Recommendations For Usage Research Articles

Parametrial evaluation in cervical cancer by magnetic resonance imaging and clinical examination: Analysis of data from the prospective Leipzig School MMR study.

5525 Parametrial evaluation in cervical cancer by magnetic resonance imaging and clinical examination Background: In cervical cancer patients, assessment of parametrial tumor extension is important for staging and treatment planning. The 2019 cervical cancer guideline published by the Féderation Internationale de Gynécologie et d’Obstétrique (FIGO) for the first time includes recommendations for usage of magnetic resonance imaging (MRI) in this setting. However, valid data regarding the accuracy of this method, especially in patients with advanced disease, are sparce. The objective of this investigation was to compare the accuracy of parametrial assessment in cervical cancer patients using MRI and clinical examination under general anesthesia. Methods: A retrospective cohort study based on data from the prospective monocentric observational Leipzig School Mesometrial Resection study was conducted. Cervical cancer patients staged FIGO IB1 to FIGO IVA who underwent primary surgery between 1999 and 2017 were included. Data from pathological specimen of these patients was compared to the MRI findings and the results from clinical examination under general anesthesia. The gynecological oncologist had access to the MR images during clinical assessment. We calculated sensitivities, specificities, and predictive values for both examination methods. We performed logistic regression modelling to determine factors influencing the accuracy of either method. Results: 400 women were included. Pathologically proven parametrial tumor invasion was present in 165 (41%) patients. Examination under anesthesia augmented by intraoperative display of MR images exhibited a higher accuracy (83%) as compared to MRI alone (76%; McNemar’s odds ratio = 2.0, 95%CI 1.25 – 3.27, p = 0.003). While accuracy was not affected by tumor size in clinical examination, MRI was associated with a significant drop in accuracy in tumors ≥ 2.5 cm (univariable logistic regression, OR for a correct diagnosis compared to smaller tumors 0.22, p < 0.001). This association remained significant in a multivariable model. There was also a significant decrease in specificity when evaluating parametrial invasion by MRI in tumors ≥ 2.5 cm in diameter (p < 0.0001). Body mass index had no influence on performance of either method. Accuracy was significantly higher when test results were concordant (OR 7.5 and 6.0 on univariable and multivariable regression modelling, respectively, p < 0.0001 in both cases). Conclusions: Clinical evaluation of the parametrium by pelvic examination under anesthesia in conjunction with intraoperative presentation of MR images leads to more accurate staging in cervical cancer patients as compared to magnetic resonance imaging alone. Clinical examination should therefore remain an integral part of parametrial assessment in cervical cancer patients.

Managing the duck curve: Energy culture and participation in local energy management programs in the United States

Local energy management programs have the potential to flatten the so-called “duck curve” and enable greater use of renewables by engaging residents to work toward shared sustainability goals. However, there are challenges with managing energy behavior to achieve desired outcomes. This study uses the Energy Cultures framework to examine motivations for participating in a local energy program. It extends the Energy Cultures framework by demonstrating its applicability to the analysis and co-design of local energy management programs, with a particular focus on community-level engagement. The research also identifies the types of information most useful in managing energy behavior. The study site is the Mueller community in Austin, Texas, U.S.A., which has high levels of solar generation and a resulting duck curve that can be addressed by local energy management. A mixed-methods approach was utilized, with qualitative data collection through stakeholder interviews and a community workshop, followed by quantitative data collected in a survey of residents. Results show a strong interest in the proposed energy program, with residents motivated by environmental, societal, and financial benefits. Individual and social norms drove favorable responses while material culture and practices did not. Valuable types of information feedback included energy usage recommendations and renewable energy use at the individual and community level. The findings demonstrate that community engagement, energy feedback, and energy culture are interdependent and that analyzing the energy culture of a community in a co-design process can help prioritize criteria for developing energy programs and tools that strengthen and sustain community engagement.

677 Personal protective equipment needs during the COVID-19 pandemic: A survey of medical dermatologists

Background: The World Health Organization recommends healthcare providers wear personal protective equipment (PPE) to prevent COVID-19 infection. There are no universally accepted recommendations for PPE usage by healthcare providers when caring for asymptomatic patients who can transmit infection. Objective: To survey PPE usage across medical dermatology practices and assess provider concern for COVID-19 transmission in the workplace. Methods: An anonymous survey was distributed via e-mail to dermatologists with membership in the Society for Dermatology Hospitalists and the Association of Professors in Dermatology.

Intrinsically Photosensitive Retinal Ganglion Cells of the Human Retina.

Light profoundly affects our mental and physical health. In particular, light, when not delivered at the appropriate time, may have detrimental effects. In mammals, light is perceived not only by rods and cones but also by a subset of retinal ganglion cells that express the photopigment melanopsin that renders them intrinsically photosensitive (ipRGCs). ipRGCs participate in contrast detection and play critical roles in non-image-forming vision, a set of light responses that include circadian entrainment, pupillary light reflex (PLR), and the modulation of sleep/alertness, and mood. ipRGCs are also found in the human retina, and their response to light has been characterized indirectly through the suppression of nocturnal melatonin and PLR. However, until recently, human ipRGCs had rarely been investigated directly. This gap is progressively being filled as, over the last years, an increasing number of studies provided descriptions of their morphology, responses to light, and gene expression. Here, I review the progress in our knowledge of human ipRGCs, in particular, the different morphological and functional subtypes described so far and how they match the murine subtypes. I also highlight questions that remain to be addressed. Investigating ipRGCs is critical as these few cells play a major role in our well-being. Additionally, as ipRGCs display increased vulnerability or resilience to certain disorders compared to conventional RGCs, a deeper knowledge of their function could help identify therapeutic approaches or develop diagnostic tools. Overall, a better understanding of how light is perceived by the human eye will help deliver precise light usage recommendations and implement light-based therapeutic interventions to improve cognitive performance, mood, and life quality.

E-Mental Health Program Usage Patterns in Randomized Controlled Trials and in the General Public to Inform External Validity Considerations: Sample Groupings Using Cluster Analyses.

BackgroundRandomized controlled trials (RCTs) with vigorous study designs are vital for determining the efficacy of treatments. Despite the high internal validity attributed to RCTs, external validity concerns limit the generalizability of results to the general population. Bias can be introduced, for example, when study participants who self-select into a trial are more motivated to comply with study conditions than are other individuals. These external validity considerations extend to e-mental health (eMH) research, especially when eMH tools are designed for public access and provide minimal or no supervision.ObjectiveClustering techniques were employed to identify engagement profiles of RCT participants and community users of a self-guided eMH program. This exploratory approach inspected actual, not theorized, RCT participant and community user engagement patterns. Both samples had access to the eMH program over the same time period and received identical usage recommendations on the eMH program website. The aim of this study is to help gauge expectations of similarities and differences in usage behaviors of an eMH tool across evaluation and naturalistic contexts.MethodsAustralian adults signed up to myCompass, a self-guided online treatment program created to reduce mild to moderate symptoms of negative emotions. They did so either by being part of an RCT onboarding (160/231, 69.6% female) or by accessing the program freely on the internet (5563/8391, 66.30% female) between October 2011 and October 2012. During registration, RCT participants and community users provided basic demographic information. Usage metrics (number of logins, trackings, and learning activities) were recorded by the system.ResultsSamples at sign-up differed significantly in age (P=.003), with community users being on average 3 years older (mean 41.78, SD 13.64) than RCT participants (mean 38.79, SD 10.73). Furthermore, frequency of program use was higher for RCT participants on all usage metrics compared to community users through the first 49 days after registration (all P values <.001). Two-step cluster analyses revealed 3 user groups in the RCT sample (Nonstarters, 10-Timers, and 30+-Timers) and 2 user groups in the community samples (2-Timers and 20-Timers). Groups seemed comparable in patterns of use but differed in magnitude, with RCT participant usage groups showing more frequent engagement than community usage groups. Only the high-usage group among RCT participants approached myCompass usage recommendations.ConclusionsFindings suggested that external validity concerns of RCT designs may arise with regards to the predicted magnitude of eMH program use rather than overall usage styles. Following up RCT nonstarters may help provide unique insights into why individuals choose not to engage with an eMH program despite generally being willing to participate in an eMH evaluation study. Overestimating frequency of engagement with eMH tools may have theoretical implications and potentially impact economic considerations for plans to disseminate these tools to the general public.

Using drama in the Palestinian EFL classroom: teachers’ attitudes, advantages, problems, and teaching techniques

The use of drama activities is a method that allows learners to improve their communication skills, think critically, learn new vocabulary, and increase their motivation for learning. This study investigates the attitudes of English language teachers, as well as the advantages, problems faced in, and teaching techniques of the English language learning process in Palestinian schools using drama activities. Using both qualitative and quantitative research methods, the researchers investigated the extent to which drama activities are used while teaching English as a second language in Palestinian schools using a questionnaire and interviews. In the questionnaire, the participating English language teachers were 39 females and 12 males. Two teachers were interviewed. The findings confirm the need to implement changes and improvements regarding the use of drama activities in the language classroom. Moreover, the findings suggest following specific drama usage recommendations to ensure satisfactory results for both teachers and students to improve the four language skills. The implication of this study calls for providing clear and sufficient materials for drama classes, as well as offering teachers training programs to enhance their abilities to use drama activities in an effective way.

Blockchain technology for immunisation documentation in India: findings from a simulation pilot

BackgroundImmunisation documentation in India has historically been fragmented over a number of systems. To reduce errors and wasted vaccinations for one of the largest and most complex public vaccination systems, data storage has migrated to electronic application-based data records. However, the system remains fragmented. There has been much interest in the global health sector about the use of blockchain technology to build secure, immutable databases for complex data in fragmented environments. As part of the Indian government's innovation initiatives, our project aims to describe a blockchain immunisation system to store immunisation data, pilot its use in India, and assess strengths, limitations, and feasibility of blockchain immunisation. MethodsA connector database—Anveshan—was developed for the state of Gujarat, India, to: (1) remove data fragmentation; (2) enable aggregate analysis to allow tracking of dynamic data; (3) track data changes; and (4) enable fault tolerance so data can be accurately preserved for long periods of time. Although live piloting was not possible because of the COVID-19 pandemic, a simulated pilot was done. A report including lessons learned, benefits and challenges of blockchain application to immunisation documentation, and recommendations for future usage was delivered. FindingsResults from the simulation showed that the Anveshan database was able to decrease data fragmentation by querying across both supply and delivery databases. Aggregate analysis capability was increased through development of a dashboard user interface that allowed policymakers and immunisation programme staff to receive real-time query feedback. Data changes could be tracked and private data encrypted by incorporating disincentives for inappropriate data modification. Blockchain technology properties increased fault tolerance, which make data less corruptible. Although blockchain technology offers benefits for data storage, it does not facilitate improvements in data collection and quality, which remain a significant challenge in India. Multiple health-care stakeholders would need to work together and have access to live data to ensure nationwide scalability. InterpretationOur findings show the challenges and benefits of a private blockchain system and identify areas requiring continued improvement for immunisation documentation in India. One important consideration in infrastructure design on a nationwide scale is the design of the blockchain system itself. This study is an important first step to show that evidence-based design innovation using blockchain can help countries such as India to address complex public health-care delivery conundrums. FundingIndia Grand Challenges grant (Bill & Melinda Gates Foundation and BIRAC, Government of India).

The development of the solitary bee Osmia bicornis is affected by some insecticide agrochemicals at environmentally relevant concentrations

Solitary bees provide essential pollination services for many arable crops, but are prone to global decline. Agricultural intensification, which is connected with pesticide usage, is among major threats to bees and, thus, to the food security and ecosystem stability. As it may not be possible to cease pesticide usage currently because of the growing demand for food, it is crucial to understand the pesticide toxicities to bees for better protection of pollinator populations. The majority of studies have focused on social bees, and those on solitary bees studied effects of adult exposure, whereas these bees are also likely to be exposed as larvae via the consumption of contaminated pollen. Here, the effects of three commonly used insecticide-based plant protection products on the development of the solitary bee, Osmia bicornis (red mason bee), were studied by exposing larvae to insecticide-contaminated multifloral pollen. The tested insecticides were: Dursban480EC, containing the organophosphate chlorpyrifos (CHP), Sherpa100EC, containing the pyrethroid cypermethrin (CYP), and Mospilan20SP with the neonicotinoid acetamiprid (ACT). When compared to the control larvae fed with uncontaminated-pollen, both CHP and CYP significantly reduced the O. bicornis larval survival and their body mass at all tested concentrations. In contrast, ACT did not affect either larval survival or body mass, but the length of larval stage to cocoon formation was significantly shortened compared to controls. None of studied insecticides affected the mass of cocooned individuals. However, at least 80% of individuals exposed to any of the tested insecticides died before reaching the adult stage, whereas 43% of the controls emerged successfully after overwintering. Although no clear monotonic dose-response relationships were found, our study showed that at least some insecticide formulations affect the development of O. bicornis even at concentrations actually found in pollen in the field, indicating an urgent need for revising current pesticide usage recommendations.

Recommendations for Usage, Commercial Contracts, and Cost Recovery in Government Contracts

Recommendations for Usage, Commercial Contracts, and Cost Recovery in Government Contracts

Review of Static Analyzer Service Models

The static program analysis is gradually adopting advanced use cases, and integration with programming tools becomes more necessary than ever. However, each integration requires a different kind of functionality implemented within an analyzer. For example, continuous integration tools typically analyze projects from scratch, while doing the same for code querying is not efficient performance-wise. The code behind such use cases makes «service models», and it tends to differ significantly between them. In this paper, we analyze the models which might be used by the static analyzer to provide its services based on aspects of security, performance, long-term storage. All models are assigned to one of the groups: logical presence (where the actual computation is performed), resource acquisition, input/output, change accounting and historic data tracking. The usage recommendations, advantages and disadvantages are listed for each reviewed model. Input/output models are tested for actual network throughput. We also describe the model which might aggregate all these use cases. The model is partially evaluated within the work-in-progress static analyzer Equid, and the observations are presented.

THE RESTORATION AND REFUNCTIONING PROPOSAL OF ÖZDOĞANLAR MANSION IN SİVAS

Özdoğanlar residence, in Sivas Province, Merkez District, Akdeğirmen neighbourhood; is one of the few original housing examples in the historical city centre which is important to protect together with the traditional houses in its vicinity. Purpose: To make the restoration decisions of the abandoned building, which has entered a period of rapid degradation due to natural and human-induced effects, and which is in danger of collapse, and to present conservation and usage recommendations. Method: Within the scope of this study, the plan setup, construction system, original elements and problems of the building are defined; its current situation, changes and deteriorations were documented and dated and related restitution proposals were presented; The potential and needs of the house and its immediate surroundings have been evaluated. Findings: It has been determined that the Özdoğanlar residence has lost its original features day by day as a result of intense exposure to atmospheric conditions due to being out of use, the additions and removals made by the former users on time, and the looting by groups prone to Vandalism. Suggestions for the solution of the identified problems of the building were determined in chemical and physical terms. These data were obtained by researching the original plan scheme, space and architectural elements of the building. Result: Özdoğanlar House, which is a qualified traditional house example with its original plan scheme and architectural features, has been documented. A restoration proposal that will preserve the original characteristics of the building was prepared and presented.

Web Profile Recommendations for Safe Surfing and Ethical Usage

People are using the internet for all their day-to-day activities like shopping, banking, mailing, etc. The term censored is a kind of spoofing website which is used to steal important information. Therefore, there is a need for an efficient prevention mechanism to find out the censored web page among the legitimate web pages. This paper proposes a study on identifying censored websites by developing an effective algorithm with domain features of URL. Detecting proxies by URL is done by implementing domain pattern matching. We found that the detector accuracy and speed, reflecting in response efficacy as perceived by users, censored websites as a great source of phishing and malicious activities that users have no knowledge about. Data from government-issued is used to detect censored sites. Security of browsers is the concern with users having low-level security settings.

Unified Univariate-Neural Network Models for Lithium-Ion Battery State-of-Charge Forecasting Using Minimized Akaike Information Criterion Algorithm

Lithium-Ion batteries require step-ahead information to apply contingency plans to prevent them from operating beyond their safe operation thresholds in grid storage and electric vehicle applications. Recently, machine learning techniques have been increasingly applied to forecast one such battery information metric, State-of-Charge % ( SOC ). Conventional standalone machine learning techniques applied in recent works suffer from an accuracy standpoint and thus have been replaced by high-fidelity hybrid machine learning techniques. Existing works on hybrid techniques either perform in-sample predictions, provide limited information of the underlying model, or do not consider varying charging-discharging rate (C-rate) dynamics of the battery. To address this issue, this article presents unified SOC forecasting models using a Minimized Akaike Information Criterion ( ${m}$ -AIC) algorithm. Initially, the ${m}$ -AIC algorithm is used in a standalone manner to precisely tune and search ARIMA (Autoregressive Integrated Moving Average) terms’ order automatically to accurately forecast the battery’s current, voltage, and SOC parameters in a univariate manner at a lower C-rate from given C-rates. The ${m}$ -AIC algorithm based univariate models’ ( m-AIC ) accuracy is further enhanced by first modeling and unifying with Multilayer Perceptron (MLP) and then with Nonlinear Autoregressive Neural Network with external input (NARX) neural networks respectively using the previously forecasted parameters (from m-AIC ). This results in unified-MLP ( u- MLP) and unified-NARX ( u- NARX) models which provide higher accuracy out-of-sample SOC forecasting at the lower C-rate for different optimizer variants. Results show that the proposed u- MLP and u- NARX models reduce the mean squared error to 0.1048% and 0.0175% in comparison to their standalone counterparts which show the lowest corresponding error values of 0.271% and 0.0236% respectively. Furthermore, an additional reference univariate model, Holt-Winters Exponential Smoothing (HWES), is analyzed (by replacing m-AIC ) for a comparative performance evaluation in both standalone and unified manners. Recommendations for usage of the preferred respective models in either manner for SOC forecasting are also presented based on epochs and error values.

Pram to Playground: Why are Five- and Six-Year-Old Students being Suspended?

This article reviews current literature, exploring the possibility that increased access to digital media and mobile screened devices may negatively impact the cognitive, emotional, and physical development of young children. Furthermore, it argues that the overuse of digital technology devices may be responsible for the rise in undesirable behaviors, leading to school suspensions. The review identified a growing body of research that suggests possible links between screen time and Attention Deficit Hyperactivity Disorder (ADHD), addiction to screened devices, lower development of social skills, and poor sleep duration. These are all disorders or conditions that can lead to negative behaviors such as inattention, aggression, depression, and irritation. Therefore, by having a better understanding of the role that digital media and mobile screened devices may have on the expression of behaviors leading to suspensions, it may be possible to make specific usage recommendations to decrease suspension rates in preparatory students.

Deeply uncertain: comparing methods of uncertainty quantification in deep learning algorithms

We present a comparison of methods for uncertainty quantification (UQ) in deep learning algorithms in the context of a simple physical system. Three of the most common uncertainty quantification methods—Bayesian neural networks (BNNs), concrete dropout (CD), and deep ensembles (DEs) — are compared to the standard analytic error propagation. We discuss this comparison in terms endemic to both machine learning (‘epistemic’ and ‘aleatoric’) and the physical sciences (‘statistical’ and ‘systematic’). The comparisons are presented in terms of simulated experimental measurements of a single pendulum—a prototypical physical system for studying measurement and analysis techniques. Our results highlight some pitfalls that may occur when using these UQ methods. For example, when the variation of noise in the training set is small, all methods predicted the same relative uncertainty independently of the inputs. This issue is particularly hard to avoid in BNN. On the other hand, when the test set contains samples far from the training distribution, we found that no methods sufficiently increased the uncertainties associated to their predictions. This problem was particularly clear for CD. In light of these results, we make some recommendations for usage and interpretation of UQ methods.

Evaluating the Sensor-Equipped Autonomous Surface Vehicle C-Worker 4 as a Tool for Identifying Coastal Ocean Acidification and Changes in Carbonate Chemistry

The interface between land and sea is a key environment for biogeochemical carbon cycling, yet these dynamic environments are traditionally under sampled. Logistical limitations have historically precluded a comprehensive understanding of coastal zone processes, including ocean acidification. Using sensors on autonomous platforms is a promising approach to enhance data collection in these environments. Here, we evaluate the use of an autonomous surface vehicle (ASV), the C-Worker 4 (CW4), equipped with pH and pCO2 sensors and with the capacity to mount additional sensors for up to 10 other parameters, for the collection of high-resolution data in shallow coastal environments. We deployed the CW4 on two occasions in Belizean coastal waters for 2.5 and 4 days, demonstrating its capability for high-resolution spatial mapping of surface coastal biogeochemistry. This enabled the characterisation of small-scale variability and the identification of sources of low pH/high pCO2 waters as well as identifying potential controls on coastal pH. We demonstrated the capabilities of the CW4 in both pre-planned “autonomous” mission mode and remote “manually” operated mode. After documenting platform behaviour, we provide recommendations for further usage, such as the ideal mode of operation for better quality pH data, e.g., using constant speed. The CW4 has a high power supply capacity, which permits the deployment of multiple sensors sampling concurrently, a shallow draught, and is highly controllable and manoeuvrable. This makes it a highly suitable tool for observing and characterising the carbonate system alongside identifying potential drivers and controls in shallow coastal regions.

Polyolefin Analyses with a 10 mm Multinuclear NMR Cryoprobe.

Polyolefins are important and broadly used materials. Their molecular microstructures have direct impact on macroscopic properties and dictate end-use applications. 13C NMR is a powerful analytical technique used to characterize polyolefin microstructures, such as long-chain branching (LCB), but it suffers from low sensitivity. Although the 13C sensitivity of polyolefin samples can be increased by about 5.5 times with a cryoprobe, when compared with a conventional broadband observe (BBO) probe, further sensitivity enhancement is in high demand for studying increasingly complex polyolefin microstructures. Toward this goal, distortionless enhancement by polarization transfer (DEPT) and refocused insensitive nuclei enhanced by polarization transfer (RINEPT) are explored. The use of hard, regular, and new short adiabatic 180° 13C pulses in DEPT and RINEPT is investigated. It is found that RINEPTs perform better than DEPTs and a sensitivity enhancement of 3.1 can be achieved with RINEPTs. The results of RINEPTs are further analyzed with statistics software JMP and recommendations for optimal usage of RINEPTs are suggested. An example of analyzing saturated chain ends in an ethylene-octene copolymer sample with a hard 180° 13C RINEPT pulse is demonstrated. It is shown that the experimental time can be further reduced in half because of faster proton relaxation, where the total experimental time is about 580 times shorter when compared to using a conventional method and a 10 mm BBO probe. A naturally abundant nitrogen-containing polyolefin is analyzed using 1H-15N HMBC and, to our knowledge, is the first 1H-15N HMBC presented in the field of polyolefin characterization. The relative amount of similar nitrogen-containing structures is quantified by two-dimensional integration of 1H-15N HMBC. Two pragmatic technical challenges related to using high-sensitivity NMR cryoprobes are also addressed: (1) A new 1H decoupling sequence Bi_Waltz_65_256pl is proposed to address decoupling artifacts in 13C{1H} NMR spectra which contain a strong 13C signal with a high signal-to-noise ratio (S/N). (2) A simple pulse sequence that affords zero-slope spectral baselines and quantitative results is presented to address acoustic ringing that is often associated with high-sensitivity cryoprobe use.

What content to post? Evaluating the effectiveness of Facebook communications in destinations

Abstract This study analyzes the marketing effectiveness of the social media posts of destination management organizations (DMOs) based on message format and content and the moderator effect of its message appeal in order to understand the users’ responses to destinations’ social media posts. The paper also discusses the most appropriate social media message strategy for Facebook campaigns for DMOs. The methodology is based on the content analysis of a sample of 3303 Facebook posts from 12 English and Spanish heritage city destinations. A Poisson regression was used to test the marketing effectiveness of the posts based on the number of Facebook reactions and message characteristics. Considering the particularities of each country, the results provide insights for DMOs for their social media message strategies. The results show that emotional messages tend to be more effective than informational messages in many cases, and several recommendations for Facebook usage are developed for the management of destinations through social media.

Use of Metal Detectors in Archaeological Research

Nowadays, the usage of remote sensing methods is an integral part of archaeological research. Remote scanning devices significantly reduce time for conducting archaeological research and allows a researcher concentrate efforts on searching and studying of archaeological sites more optimally. One of such devices for remote geophysical sounding is a metal detector. The article briefly presents information about the history of geophysical method development, based on the creation and improvement of a ground-based sensing device – the metal detector. Moreover, the author gives examples of its foreign experience in archaeological research as an additional scanning tool, where, in combination with traditional research methods, the metal detector is effective and significantly increases the statistics of metal artifacts found. In addition, the effective capabilities and the feasibility of using a metal detector in various regions of Ukraine, in the process of conducting modern archaeological research (archaeological explorations, stationary archaeological excavations and scientific and rescue studies), are examined based on the author’s personal experience. The algorithm of working with a metal detector at various archaeological sites, both entire complexes and individual objects, is analyzed. The research was carried out exclusively within the framework of professional archaeological ethics: metal detection was carried out purely during the work of archaeological expeditions in the area of the relevant monuments identified by permits. The metal detector was used for the systematic detection of metal artifacts in combination with standard methods of archaeological practice in general. In this article, a metal detector research is primarily considered as a means of obtaining important scientific information, and not as a tool for digging up metal artifacts. To conclude, methodological recommendations for the metal detector usage and issues related to the regulation of its usage in the examination of archaeological sites are presented.

ROLE OF ONLINE COLLABORATIVE PLATFORM IN HIGHER EDUCATION CONTEXT

The education sector has already embraced the new generation of technology and started working towards the enhancement of various teaching and learning strategies. With the involvement of various e-tools, teaching and learning process is reaching its next level of implementation. At present, almost every educational establishment is working on implementing various e-resources on their own Virtual Learning Environment. Some of these are even cloud-based and hence enable the end-users (teachers and students), to access the e-resources and collaborate in-class activities even from remote locations. When it comes to group assessments, various collaborative tools come into the picture. Many educational organizations allow their students to access social media platform such as Facebook etc and conduct collaborative exercises on it. One of the critical aspects of enhancing learning through social networks is the fact that distance or off-campus students are limited from meeting with their teachers and addressing them face-to-face. However, both on-campus and off-campus students do have a Facebook account, thus breaking the distance barrier between students and teachers. By using Facebook chat, students can communicate in real-time with each other or with their lecturers. Other such platforms include Microsoft Kaizala, which is becoming popular during these days since it doesn’t require the participants to share their private accounts or mobile numbers in order to do an online collaboration for academic purpose. This research paper contains a study of various online collaborative tools, their pros and cons, recommendations for usage and implementation. Finally, the authors will reflect on their studies and suggest various ways of implementations for different purpose and nature of assessments, in order to cover the learning outcomes of the session.