotechnical studies carried out, the area where the route was defined, passes through a zone of longitudinal fault to the runway, with strong breaking / fracturing, with presence of voids, intense alteration and with advanced argilization of the rock and with the filling up parts of the faults by organic and compressible soils leachate from other horizons. This geology presents as a geotechnical aggravating agent a medium of high hydraulic load and very low resistance to penetration. For more than 20 years, the region presented constant excessive deformations in the upper layers of the pavement, which after routine services of regularization, reconformation, re-compaction of the layers and application of the asphalt coating. The faults were quickly propagated to the surface of the asphalt pavement, generating a longitudinal shear, forming steps (unevenness), close to 40 cm, causing numerous accidents and discomfort to the drivers, since the geometric positioning was in a horizontal curve. Several projects were presented to the region's highway department to solve the problem. Due to the need for partial closure of the runway, the short time for execution, the use of geosynthetics was proposed and the most adequate solution for the problem was taken into account the movement of existing geological faults and the position of the water level in relation to several Layers of pavement and failure. In order to avoid any flow of water in the body of the landfill and in the filling material of the faults, a drainage curtain solution was used, carried out at 4.0 meters depth, with drainage geo-composite and as reinforcement element and inhibitor of the possible A geogrid of 200 kN / m of resistance was inserted at the base of the reconstituted landfill. Recent evaluations, after 13 years of application of the solution, show the efficiency of the technique used, supported by the geotechnical studies carried out in the area.

Keywords: geosynthetics, geocomposite, geogrid, road, recovery, geological failure

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Authors: Stefan Papastefanou

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Artificial intelligence (AI) is an interdisciplinary field of computer science with the aim of creating intelligent machine behavior. Early approaches to AI have been configured to operate in very constrained environments where the behavior of the AI system was previously determined by formal rules. Knowledge was presented as a set of rules that allowed the AI system to determine the results for specific problems; as a structure of if-else rules that could be traversed to find a solution to a particular problem or question. However, such rule-based systems typically have not been able to generalize beyond the knowledge provided. All over the world and especially in IT-heavy industries such as the United States, the European Union, Singapore, and China, machine learning has developed to be an immense asset, and its applications are becoming more and more significant. It has to be examined how such products of machine learning models can and should be protected by IP law and for the purpose of this paper patent law specifically, since it is the IP law regime closest to technical inventions and computing methods in technical applications. Genetic breeding models are currently less popular than recursive neural network method and deep learning, but this approach can be more easily described by referring to the evolution of natural organisms, and with increasing computational power; the genetic breeding method as a subset of the evolutionary algorithms models is expected to be regaining popularity. The research method focuses on patentability (according to the world’s most significant patent law regimes such as China, Singapore, the European Union, and the United States) of AI inventions and machine learning. Questions of the technical nature of the problem to be solved, the inventive step as such, and the question of the state of the art and the associated obviousness of the solution arise in the current patenting processes. Most importantly, and the key focus of this paper is the problem of patenting inventions that themselves are developed through machine learning. The inventor of a patent application must be a natural person or a group of persons according to the current legal situation in most patent law regimes. In order to be considered an 'inventor', a person must actually have developed part of the inventive concept. The mere application of machine learning or an AI algorithm to a particular problem should not be construed as the algorithm that contributes to a part of the inventive concept. However, when machine learning or the AI algorithm has contributed to a part of the inventive concept, there is currently a lack of clarity regarding the ownership of artificially created inventions. Since not only all European patent law regimes but also the Chinese and Singaporean patent law approaches include identical terms, this paper ultimately offers a comparative analysis of the most relevant patent law regimes.

Keywords: algorithms, inventor, genetic breeding models, machine learning, patentability

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Authors: Yasser R. Tawfic, Mohamed A. Eid

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Foundation differential settlement and supported structure tilting is an occasionally occurred engineering problem. This may be caused by overloading, changes in ground soil properties or unsupported nearby excavations. Engineering thinking points directly toward the logic solution for such problem by uplifting the settled side. This can be achieved with deep foundation elements such as micro-piles and macro-piles™, jacked piers and helical piers, jet grouted soil-crete columns, compaction grout columns, cement grouting or with chemical grouting, or traditional pit underpinning with concrete and mortar. Although, some of these techniques offer economic, fast and low noise solutions, many of them are quite the contrary. For tilted structures, with limited inclination, it may be much easier to cause a balancing settlement on the less-settlement side which shall be done carefully in a proper rate. This principal has been applied in Leaning Tower of Pisa stabilization with soil extraction from the ground surface. In this research, the authors attempt to introduce a new solution with a different point of view. So, micro-tunneling technique is presented in here as an intended ground deformation cause. In general, micro-tunneling is expected to induce limited ground deformations. Thus, the researchers propose to apply the technique to form small size ground unsupported holes to produce the target deformations. This shall be done in four phases: •Application of one or more micro-tunnels, regarding the existing differential settlement value, under the raised side of the tilted structure. •For each individual tunnel, the lining shall be pulled out from both sides (from jacking and receiving shafts) in slow rate. •If required, according to calculations and site records, an additional surface load can be applied on the raised foundation side. •Finally, a strengthening soil grouting shall be applied for stabilization after adjustment. A finite element based numerical model is presented to simulate the proposed construction phases for different tunneling positions and tunnels group. For each case, the surface settlements are calculated and induced plasticity points are checked. These results show the impact of the suggested procedure on the tilted structure and its feasibility. Comparing results also show the importance of the position selection and tunnels group gradual effect. Thus, a new engineering solution is presented to one of the structural and geotechnical engineering challenges.

Keywords: differential settlement, micro-tunneling, soil-structure interaction, tilted structures

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Authors: Alper Tolga Kumtepe, Erdem Erdogdu, M. Recep Okur, Eda Kaypak, Ozlem Kaya, Serap Ugur, Deniz Dincer, Hakan Yildirim

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Interaction is one of the most important components of open and distance learning. According to Moore, who proposed one of the keystones on interaction types, there are three basic types of interaction: learner-teacher, learner-content, and learner-learner. From these interaction types, learner-content interaction, without doubt, can be identified as the most fundamental one on which all education is based. Efficacy, efficiency, and attraction of open and distance learning systems can be achieved by the practice of effective learner-content interaction. With the development of new technologies, interactive e-learning materials have been commonly used as a resource in open and distance learning, along with the printed books. The intellectual engagement of the learners with the content that is course materials may also affect their satisfaction for the open and distance learning practices in general. Learner satisfaction holds an important place in open and distance learning since it will eventually contribute to the achievement of learning outcomes. Using the learner-content interaction activities in course materials, Anadolu University, by its Open Education system, tries to involve learners in deep and meaningful learning practices. Especially, during the e-learning material design and production processes, identifying appropriate learner-content interaction activities within the context of learning outcomes holds a big importance. Considering the lack of studies adopting this approach, as well as its being a study on the use of e-learning materials in Open Education system, this research holds a big value in open and distance learning literature. In this respect, the present study aimed to investigate a) which learner-content interaction activities included in interactive courses are the most effective in learners’ achievement of verbal information learning outcomes and b) to what extent distance learners are satisfied with these learner-content interaction activities. For this study, the quasi-experimental research design was adopted. The 120 participants of the study were from Anadolu University Open Education Faculty students living in Eskişehir. The students were divided into 6 groups randomly. While 5 of these groups received different learner-content interaction activities as a part of the experiment, the other group served as the control group. The data were collected mainly through two instruments: pre-test and post-test. In addition to those tests, learners’ perceived learning was assessed with an item at the end of the program. The data collected from pre-test and post-test were analyzed by ANOVA, and in the light of the findings of this approximately 24-month study, suggestions for the further design of e-learning materials within the context of learner-content interaction activities will be provided at the conference. The current study is planned to be an antecedent for the following studies that will examine the effects of activities on other learning domains.

Keywords: interaction, distance education, interactivity, online courses

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Authors: Filomena Lopes, Miguel Magalhaes, Carla Santos Pereira, Natercia Durao, Cristina Costa-Lobo

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The option to implement curricular internships with undergraduate students is a pedagogical option with some good results perceived by academic staff, employers, and among graduates in general and IT (Information Technology) in particular. Knowing that this type of exercise has never been so relevant, as one tries to give meaning to the future in a landscape of rapid and deep changes. We have as an example the potential disruptive impact on the jobs of advances in robotics, artificial intelligence and 3-D printing, which is a focus of fierce debate. It is in this context that more and more students and employers engage in the pursuit of career-promoting responses and business development, making their investment decisions of training and hiring. Three decades of experience and research in computer science degree and in information systems technologies degree at the Portucalense University, Portuguese private university, has provided strong evidence of its advantages. The Human Interaction Skills development as well as the attractiveness of such experiences for students are topics assumed as core in the Ccnception and management of the activities implemented in these study cycles. The objective of this paper is to gather evidence of the Human Interaction Skills explained and valued within the curriculum internship experiences of IT students employability. Data collection was based on the application of questionnaire to intern counselors and to students who have completed internships in these undergraduate courses in the last decade. The trainee supervisor, responsible for monitoring the performance of IT students in the evolution of traineeship activities, evaluates the following Human Interaction Skills: Motivation and interest in the activities developed, interpersonal relationship, cooperation in company activities, assiduity, ease of knowledge apprehension, Compliance with norms, insertion in the work environment, productivity, initiative, ability to take responsibility, creativity in proposing solutions, and self-confidence. The results show that these undergraduate courses promote the development of Human Interaction Skills and that these students, once they finish their degree, are able to initiate remunerated work functions, mainly by invitation of the institutions in which they perform curricular internships. Findings obtained from the present study contribute to widen the analysis of its effectiveness in terms of future research and actions in regard to the transition from Higher Education pathways to the Labour Market.

Keywords: human interaction skills, employability, internships, information technology, higher education

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Authors: Sevdenur Onger, Ali Asram Sagiroglu

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Hyperpigmentation is a cosmetically unappealing skin problem caused by an overabundance of melanin in the skin. Its pathophysiology is caused by melanocytes being exposed to paracrine melanogenic stimuli, which can upregulate melanogenesis-related enzymes (such as tyrosinase) and cause melanosome formation. Tyrosinase is linked to the development of melanosomes biochemically, and it is the main target of hyperpigmentation treatment. therefore, decreasing tyrosinase activity to reduce melanosomes has become the main target of hyperpigmentation treatment. Niacinamide (NA) is a natural chemical found in a variety of plants that is used as a skin-whitening ingredient in cosmetic formulations. NA decreases melanogenesis in the skin by inhibiting melanosome transfer from melanocytes to covering keratinocytes. Furthermore, NA protects the skin from reactive oxygen species and acts as a main barrier with the skin, reducing moisture loss by increasing ceramide and fatty acid synthesis. However, it is very difficult for hydrophilic compounds such as NA to penetrate deep into the skin. Furthermore, because of the nicotinic acid in NA, it is an irritant. As a result, we've concentrated on strategies to increase NA skin permeability while avoiding its irritating impacts. Since nanotechnology can affect drug penetration behavior by controlling the release and increasing the period of permanence on the skin, it can be a useful technique in the development of whitening formulations. Liposomes have become increasingly popular in the cosmetics industry in recent years due to benefits such as their lack of toxicity, high penetration ability in living skin layers, ability to increase skin moisture by forming a thin layer on the skin surface, and suitability for large-scale production. Therefore, liposomes containing NA were developed for this study. Different formulations were prepared by varying the amount of phospholipid and cholesterol and examined in terms of particle sizes, polydispersity index (PDI) and pH values. The pH values of the produced formulations were determined to be suitable with the pH value of the skin. Particle sizes were determined to be smaller than 250 nm and the particles were found to be of homogeneous size in the formulation (pdi<0.30). Despite the important advantages of liposomal systems, they have low viscosity and stability for topical use. For these reasons, in this study, liposomal cream formulations have been prepared for easy topical application of liposomal systems. As a result, liposomal cream formulations containing NA have been successfully prepared and characterized. Following the in-vitro release and ex-vivo diffusion studies to be conducted in the continuation of the study, it is planned to test the formulation that gives the most appropriate result on the volunteers after obtaining the approval of the ethics committee.

Keywords: delivery systems, hyperpigmentation, liposome, niacinamide

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Authors: A. M. Byrne, E. Bonfiglio, C. Rigby, N. Edelstyn

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Introduction: Neuromarketing employs numerous methodologies when investigating products and advertisement effectiveness. Electroencephalography (EEG), a non-invasive measure of electrical activity from the brain, is commonly used in neuromarketing. EEG data can be considered using time-frequency (TF) analysis, where changes in the frequency of brainwaves are calculated to infer participant’s mental states, or event-related potential (ERP) analysis, where changes in amplitude are observed in direct response to a stimulus. This presentation discusses the findings of a systematic review of EEG measures in neuromarketing. A systematic review summarises evidence on a research question, using explicit measures to identify, select, and critically appraise relevant research papers. Thissystematic review identifies which EEG measures are the most robust predictor of customer preference and purchase intention. Methods: Search terms identified174 papers that used EEG in combination with marketing-related stimuli. Publications were excluded if they were written in a language other than English or were not published as journal articles (e.g., book chapters). The review investigated which TF effect (e.g., theta-band power) and ERP component (e.g., N400) most consistently reflected preference and purchase intention. Machine-learning prediction was also investigated, along with the use of EEG combined with physiological measures such as eye-tracking. Results: Frontal alpha asymmetry was the most reliable TF signal, where an increase in activity over the left side of the frontal lobe indexed a positive response to marketing stimuli, while an increase in activity over the right side indexed a negative response. The late positive potential, a positive amplitude increase around 600 ms after stimulus presentation, was the most reliable ERP component, reflecting the conscious emotional evaluation of marketing stimuli. However, each measure showed mixed results when related to preference and purchase behaviour. Predictive accuracy was greatly improved through machine-learning algorithms such as deep neural networks, especially when combined with eye-tracking or facial expression analyses. Discussion: This systematic review provides a novel catalogue of the most effective use of each EEG measure commonly used in neuromarketing. Exciting findings to emerge are the identification of the frontal alpha asymmetry and late positive potential as markers of preferential responses to marketing stimuli. Predictive accuracy using machine-learning algorithms achieved predictive accuracies as high as 97%, and future research should therefore focus on machine-learning prediction when using EEG measures in neuromarketing.

Keywords: EEG, ERP, neuromarketing, machine-learning, systematic review, time-frequency

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Authors: Olga Maksakova

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A work with unconscious patients after acute brain damages besides special knowledge and practical skills of all the participants requires a very specific organization. A lot of said about team approach in neurorehabilitation, usually as for outpatient mode. Rehabilitologists deal with fixed patient problems or deficits (motion, speech, cognitive or emotional disorder). Team-building means superficial paradigm of management psychology. Linear mode of teamwork fits casual relationships there. Cases with deep altered states of consciousness (vegetative states, coma, and confusion) require non-linear mode of teamwork: recovery of consciousness might not be the goal due to phenomenon uncertainty. Rehabilitation team as Semi-open Complex System includes the patient as a part. Patient's response pattern becomes formed not only with brain deficits but questions-stimuli, context, and inquiring person. Teamwork is sourcing of phenomenology knowledge of patient's processes as Third-person approach is replaced with Second- and after First-person approaches. Here is a chance for real-time change. Patient’s contacts with his own body and outward things create a basement for restoration of consciousness. The most important condition is systematic feedbacks to any minimal movement or vegetative signal of the patient. Up to now, recovery work with the most severe contingent is carried out in the mode of passive physical interventions, while an effective rehabilitation team should include specially trained psychologists and psychotherapists. It is they who are able to create a network of feedbacks with the patient and inter-professional ones building up the team. Characteristics of ‘Team-Patient’ system (TPS) are energy, entropy, and complexity. Impairment of consciousness as the absence of linear contact appears together with a loss of essential functions (low energy), vegetative-visceral fits (excessive energy and low order), motor agitation (excessive energy and excessive order), etc. Techniques of teamwork are different in these cases for resulting optimization of the system condition. Directed regulation of the system complexity is one of the recovery tools. Different signs of awareness appear as a result of system self-organization. Joint meetings are an important part of teamwork. Regular or event-related discussions form the language of inter-professional communication, as well as the patient's shared mental model. Analysis of complex communication process in TPS may be useful for creation of the general theory of consciousness.

Keywords: rehabilitation team, urgent rehabilitation, severe brain damage, consciousness disorders, complex system theory

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Authors: Paola Molteni, Luigi d’Alonzo

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Background: Sensory issues are now considered one of the key aspects in defining and diagnosing autism, changing the perspectives on behavioural analysis and intervention in mainstream educational services. However, Italian teachers’ training is yet not specific on the topic of autism and its sensory-related effects and this research investigates the teacher’s capability in understanding the student’s needs and his/her challenging behaviours considering sensory perceptions. Objectives: The research aims to analyse mainstream schools teachers’ awareness on students’ sensory perceptions and how this affects classroom inclusion and learning process. The research questions are: i) Are teachers able to identify student’s sensory issues?; ii) Are trained teachers more able to identify sensory problems then untrained ones?; iii) What is the impact of sensory issues on inclusion in mainstream classrooms?; iv) What should teachers know about autistic sensory dimensions? Methods: This research was designed as a pilot study that involves a multi-methods approach, including action and collaborative research methodology. The designed research allows the researcher to catch the complexity of a province school district (from kindergarten to high school) through a deep detailed analysis of selected aspects. The researcher explored the questions described above through 133 questionnaires and 6 focus groups. The qualitative and quantitative data collected during the research were analysed using the Interpretative Phenomenological Analysis (IPA). Results: Mainstream schools teachers are not able to confidently recognise sensory issues of children included in the classroom. The research underlines: how professionals with no specific training on autism are not able to recognise sensory problems in students on the spectrum; how hearing and sight issues have higher impact on classroom inclusion and student’s learning process; how a lack of understanding is often followed by misinterpretations of the impact of sensory issues and challenging behaviours. Conclusions: As this research has shown, promoting and enhancing the importance of understanding sensory issues related to autism is fundamental to enable mainstream schools teachers to define educational and life-long plans able to properly answer the student’s needs and support his/her real inclusion in the classroom. This study is a good example of how the educational research can meet and help the daily practice in working with people on the autism spectrum and support the training design for mainstream school teachers: the emerging need of designed preparation on sensory issues is fundamental to be considered when planning school district in-service training programmes, specifically declined for inclusive services.

Keywords: autism spectrum condition, scholastic inclusion, sensory overload, teacher's training

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Authors: Mehrnaz Mostafavi

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Recent advances in single-molecule protein identification (ID) and quantification techniques are poised to revolutionize proteomics, enabling researchers to delve into single-cell proteomics and identify low-abundance proteins crucial for biomedical and clinical research. This paper introduces a different approach to single-molecule protein ID and quantification using tri-color amino acid tags and a plasmonic nanopore device. A comprehensive simulator incorporating various physical phenomena was designed to predict and model the device's behavior under diverse experimental conditions, providing insights into its feasibility and limitations. The study employs a whole-proteome single-molecule identification algorithm based on convolutional neural networks, achieving high accuracies (>90%), particularly in challenging conditions (95–97%). To address potential challenges in clinical samples, where post-translational modifications affecting labeling efficiency, the paper evaluates protein identification accuracy under partial labeling conditions. Solid-state nanopores, capable of processing tens of individual proteins per second, are explored as a platform for this method. Unlike techniques relying solely on ion-current measurements, this approach enables parallel readout using high-density nanopore arrays and multi-pixel single-photon sensors. Convolutional neural networks contribute to the method's versatility and robustness, simplifying calibration procedures and potentially allowing protein ID based on partial reads. The study also discusses the efficacy of the approach in real experimental conditions, resolving functionally similar proteins. The theoretical analysis, protein labeler program, finite difference time domain calculation of plasmonic fields, and simulation of nanopore-based optical sensing are detailed in the methods section. The study anticipates further exploration of temporal distributions of protein translocation dwell-times and the impact on convolutional neural network identification accuracy. Overall, the research presents a promising avenue for advancing single-molecule protein identification and quantification with broad applications in proteomics research. The contributions made in methodology, accuracy, robustness, and technological exploration collectively position this work at the forefront of transformative developments in the field.

Keywords: nano proteomics, nanopore-based optical sensing, deep learning, artificial intelligence

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Authors: Hind Alshoubaki

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The world is now confronting a widespread urban phenomenon: refugee camps, which have mostly been established in ‘rushing mode,’ pointing toward affording temporary settlements for refugees that provide them with minimum levels of safety, security and protection from harsh weather conditions within a very short time period. In fact, those emergency settlements are transforming into permanent ones since time is a decisive factor in terms of construction and camps’ age. These play an essential role in transforming their temporary character into a permanent one that generates deep modifications to the city’s territorial structure, shaping a new identity and creating a contentious change in the city’s form and history. To achieve a better understanding for the transformation of refugee camps, this study is based on a mixed-methods approach: the qualitative approach explores different refugee camps and analyzes their transformation process in terms of population density and the changes to the city’s territorial structure and urban features. The quantitative approach employs a statistical regression analysis as a reliable prediction of refugees’ satisfaction within the Zaatari camp in order to predict its future transformation. Obviously, refugees’ perceptions of their current conditions will affect their satisfaction, which plays an essential role in transforming emergency settlements into permanent cities over time. The test basically discusses five main themes: the access and readiness of schools, the dispersion of clinics and shopping centers; the camp infrastructure, the construction materials, and the street networks. The statistical analysis showed that Syrian refugees were not satisfied with their current conditions inside the Zaatari refugee camp and that they had started implementing changes according to their needs, desires, and aspirations because they are conscious about the fact of their prolonged stay in this settlement. Also, the case study analyses showed that neglecting the fact that construction takes time leads settlements being created with below-minimum standards that are deteriorating and creating ‘slums,’ which lead to increased crime rates, suicide, drug use and diseases and deeply affect cities’ urban tissues. For this reason, recognizing the ‘temporary-eternal’ character of those settlements is the fundamental concept to consider refugee camps from the beginning as definite permanent cities. This is the key factor to minimize the trauma of displacement on both refugees and the hosting countries. Since providing emergency settlements within a short time period does not mean using temporary materials, having a provisional character or creating ‘makeshift cities.’

Keywords: refugee, refugee camp, temporary, Zaatari

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Authors: Rhommel Grutas, Ishmael Narag, Harley Lacbawan

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Construction of high-rise buildings is a means to address the increasing population in Metro Manila, Philippines. The existence of the Valley Fault System within the metropolis and other nearby active faults poses threats to a densely populated city. The distant, shallow and large magnitude earthquakes have the potential to generate slow and long-period vibrations that would affect medium-to-high rise buildings. Heavy damage and building collapse are consequences of prolonged shaking of the structure. If the ground and the building have almost the same period, there would be a resonance effect which would cause the prolonged shaking of the building. Microzoning the long-period ground response would aid in the seismic design of medium to high-rise structures. The shear-wave velocity structure of the subsurface is an important parameter in order to evaluate ground response. Borehole drilling is one of the conventional methods of determining shear-wave velocity structure however, it is an expensive approach. As an alternative geophysical exploration, microtremor array measurements can be used to infer the structure of the subsurface. Microtremor array measurement system was used to survey fifty sites around Metro Manila including some municipalities of Rizal and Cavite. Measurements were carried out during the day under good weather conditions. The team was composed of six persons for the deployment and simultaneous recording of the microtremor array sensors. The instruments were laid down on the ground away from sewage systems and leveled using the adjustment legs and bubble level. A total of four sensors were deployed for each site, three at the vertices of an equilateral triangle with one sensor at the centre. The circular arrays were set up with a maximum side length of approximately four kilometers and the shortest side length for the smallest array is approximately at 700 meters. Each recording lasted twenty to sixty minutes. From the recorded data, f-k analysis was applied to obtain phase velocity curves. Inversion technique is applied to construct the shear-wave velocity structure. This project provided a microzonation map of the metropolis and a profile showing the long-period response of the deep sedimentary basin underlying Metro Manila which would be suitable for local administrators in their land use planning and earthquake resistant design of medium to high-rise buildings.

Keywords: earthquake, ground motion, microtremor, seismic microzonation

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Authors: Cazadira Fediva Tamzil, Agung Sulthonaulia Utama

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The rise in popularity of Indonesian Islamic fashion displayed and sold through social networking sites, especially Instagram, might seem at first glance like a commonplace and localized phenomenon. However, when analyzed critically, it actually reveals the relations between the global and local Indonesian economy, as well as a deep socio-anthropological dimension relating to religion, culture, class, work, identity. Conducted using a qualitative methodology, data collection technique of literature review, and observation of various social networking sites, this research finds four things that lead to the aforementioned conclusion. First, the rise of online Islamic fashion retailers was triggered by the shift in the structure of global and national Indonesian economy as well as the free access of information made possible by democratization in Indonesia and worldwide advances in terms of technology. All of those factors combined together gave birth to a large amount of middle-class Indonesians with high consumer culture and entrepreneurial flair. Second, online Islamic fashion retailers are the new cultural trendsetters in society. All these show how Indonesians are becoming increasingly pious, no longer only adhere to Western conception of luxury and that many are increasingly exploiting Islam commercial and status-acquiring purposes. Third, the online Islamic fashion retailers actually reveal a shift in the conception of ‘work’ – social media has made work no longer only confined to the toiling activities inside factories, but instead something that can be done from any location only through posting online words or pictures that can increase a fashion product’s capital value. Without realizing it, many celebrities and online retailers who promote Islamic fashion through social media on a daily basis are now also ‘semi-free immaterial labors’ – a slight reconceptualization to Tiziana Terranova’s concept of ‘free labor’ and Maurizio Lazzarato’s ‘immaterial labor’, which basically refer to people who create economic value and thus help out capitals from producing immaterial things with only little compensation in return. Fourth, this research also shows that the diversity of Islamic fashion styles being sold on Instagram reflects the polarized identity of Islam in Indonesia. In stark contrast with the theory which states that globalization always leads to the strengthening and unification of identity, this research shows how polarized the Islamic identity in Indonesia really is – even in the face of globalization.

Keywords: global economy, Indonesian online Islamic fashion, political relations, socio-anthropology

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Authors: Ajay Kumar Pandey, Mayank Kumar

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White grub (Coleoptera: Scarabaeidae) is a major destructive pest in western Himalayan region of Uttarakhand. Beetles feed on apple, apricot, plum, walnut etc. during night while, second and third instar grubs feed on live roots of cultivated as well as non-cultivated crops. Collection and identification of scarab beetles through light trap was carried out at Crop Research Centre, Govind Ballab Pant University Pantnagar, Udham Singh Nagar (Uttarakhand) during 2018. Field trials were also conducted in 2018 to evaluate pre and post sown application of different insecticides against the white grub infesting soybean. The insecticides like Carbofuran 3 Granule (G) (750 g a.i./ha), Clothianidin 50 Water Dispersal Granule (WG) (120 g a.i./ha), Fipronil 0.3 G (50 g a.i./ha), Thiamethoxam 25 WG (80 g a.i./ha), Imidacloprid 70 WG (300 g a.i./ha), Chlorantraniliprole 0.4% G(100 g a.i./ha) and mixture of Fipronil 40% and Imidacloprid 40% WG (300 g a.i./ha) were applied at the time of sowing in pre sown experiment while same dosage of insecticides were applied in standing soybean crop during (first fortnight of July). Commutative plant mortality data were recorded after 20, 40, 60 days intervals and compared with untreated control. Total 23 species of white grub beetles recorded on the light trap and Holotrichia serrata Fabricious (Coleoptera: Melolonthinae) was found to be predominant species by recording 20.6% relative abundance out of the total light trap catch (i.e. 1316 beetles) followed by Phyllognathus sp. (14.6% relative abundance). H. rosettae and Heteronychus lioderus occupied third and fourth rank with 11.85% and 9.65% relative abundance, respectively. The emergence of beetles of predominant species started from 15th March, 2018. In April, average light trap catch was 382 white grub beetles, however, peak emergence of most of the white grub species was observed from June to July, 2018 i.e. 336 beetles in June followed by 303 beetles in the July. On the basis of the emergence pattern of white grub beetles, it may be concluded that the Peak Emergence Period (PEP) for the beetles of H. serrata was second fortnight of April for the total period of 15 days. In May, June and July relatively low population of H. serrata was observed. A decreasing trend in light trap catch was observed and went on till September during the study. No single beetle of H. serrata was observed on light trap from September onwards. The cumulative plant mortality data in both the experiments revealed that all the insecticidal treatments were significantly superior in protection-wise (6.49-16.82% cumulative plant mortality) over untreated control where highest plant mortality was 17.28 to 39.65% during study. The mixture of Fipronil 40% and Imidacloprid 40% WG applied at the rate of 300 g a.i. per ha proved to be most effective having lowest plant mortality i.e. 9.29 and 10.94% in pre and post sown crop, followed by Clothianidin 50 WG (120 g a.i. per ha) where the plant mortality was 10.57 and 11.93% in pre and post sown treatments, respectively. Both treatments were found significantly at par among each other. Production-wise, all the insecticidal treatments were found statistically superior (15.00-24.66 q per ha grain yields) over untreated control where the grain yield was 8.25 & 9.13 q per ha. Treatment Fipronil 40% + Imidacloprid 40% WG applied at the rate of 300 g a.i. per ha proved to be most effective and significantly superior over Imidacloprid 70WG applied at the rate of 300 g a.i. per ha.

Keywords: bio efficacy, insecticide, soybean, white grub

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Authors: Prabhjot Kaur, B.K. Kang, Balwinder Singh

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The tobacco caterpillar, Spodoptera litura (Fabricius) (Lepidoptera: Noctuidae) is an agricultural important pest species. S. litura has a wide host range of approximately recorded 150 plant species worldwide. In Punjab, this pest attains sporadic status primarily on cauliflower, Brassica oleracea (L.). This pest destroys vegetable crop and particularly prefers the cruciferae family. However, it is also observed feeding on other crops such as arbi, Colocasia esculenta (L.), mung bean, Vigna radiata (L.), sunflower, Helianthus annuus (L.), cotton, Gossypium hirsutum (L.), castor, Ricinus communis (L.), etc. Larvae of this pest completely devour the leaves of infested plant resulting in huge crop losses which ranges from 50 to 70 per cent. Indiscriminate and continuous use of insecticides has contributed in development of insecticide resistance in insects and caused the environmental degradation as well. Moreover, a base line data regarding the toxicity of the newer insecticides would help in understanding the level of resistance developed in this pest and any possible cross-resistance there in, which could be assessed in advance. Therefore, present studies on development of resistance in S. litura against four new chemistry insecticides (emamectin benzoate, chlorantraniliprole, indoxacarb and spinosad) were carried out in the Toxicology laboratory, Department of Entomology, Punjab Agricultural University, Ludhiana, Punjab, India during the year 2011-12. Various stages of S. litura (eggs, larvae) were collected from four different locations (Malerkotla, Hoshiarpur, Amritsar and Samrala) of Punjab. Resistance is developed in third instars of lepidopterous pests. Therefore, larval bioassays were conducted to estimate the response of field populations of thirty third-instar larvae of S. litura under laboratory conditions at 25±2°C and 65±5 per cent relative humidity. Leaf dip bioassay technique with diluted insecticide formulations recommended by Insecticide Resistance Action Committee (IRAC) was performed in the laboratory with seven to ten treatments depending on the insecticide class, respectively. LC50 values were estimated by probit analysis after correction to record control mortality data which was used to calculate the resistance ratios (RR). The LC50 values worked out for emamectin benzoate, chlorantraniliprole, indoxacarb, spinosad are 0.081, 0.088, 0.380, 4.00 parts per million (ppm) against pest populations collected from Malerkotla; 0.051, 0.060, 0.250, 3.00 (ppm) of Amritsar; 0.002, 0.001, 0.0076, 0.10 ppm for Samrala and 0.000014, 0.00001, 0.00056, 0.003 ppm against pest population of Hoshiarpur, respectively. The LC50 values for populations collected from these four locations were in the order Malerkotla>Amritsar>Samrala>Hoshiarpur for the insecticides (emamectin benzoate, chlorantraniliprole, indoxacarb and spinosad) tested. Based on LC50 values obtained, emamectin benzoate (0.000014 ppm) was found to be the most toxic among all the tested populations, followed by chlorantraniliprole (0.00001 ppm), indoxacarb (0.00056 ppm) and spinosad (0.003 ppm), respectively. The pairwise correlation coefficients of LC50 values indicated that there was lack of cross resistance for emamectin benzoate, chlorantraniliprole, spinosad, indoxacarb in populations of S. litura from Punjab. These insecticides may prove to be promising substitutes for the effective control of insecticide resistant populations of S. litura in Punjab state, India.

Keywords: Spodoptera litura, insecticides, toxicity, resistance

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Authors: Camille Rich, Nadine Ferris France, Ann Nolan, Webster Mavhu, Vongai Munatsi

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Background and Aim: Zimbabwe has one of the highest HIV rates in the world, with a 12.7% adult prevalence rate. Young adults are a key group affected by HIV, and one-third of all new infections in Zimbabwe are amongst people ages 18-24 years. Stigma remains one of the main barriers to managing and reducing the HIV crisis, especially for young adults. There are several types of stigma, including enacted stigma, the outward discrimination towards someone and self-stigma, the negative self-judgments one has towards themselves. Self-stigma can have severe consequences, including feelings of worthlessness, shame, suicidal thoughts, and avoidance of medical help. This can have detrimental effects on those living with HIV. However, the unique beliefs and impacts of self-stigma amongst key groups living with HIV have not yet been explored. Therefore, the focus of this study is on the beliefs and experiences of HIV-related self-stigma, as experienced by young adults living in Harare, Zimbabwe. Research Methods: A qualitative approach was taken for this study, using sixteen semi-structured interviews with young adults (18-24 years) who are living with HIV in Harare. Participants were conveniently and purposefully sampled as members of Africa, an organization dedicated to young people living with HIV. Interviews were conducted over Zoom due to the COVID-19 pandemic, recorded and then coded using the software NVivo. The data was analyzed using both inductive and deductive Thematic Analysis to find common themes. Results: All of the participants experienced HIV-related self-stigma, and both beliefs and experiences were explored. These negative self-perceptions included beliefs of worthlessness, hopelessness, and negative body image. The young adults described believing they were not good enough to be around HIV negative people or that they could never be loved due to their HIV status. Developing self-stigmatizing thoughts came from internalizing negative cultural values, stereotypes about people living with HIV, and adverse experiences. Three main themes of self-stigmatizing experiences emerged: disclosure difficulties, relationship complications, and being isolated. Fear of telling someone their status, rejection in a relationship, and being excluded by others due to their HIV status contributed to their self-stigma. These experiences caused feelings of loneliness, sadness, shame, fear, and low self-worth. Conclusions: This study explored the beliefs and experiences of HIV-related self-stigma of these young adults. The emergence of negative self-perceptions demonstrated deep-rooted beliefs of HIV-related self-stigma that adversely impact the participants. The negative self-perceptions and self-stigmatizing experiences caused the participants to feel worthless, hopeless, shameful, and alone-negatively impacting their physical and mental health, personal relationships, and sense of self-identity. These results can now be used to pursue interventions to target the specific beliefs and experiences of young adults living with HIV and reduce the adverse consequences of self-stigma.

Keywords: beliefs, HIV, self-stigma, stigma, Zimbabwe

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Authors: Swadha Singh

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International Solar Alliance is the foremost treaty-based global organization concerned with tapping the potential of sun-abundant nations between the Tropics of Cancer and Capricorn and enables co-operation among them. As a founding member of the International Solar Alliance, India exhibits its positioning as an upcoming leader in clean energy. India has set ambitious goals and targets to expand the share of solar in its energy mix and is playing a proactive role both at the regional and global levels. ISA aims to serve multiple goals- bring about scale commercialization of solar power, boost domestic manufacturing, and leverage solar diplomacy in African countries, amongst others. Against this backdrop, this paper attempts to examine the ways in which ISA as an intergovernmental organization under Indian leadership can leverage the cause of clean energy (solar) diplomacy and effectively shape partnerships and collaborations with other developing countries in terms of sharing solar technology, capacity building, risk mitigation, mobilizing financial investment and providing an aggregate market. A more specific focus of ISA is on the developing countries, which in the absence of a collective, are constrained by technology and capital scarcity, despite being naturally endowed with solar resources. Solar rich but finance-constrained economies face political risk, foreign exchange risk, and off-taker risk. Scholars argue that aligning India’s climate change discourse and growth prospects in its engagements, collaborations, and partnerships at the bilateral, multilateral and regional level can help promote trade, attract investments, and promote resilient energy transition both in India and in partner countries. For developing countries, coming together in an action-oriented way on issues of climate and clean energy is particularly important since it is developing and underdeveloped countries that face multiple and coalescing challenges such as the adverse impact of climate change, uneven and low access to reliable energy, and pressing employment needs. Investing in green recovery is agreed to be an assured way to create resilient value chains, create sustainable livelihoods, and help mitigate climate threats. If India is able to ‘green its growth’ process, it holds the potential to emerge as a climate leader internationally. It can use its experience in the renewable sector to guide other developing countries in balancing multiple similar objectives of development, energy security, and sustainability. The challenges underlying solar expansion in India have lessons to offer other developing countries, giving India an opportunity to assume a leadership role in solar diplomacy and expand its geopolitical influence through inter-governmental organizations such as ISA. It is noted that India has limited capacity to directly provide financial funds and support and is not a leading manufacturer of cheap solar equipment, as does China; however, India can nonetheless leverage its large domestic market to scale up the commercialization of solar power and offer insights and learnings to similarly placed abundant solar countries. The paper examines the potential of and limits placed on India’s solar diplomacy.

Keywords: climate diplomacy, energy security, solar diplomacy, renewable energy

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Authors: Benjamin Blat Belmonte, Stephan Rinderknecht

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The transition to electric vehicles (EVs) stands at the forefront of innovative strategies designed to address environmental concerns and reduce fossil fuel dependency. As the number of EVs on the roads increases, so too does the potential for their integration into energy markets. This research dives deep into the transformative possibilities of using electric vehicle fleets, specifically electric bus fleets, not just as consumers but as active participants in the energy market. This paper investigates the feasibility and grid effects of electric vehicle fleet operators in the energy market. Our objective centers around a comprehensive exploration of the sector coupling domain, with an emphasis on the economic potential in both electricity and balancing markets. Methodologically, our approach combines data mining techniques with thorough pre-processing, pulling from a rich repository of electricity and balancing market data. Our findings are grounded in the actual operational realities of the bus fleet operator in Darmstadt, Germany. We employ a Mixed Integer Linear Programming (MILP) approach, with the bulk of the computations being processed on the High-Performance Computing (HPC) platform ‘Lichtenbergcluster’. Our findings underscore the compelling economic potential of EV fleets in the energy market. With electric buses becoming more prevalent, the considerable size of these fleets, paired with their substantial battery capacity, opens up new horizons for energy market participation. Notably, our research reveals that economic viability is not the sole advantage. Participating actively in the energy market also translates into pronounced positive effects on grid stabilization. Essentially, EV fleet operators can serve a dual purpose: facilitating transport while simultaneously playing an instrumental role in enhancing grid reliability and resilience. This research highlights the symbiotic relationship between the growth of EV fleets and the stabilization of the energy grid. Such systems could lead to both commercial and ecological advantages, reinforcing the value of electric bus fleets in the broader landscape of sustainable energy solutions. In conclusion, the electrification of transport offers more than just a means to reduce local greenhouse gas emissions. By positioning electric vehicle fleet operators as active participants in the energy market, there lies a powerful opportunity to drive forward the energy transition. This study serves as a testament to the synergistic potential of EV fleets in bolstering both economic viability and grid stabilization, signaling a promising trajectory for future sector coupling endeavors.

Keywords: electric vehicle fleet, sector coupling, optimization, electricity market, balancing market

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Authors: Mathieu Bourdeau, Philippe Basset, Julien Waeytens, Elyes Nefzaoui

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As residential buildings account for a third of the overall energy consumption and greenhouse gas emissions in Europe, building energy modeling is an essential tool to reach energy efficiency goals. In the energy modeling process, calibration is a mandatory step to obtain accurate and reliable energy simulations. Nevertheless, the comparison between simulation results and the actual building energy behavior often highlights a significant performance gap. The literature discusses different origins of energy performance gaps, from building design to building operation. Then, building operation description in energy models, especially energy usages and users’ behavior, plays an important role in the reliability of simulations but is also the most accessible target for post-occupancy energy management and optimization. Therefore, the present study aims to discuss results on the calibration ofresidential building energy models using real operation data. Data are collected through a sensor network of more than 180 sensors and advanced energy meters deployed in three collective residential buildings undergoing major retrofit actions. The sensor network is implemented at building scale and in an eight-apartment sample. Data are collected for over one year and half and coverbuilding energy behavior – thermal and electricity, indoor environment, inhabitants’ comfort, occupancy, occupants behavior and energy uses, and local weather. Building energy simulations are performed using a physics-based building energy modeling software (Pleaides software), where the buildings’features are implemented according to the buildingsthermal regulation code compliance study and the retrofit project technical files. Sensitivity analyses are performed to highlight the most energy-driving building features regarding each end-use. These features are then compared with the collected post-occupancy data. Energy-driving features are progressively replaced with field data for a step-by-step calibration of the energy model. Results of this study provide an analysis of energy performance gap on an existing residential case study under deep retrofit actions. It highlights the impact of the different building features on the energy behavior and the performance gap in this context, such as temperature setpoints, indoor occupancy, the building envelopeproperties but also domestic hot water usage or heat gains from electric appliances. The benefits of inputting field data from an extensive instrumentation campaign instead of standardized scenarios are also described. Finally, the exhaustive instrumentation solution provides useful insights on the needs, advantages, and shortcomings of the implemented sensor network for its replicability on a larger scale and for different use cases.

Keywords: calibration, building energy modeling, performance gap, sensor network

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Authors: Gebreselassie Sebhatleab

Abstract:

According to the Global Peace Index report (GPI, 2023), global peacefulness has deteriorated by more than 0.42%. Old and new conflicts, COVID-19, and political and cultural polarization are the main drivers of conflicts in the world. The 2022 was the deadliest year for armed conflict in the history of the GPI. In Ethiopia, over half a million people died in the Tigray war, which was the largest conflict death event since the 1994 Rwandan genocide. In total, 84 countries recorded an improvement, while 79 countries recorded a deterioration in peacefulness across the globe. The Russia-Ukraine war and its consequences were the main drivers of the deterioration in peacefulness globally. Both Russia and Ukraine are now ranked amongst the ten least peaceful countries, and Ukraine had the largest deterioration of any country in the 2023 GPI. In the same year, the global impact of violence on the economy was 17 percent, which was equivalent to 10.9% of global GDP. Besides, the brutal conflict in Tigray started in November. 2020 claimed more than half a million lives lost and displaced nearly 3 million people, along with widespread human rights violations and sexual violence has left deep damage on the population. The displaced people are still unable to return home because the western, southern and Eastern parts of Tigray are occupied by Eritrean and Amhara forces, despite the Pretoria Agreement. Currently, armed conflicts in Amhara in the Oromya regions are intensified, and human rights violations are being reported in both regions. Meanwhile, protests have been held by war-injured TDF members, IDPs and teachers in the Tigray region. Hence, the general objective of this project is to explore the challenges of peace-building processes in the border woredas of the Eastern Zone of the Tigray Region. Methodologically, the project will employ exploratory qualitative research designs to gather and analyze qualitative data. A purposive sampling technique will be applied to gather pertinent information from the key stakeholders. Open-ended interview questions will be prepared to gather relevant information about the challenges and perceptions of peacebuilding in the study area. Data will be analyzed using qualitative methods such as content analysis, narrative analysis and phenomenological analysis to deeply investigate the challenges of peace-building in the study woredas. Findings of this research project will be employed for program intervention to promote sustainable peace in the study area.

Keywords: peace building, conflcit and violence, political instability, insecurity

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Authors: Yogesh Kumar Singh, T. S. Murugesh Prabhu, Upasana Dutta, Girishchandra Yendargaye, Rahul Yadav, Rohini Gopinath Kale, Binay Kumar, Manoj Khare

Abstract:

The Indian subcontinent is severely affected by floods that cause intense irreversible devastation to crops and livelihoods. With increased incidences of floods and their related catastrophes, an Early Warning System for Flood Prediction and an efficient Flood Management System for the river basins of India is a must. Accurately modeled hydrological conditions and a web-based early warning system may significantly reduce economic losses incurred due to floods and enable end users to issue advisories with better lead time. This study describes the design and development of an EWS-FP using advanced computational tools/methods, viz. High-Performance Computing (HPC), Remote Sensing, GIS technologies, and open-source tools for the Mahanadi River Basin of India. The flood prediction is based on a robust 2D hydrodynamic model, which solves shallow water equations using the finite volume method. Considering the complexity of the hydrological modeling and the size of the basins in India, it is always a tug of war between better forecast lead time and optimal resolution at which the simulations are to be run. High-performance computing technology provides a good computational means to overcome this issue for the construction of national-level or basin-level flash flood warning systems having a high resolution at local-level warning analysis with a better lead time. High-performance computers with capacities at the order of teraflops and petaflops prove useful while running simulations on such big areas at optimum resolutions. In this study, a free and open-source, HPC-based 2-D hydrodynamic model, with the capability to simulate rainfall run-off, river routing, and tidal forcing, is used. The model was tested for a part of the Mahanadi River Basin (Mahanadi Delta) with actual and predicted discharge, rainfall, and tide data. The simulation time was reduced from 8 hrs to 3 hrs by increasing CPU nodes from 45 to 135, which shows good scalability and performance enhancement. The simulated flood inundation spread and stage were compared with SAR data and CWC Observed Gauge data, respectively. The system shows good accuracy and better lead time suitable for flood forecasting in near-real-time. To disseminate warning to the end user, a network-enabled solution is developed using open-source software. The system has query-based flood damage assessment modules with outputs in the form of spatial maps and statistical databases. System effectively facilitates the management of post-disaster activities caused due to floods, like displaying spatial maps of the area affected, inundated roads, etc., and maintains a steady flow of information at all levels with different access rights depending upon the criticality of the information. It is designed to facilitate users in managing information related to flooding during critical flood seasons and analyzing the extent of the damage.

Keywords: flood, modeling, HPC, FOSS

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Authors: Mandeep Singh Azad.Dibyendu Chakraborty, Vikas Vohra

Abstract:

Introduction: Poonch is one of the remotest districts of the Jammu and Kashmir (UT) and situated on international borders. This native poultry population in these areas is quite hardy and thrives well in adverse climatic conditions. Till date, no local breed from this area (Jammu Province) has been characterized thus present study was undertaken with the main objectives of molecular characterization of ChB6 gene in local native chicken of Poonch region located at international borders between India and Pakistan. The chicken B-cell marker (ChB6) gene has been proposed as a candidate gene in regulating B-cell development. Material and Method: RNA was isolated by Blood RNA Purification Kit (HiPura) and Trizol method from whole blood samples. Positive PCR products with size 1110 bp were selected for further purification, sequencing and analysis. The amplified PCR product was sequenced by Sangers dideoxy chain termination method. The obtained sequence of ChB6 gene of Poonchi chicken were compared by MEGAX software. BioEdit software was used to construct phylogenic tree, and Neighbor Joining method was used to infer evolutionary history. In order to compute evolutionary distance Maximum Composite Likelihood method was used. Results: The positively amplified samples of ChB6 genes were then subjected to Sanger sequencing with “Primer Walking. The sequences were then analyzed using MEGA X and BioEdit software. The sequence results were compared with other reported sequence from different breed of chicken and with other species obtained from the NCBI (National Center for Biotechnology Information). ClustalW method using MEGA X software was used for multiple sequence alignment. The sequence results of ChB6 gene of Poonchi chicken was compared with Centrocercus urophasianus, G. gallus mRNA for B6.1 protein, G. gallus mRNA for B6.2, G. gallus mRNA for B6.3, Gallus gallus B6.1, Halichoeres bivittatus, Miniopterus fuliginosus Ferringtonia patagonica, Tympanuchus phasianellus. The genetic distances were 0.2720, 0.0000, 0.0245, 0.0212, 0.0147, 1.6461, 2.2394, 2.0070 and 0.2363 for ChB6 gene of Poonchi chicken sequence with other sequences in the present study respectively. Sequencing results showed variations between different species. It was observed that AT content were higher then GC content for ChB6 gene. The lower AT content suggests less thermostable. It was observed that there was no sequence difference within the Poonchi population for ChB6 gene. The high homology within chicken population indicates the conservation of ChB6 gene. The maximum difference was observed with Miniopterus fuliginosus (Eastern bent-wing bat) followed by Ferringtonia patagonica and Halichoeres bivittatus. Conclusion: Genetic variation is the essential component for genetic improvement. The results of immune related gene Chb6 shows between population genetic variability. Therefore, further association studies of this gene with some prevalent diseases in large population would be helpful to identify disease resistant/ susceptible genotypes in the indigenous chicken population.

Keywords: ChB6, sequencing, ClustalW, genetic distance, poonchi chicken, SNP

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