Future Objectives Research Articles

Use of Bidirectional Long Short Term Memory in Spoken Word Detection with reference to the Assamese language

Objectives : The proposed method is based on a unique technique of Deep learning for identifying spoken words with reference to Assamese language. Most of the DNN based algorithms have been successfully implemented in the field of image recognition, computer vision, natural language processing and medical picture analysis. Methods: The method used here is the Bidirectional Long Short Term Memory (BLSTM). BLSTM incorporates both past and future situations together. The speech database for this research work is hired from the repository of Indian Language Technology Proliferation and Development Center (ILTP-DC). This repository contains 32,335 utterances by 1000 numbers of male and female participants, which is comprised of 262 unique Assamese native words. The BLSTM based recognition model is using 10 out of the 262 unique words and the remaining words are used in construction or generation of synthesized sentences. The feature extraction module uses 39 feature coefficients, which are composed of MFCC, ΔMFCC and ΔΔMFCC coefficients. Findings: The Word Error Rate (WER) of the BLSTM based recognition model is 18.84% with an average accuracy of 98.12%, which sets one promising benchmark when compared to recent findings. Novelty: In this work an attempt has been made with a different approach to detect certain keywords of Assamese language by adopting deep learning methodology. The future objective of this proposed work is to improve the detection capability of this model by considering multiple DNN models together in a hybrid approach along with the inclusion of additional features. Keywords: Bidirectional Long Short Term Memory; Deep Learning; Speech recognition; WER; MFCC

Learning in and across communities of practice: health professions education students’ learning from boundary crossing

Learning to adapt to new contexts is crucial in health professions education (HPE). Boundaries between and within contexts challenge continuity in students’ learning processes. Little is known about how HPE students can make these “boundary experiences” productive for learning. We investigated how and what nursing students learn from boundary experiences while they are simultaneously growing into a community of practice (CoP). Using a boundary-crossing lens, experiences of discontinuity were identified in pre-placement and post-placement interviews and diary fragments with 14 nursing students during their placement in an academic hospital. We found that students experience discontinuity as a result of different approaches to nursing care and to learning, both between (academic and clinical) settings and within a setting. When students feel safe enough, they can convert boundary experiences into meaningful learning situations, such as critical discussions with staff. Successfully overcoming boundary experiences improves students’ understanding of healthcare and professional development and helps them to develop a personal approach to learning. Students critically address boundary experiences when they are motivated to learn and when they perceive a violation of ethical standards but not when they are concerned that it will affect their assessment. Objects designed to bridge theory and practice can generate additional barriers. This study adds to the HPE literature by demonstrating the learning potential of boundaries and to the broader literature by showing how responses to boundary experiences are intertwined with the process of growing into a CoP. The findings can be used to design future boundary objects.

Messenger RNA Based Vaccines and Their immunological effect on diseases

Because of its capabilities for fast development, potency, secure delivery, and promise for cost effective manufacture, mRNA vaccines are a promising vaccination technique. Many recent research has suggested that mRNA vaccines could be effective intreating a wide range of tumor and viral disorders where standard vaccine techniques have failed to stimulate protective immune responses. The inefficient and unstable in vivo distribution of mRNA has limited their application. Direct electroporation of mRNA vaccines into dendritic cells induced the generation of protective antibodies capable of destroying infected or transformed cells and inducing polyclonal CD8+ and CD4+ that mediated Ag specific T cell responses. in this review mRNA vaccines in detail were examined, as well as future objectives and challenges in the prevention of infectious diseases

A Comprehensive HBIM to XR Framework for Museum Management and User Experience in Ducal Palace at Urbino

Digitization of Cultural and Museum Heritage represents one of the most engaging challenges that would ensure a sustainable and ethical approach for next generations; digital technology’s pervasiveness imposes a comprehensive management of architectural heritage by producing facsimiles of buildings and artworks and by testing robust methodologies, with the final result of providing effective multipurpose models. In this context, the main goal of the present paper is to develop a semantically aware HBIM model that includes an intelligent objects parametrization, leveraging Extended Reality (XR) technologies and digital curation of contents to pursue the preservation of Cultural Heritage (CH) as a whole. This research is implemented in the case study of the Ducal Palace of Urbino that houses the National Gallery of Marche. It was chosen as a remarkable example of a museum located in an architectural complex with a relevant historical background and fine detail of shapes and mouldings. In Italy, as in other European scenarios, museums and their collections need suitable dissemination and management systems that take advantage of the recent digital paradigms. The challenging approach is to exploit existing platforms and software and to adopt a cognitive modelling process, able to develop tools supporting managers and museum curators while enabling user experiences using immersive and interactive features. In order to stress the workflow, this work proposes the use of families with high Level of Detail (LOD) and high Level of Information (LOI). The present article provides, as well, an accurate data enrichment process specifically designed for a gallery’s artworks such as paintings and sculptures, in line with the national and international policies. The study presents a robust and reproducible methodology for digital musealization and management, focusing, as future overall objectives, towards a greater merging between the HBIM approach and XR technologies, also facilitated by training new professional figures with more in-depth digital skills.

Kantian Desires: A Holistic Account

Commentators provide two different accounts of desires in Kant: “feeling-based” accounts stress their connection with feelings, while “action-based” accounts view them as causes of action. I argue that “feeling-based” accounts blur the feeling-desire distinction, while the “action-based” accounts conflict with Kantian desires that do not cause action. On my alternative, Kantian desires are dispositions to action normally directed at producing future objects, and so they differ from the feelings they are connected to, which refer to the way we are affected by objects. This account preserves the feeling-desire distinction, is compatible with desires that do not cause action, and anticipates holistic theories of desire that combine dispositional, hedonic, and evaluative components.

Predictors of early discharge after transcatheter aortic valve implantation: insight from the CoreValve ClinicalService.

The aim of this study was to minimize the procedure, and reduce the length of hospital stay (LoS) is the future objective for transcatheter aortic valve replacement (TAVI).Aims of the study are to identify procedural and electrocardiographical predictors of fast-track discharge in patients who underwent TAVI. Patients treated with TAVI included in the One Hospital ClinicalService project were categorized according to the LoS. 'Fast-Track' population, with a postprocedural LoS less than or equal to 3 days, was compared with the 'Slow-Track' population with a postprocedural LoS greater than 3 days. One thousand five hundred and one patients were collected. Despite single baseline characteristics being almost similar between the two groups, Slow-Track group showed a higher surgical risk (P < 0.001). Patients in the Slow-Track group were more frequently treated with general anaesthesia (P = 0.002) and less frequently predilated (P < 0.001) and received a lower amount of contrast media. No difference between Slow-Track and Fast-Track patients was observed at 30 days in death and in cardiovascular rehospitalization.In the multivariable analysis, STS score of at least 4% [odds ratio (OR): 1.64; P = 0.01], general anaesthesia (OR: 2.80; P = 0.03), predilation (OR: 0.45; P < 001), NYHA 3-4 at baseline (OR: 1.65; P = 0.01), AVB I/LBBB/RBBB onset (OR: 2.41; P < 0.001) and in-hospital new PM (OR: 2.63; P < 0.001) were independently associated with a higher probability of Slow-Track. Fast-Track patients were safely discharged home showing no difference in clinical outcomes after discharge up to 30 days compared with the Slow-Track group. The STS score, general anaesthesia, NYHA 3--4 at baseline, in-hospital onset of conduction disturbances and new PM implantation after TAVI turned out to be predictors of Slow-Track.

Traffic Accident Detection via Self-Supervised Consistency Learning in Driving Scenarios

With the rapid progress of autonomous driving and advanced driver assistance systems, there are growing efforts to promote their safety in natural driving scenarios, especially for the detection of the traffic accidents. However, because of the dynamic camera motion and complex scene in driving situations, traffic accident detection is still challenging. In this work, we aim to give the ability of Traffic Accident Detection for driving systems by proposing a Self-Supervised Consistency learning framework, termed as SSC-TAD, that involves the appearance, motion, and context consistency learning. The key formulation is to find the inconsistency of video frames, object locations and the spatial relation structure of scene temporally between different frames captured by the dashcam videos. Within this field, different from the previous works which concentrate on predicting the future object locations or frames, we further focus on predicting the visual scene context in driving scenarios and detecting the traffic accident by considering the temporal frame consistency, temporal object location consistency, and the spatial-temporal relation consistency of road participants. In this work, this formulation is fulfilled by a collaborative multi-task consistency learning network and the visual scene context feature is represented by a graph convolution network. The superiority to the state-of-the-art is verified by exhaustive evaluations on two large scale datasets, i.e., the AnAn Accident Detection (A3D) dataset and DADA-2000 dataset collected recently.

Does Sustainable Consumption Matter? The Influence of the COVID-19 Pandemic on Medication Use in Brasov, Romania

Sustainable consumption refers to the choice, purchase, use, and disposal of goods so as to enable all people to meet their present and future objective needs. However, panic caused by the gradual onset of the pandemic had a considerable impact on the behavior of consumption and purchase of medication, and the question remains whether sustainable consumption still matters during a crisis or not. The present study aims to analyze whether the pandemic has influenced the behavior of medication use among residents of Brasov County amid panic caused by the virus and to determine the primary sources of information on methods of the prevention and treatment of health conditions. The study focusses on the differences between the two target groups, young people, and adults, considering three socio-demographic factors, such as age, gender, and background. The present research uses two methods of data collection: an interview with 5 doctors and a questionnaire with 543 respondents. This research draws attention to the fact that the behaviors of purchasing and consuming medication during the COVID-19 pandemic has changed due to the spreading of the new virus and the state of emergency, as well as with medication use becoming less sustainable. The results showed that adults were more engaged in the panic buying of medication compared to young people during the pandemic; however, in normal times, young people use more medication. Our study shows that females tend to consume more medicines than males. Moreover, they are more susceptible for seeking media guidance and following advice from the digital realm, because they avoid going to the doctor, especially during the COVID-19 period. Depending on the environment of residence, it was found that people in rural areas generally tend to consume more medication than those in urban areas. However, during the pandemic, the drug use of this category of population has decreased because they do not tend to self-medicate and avoid visiting the doctor because of the fear of becoming contaminated. The results of the research could help to establish measures in order to prevent the panic buying of self-medication and pharmaceuticals, both during pandemics and in normal times, because such behaviors can have negative effects on both health and the environment.

BEHAVIORAL FINANCE AND ANALYSIS OF INVESTORS BEHAVIOR TOWARDS INVESTMENT AVENUES

The purpose of this study is to know the buying behavior of an individual for different investment avenues. Investing is fundamental to accomplish your objectives. It is the best way to improve your future. By making ventures, you are additionally keeping and amassing a corpus for later. Aside from that, making regular investments compels you to save an aggregate routinely, subsequently assisting you with imparting a financial discipline over the long haul. The influence of compounding additionally aids abundance creation. Putting is further useful in gathering future objectives like buying a house, going on an unfamiliar get-away, or arranging your retirement.&#x0D; This study aims to examine the several factors such as age, education, gender, risk, financial literacy etc. On different investment avenues. There are lot of investment choices and an individual strives to invest in a better one. There are large number of people who have ability to invest in share market, real estate, gold, bonds and many more.

EFFECT OF SUCCESSION PLANNING ON EMPLOYEE RETENTION (A CASE STUDY OF CUSTOMER SERVICE INDUSTRY IN KARACHI)

Employee retention is an important factor that affects the performance of the company. The day when an organization started operation to the present day. It remains a question to the organization. How do retain productive employees? Globally, 56.5% of employees are intending to change their job due to several reasons. In Pakistan, 23% employees working in the customer service industry have intention to leave their current organization. Succession planning can be an effective tool for employee retention. It is the process of preparing employees for the attainment of the future objectives of organization by enhancing their abilities and skills. The study has focused on analyzing the impact of succession planning on employee retention specifically for the customer service industry in Pakistan. A survey of 300 respondents was conducted through a close-ended questionnaire to collect primary data and the secondary data were collected from published articles. The data were analyzed through SPSS. The respondents for the survey were selected for an interview through a multistage sample using mix approach based on Probability and non-probability sampling. The Study performed Cross tab Analysis, a Chi-Square test, an independent t-test, ANOVA, and binary logistics to analyze variables. The result of the study showed that succession planning has a positive significant impact of 2.1 times on employee retention which is independent of gender variation. A one-time increase in the effectiveness of a succession plan can increase employee retention by 2.1 times.

Georgia’s and Ukraine’s Cooperation With NATO: Past, Status Quo and Future Perspective

Georgia and Ukraine have the strongest institutional, legal, and practical ties to NATO among post-Soviet states. The progressive strengthening of relations with the North Atlantic Alliance is a means for both nations to attain a future strategic objective in this direction – NATO membership. Georgia and Ukraine are implementing reforms for this purpose, displaying their dedication to democratic society's guiding ideals. Furthermore, governments are making systematic efforts to conform to Alliance military standards. Russia's growing hostility is a major impediment to Georgia and Ukraine joining NATO. The events of the war in August 2008 and the war on Ukrainian territory, which began in 2014, demonstrate that the Kremlin is willing to engage in open military aggression to prevent Georgia and Ukraine from joining NATO. The Kremlin's geopolitical goals have been severely hampered by Russia's large-scale conflict with Ukraine. But, despite significant help from Western governments to the Ukrainian state, including military aid, the question of Ukraine's and Georgia's participation in NATO remains open.

Seizure medication and planned pregnancy: balancing the risks and outcomes

ABSTRACT Introduction The therapeutic management of women with epilepsy (WWE) of childbearing age can be complicated by the need to balance maternal/fetal risks related to seizure occurrence during gestation with the potential teratogenic risks related to the use of anti-seizure medications (ASMs). Areas covered The authors review clinical evidence on seizure-related and ASM-related risks during pregnancy. Current regulatory indications are discussed, evaluating their impact on clinical practice, and ethical implications of pharmacological decisions are debated. Expert opinion If properly informed about the maternal/fetal risks carried by different pharmacological choices, WWE can become the final decision makers regarding their care in every phase of their life. Over the coming years, analysis of aggregated pregnancy registry data on the structural impact, on the fetus, of low doses of valproate and of newer ASMs, together with analysis of the main population study data on functional (cognitive and behavioral) outcomes, could lead to huge advances, making choosing an ASM a less complex process for the clinician and a less painful decision for the woman. Future objectives should include identification of the potential role of the pharmacogenomic profile of WWE in determining the risk of fetal malformations.

Calculating genetic risk for dysfunction in pleiotropic biological processes using whole exome sequencing data

BackgroundNumerous genes are implicated in autism spectrum disorder (ASD). ASD encompasses a wide-range and severity of symptoms and co-occurring conditions; however, the details of how genetic variation contributes to phenotypic differences are unclear. This creates a challenge for translating genetic evidence into clinically useful knowledge. Sleep disturbances are particularly prevalent co-occurring conditions in ASD, and genetics may inform treatment. Identifying convergent mechanisms with evidence for dysfunction that connect ASD and sleep biology could help identify better treatments for sleep disturbances in these individuals.MethodsTo identify mechanisms that influence risk for ASD and co-occurring sleep disturbances, we analyzed whole exome sequence data from individuals in the Simons Simplex Collection (n = 2380). We predicted protein damaging variants (PDVs) in genes currently implicated in either ASD or sleep duration in typically developing children. We predicted a network of ASD-related proteins with direct evidence for interaction with sleep duration-related proteins encoded by genes with PDVs. Overrepresentation analyses of Gene Ontology-defined biological processes were conducted on the resulting gene set. We calculated the likelihood of dysfunction in the top overrepresented biological process. We then tested if scores reflecting genetic dysfunction in the process were associated with parent-reported sleep duration.ResultsThere were 29 genes with PDVs in the ASD dataset where variation was reported in the literature to be associated with both ASD and sleep duration. A network of 108 proteins encoded by ASD and sleep duration candidate genes with PDVs was identified. The mechanism overrepresented in PDV-containing genes that encode proteins in the interaction network with the most evidence for dysfunction was cerebral cortex development (GO:0,021,987). Scores reflecting dysfunction in this process were associated with sleep durations; the largest effects were observed in adolescents (p = 4.65 × 10–3).ConclusionsOur bioinformatic-driven approach detected a biological process enriched for genes encoding a protein–protein interaction network linking ASD gene products with sleep duration gene products where accumulation of potentially damaging variants in individuals with ASD was associated with sleep duration as reported by the parents. Specifically, genetic dysfunction impacting development of the cerebral cortex may affect sleep by disrupting sleep homeostasis which is evidenced to be regulated by this brain region. Future functional assessments and objective measurements of sleep in adolescents with ASD could provide the basis for more informed treatment of sleep problems in these individuals.

The possibility of an impetus heuristic.

Evidence consistent with a belief in impetus is drawn from studies of naïve physics, perception of causality, perception of force, and representational momentum, and the possibility of an impetus heuristic is discussed. An impetus heuristic suggests the motion path of an object that was previously constrained or influenced by an external source (e.g., object, force) appears to exhibit the same constraint or influence even after that constraint or influence is removed. Impetus is not a valid physical principle, but use of an impetus heuristic can in some circumstances provide approximately correct predictions regarding future object motion, and such predictions require less cognitive effort and resources than would predictions based upon objective physical principles. The relationship of an impetus heuristic to naïve impetus theory and to objective physical principles is discussed, and use of an impetus heuristic significantly challenges claims that causality or force can be visually perceived. Alternatives to an impetus heuristic are considered, and potential boundary conditions and falsification of the impetus notion are discussed. Overall, use of an impetus heuristic offers a parsimonious explanation for findings across a wide range of perceptual domains and could potentially be extended to more metaphorical types of motion.

Using a Participatory Approach to Develop Research Priorities for Future Leaders in Cancer-Related Precision Public Health.

Precision public health is an emerging discipline combining principles and frameworks of precision health with the goal of improving population health. The development of research priorities drawing on the strengths of precision and public health is critical to facilitate the growth of the discipline to improve health outcomes. We held an interactive workshop during a virtual conference bringing together early-career researchers across public health disciplines to identify research priorities in precision public health. The workshop participants discussed and voted to identify three priority areas for future research and capacity building including 1) enhancing equity and access to precision public health research and resources, 2) improving tools and metrics for evaluation and 3) applying principles of implementation science to support sustainable practices. Participants also developed future objectives for achieving each priority. Future efforts by working groups will continue the process of identifying, revising, and advancing critical research priorities to grow the impact of precision public health.

QOL-33. Adaptive behaviour of patients treated for malignant brain tumor in the first three years of life

BACKGROUND: Adaptive behavior is defined as the effectiveness and degree to which an individual meets social/cultural standards of personal independence and social responsibility. Patients treated for brain tumor are at risk of alteration of adaptive behaviour that, with a reduced intellectual function, makes diagnosis of mental retard. OBJECTIVE: The aim of this study was to evaluate the adaptive behaviour of patients treated for malignant brain tumor in the first three years of life and the variables that may correlate with its alteration. PATIENTS AND METHODS: Twelve survivors of brain tumor diagnosed in the first three years of life followed in the Pediatric Hematology and Oncology Department of Padua between January 2000 and December 2020 were enrolled in this study. We defined the level of the adaptive behaviour by evaluation adaptive behavior questionnaire (ABAS II) completed by the parents. RESULTS: None of the patients shows a high level of adaptive behavior. Preliminary evidences suggest that, the level of adaptive behavior may be influenced by the sex, irradiation and time from the end of treatment. In details, females show a higher level of performance than males, patients not treated with radiotherapy performed better than patients irradiated and longer-term survivors have a better level of adaptive behaviour. CONCLUSIONS: This study confirms that patients treated for brain tumor show a lower level of adaptive behaviour than peers. The future objective is to assess adaptive behaviour at many times to recognize the problem early.

The Economic Factor and Its Role in the Global Shift in Defence Strategy and Power

"When defence decision-makers tend to look to the future and set objectives for short, medium and long term, they face uncertainties and try to work around multiple scenarios that differ in relation to various fields. One such field is that of economy. And economy has changed as global economic power has shifted. If global economy has shifted so has defence power. The purpose of this paper is to analyse what economic factors influence long-term defence planning and what decision-makers should try to consider when deciding upon different scenarios. Without rushing to conclusions, we can assume that we live in a highly volatile world, where there is a shift in terms of main global actors. With the evolution of technology, with the impact of the Covid-19 pandemic, with geopolitical shifts, like the situation in Afghanistan, all of these factors can be monitored under the umbrella of the economic impact that they have. The effects are there for us to study and to conclude on how the world that we will live in tomorrow shapes up and what decision-makers should focus on when it comes to thinking strategically about developing own countries’ defence power."

Domeniul economic și impactul său în evoluția globală a puterii și strategiei de apărare

"When defence decision-makers tend to look to the future and set objectives for short, medium and long term, they face uncertainties and try to work around multiple scenarios that differ in relation to various fields. One such field is that of economy. And economy has changed as global economic power has shifted. If global economy has shifted so has defence power. The purpose of this paper is to analyse what economic factors influence long-term defence planning and what decision-makers should try to consider when deciding upon different scenarios. Without rushing to conclusions, we can assume that we live in a highly volatile world, where there is a shift in terms of main global actors. With the evolution of technology, with the impact of the Covid-19 pandemic, with geopolitical shifts, like the situation in Afghanistan, all of these factors can be monitored under the umbrella of the economic impact that they have. The effects are there for us to study and to conclude on how the world that we will live in tomorrow shapes up and what decision-makers should focus on when it comes to thinking strategically about developing own countries’ defence power."

Online Distributed Optimization With Nonconvex Objective Functions: Sublinearity of First-Order Optimality Condition-Based Regret

In this article, the problem of online distributed optimization with a set constraint is solved by employing a network of agents. Each agent only has access to a local objective function and set constraint, and can only communicate with its neighbors via a digraph, which is not necessarily balanced. Moreover, agents do not have prior knowledge of their future objective functions. Different from existing works on online distributed optimization, we consider the scenario, where objective functions at each time step are nonconvex. To handle this challenge, we propose an online distributed algorithm based on the consensus algorithm and the mirror descent algorithm. Of particular interest is that regrets involving first-order optimality condition are used to measure the performance of the proposed algorithm. Under mild assumptions on the communication graph and objective functions, we prove that regrets grow sublinearly. Finally, a simulation example is worked out to demonstrate the effectiveness of our theoretical results.

Covering, corner-searching and occupying: A three-stage intelligent algorithm for the 2d multishape part packing problem.

The bin packing problem has a wide range of applications in industry. With the upgrade of the task difficulty, the traditional 2d rectangular layout algorithm can no longer meet the needs of modern industry, such as express packing task and exoplanet ore collection task. The express or ore samples come in heterogeneous shapes so they cannot all be treated as rectangular pieces. In this paper, we propose a three-stage method called covering, corner-searching and occupying (C,S&O) to solve the two-dimensional multishape part packing problem. The objective of the packing problem variant is to ensure maximum use of the raw material and minimize the trim loss. The algorithm cannot make use of information about the sequence of future objects that are going to arrive, only knowing the shape and size of the coming one, and the coming part must be packed into the bin immediately after its arrival without buffering or readjusting. The method of C,S&O hybridizes the idea of “gold corners, silver edges and grass belly” in the Chinese game Go and the method of finding picture corners in machine vision. In the first stage, the rectangular bin and the coming part are transformed into matrix representation, and generating the position matrix that indicates possible ways of packing the part into the bin. In the second stage, the suitable layout position of the coming part is obtained using machine vision image processing technology for reference. The third stage is calculating the environment matching degree to determine the current optimal placement orientation. In order to facilitate the display of the simulation results, only three shapes of parts are considered in the simulation, rectangle, circle and triangle. The experimental results show the effectiveness of this method. Consulting the literature, it is found that this paper is the first to propose a layout method for multishape manufacturing parts.