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This study presents an overview of the current situation of highly hazardous pesticides (HHPs) in North Africa and Near East countries (NENA). This work reviews the registered pesticides in the region and identify HHPs being used according to the criteria 1–8 for HHPs of FAO/WHO Guidelines on HHPs. In addition, to identify the weakness and the need of the region to mitigate the risk from the use of HHPs, the report ended with recommendations needed in the region to improve the pesticide managements and registration, such as improving the agricultural practices by adopting the integrated pest management IPM and including replacing HHPs with ecosystem-friendly alternatives if available. The total number of pesticides registered and used in NENA region is 642 active ingredients (IA). Eighty-nine HHPs are still in use in NENA region and 50% of them are evaluated under 1–7 criteria of GHS HHPs. This evaluation shows that 50% of HHPs are insecticides, 22% fungicides, 10% herbicides, 8% nematocides, and 10% rodenticides. The rest of 38 HHPs are identified under criteria 8. This high number of HHPs still in use in some NENA countries urges the need of technical assistance to reduce the use of HHPs. The type of assistant varies from country to other; to identify the priority of technical and legal assistant needed, a country-based assessments must be carried out at the near future.

Comparative chemical hazard assessment, which compares hazards for several endpoints across several chemicals, can be used for a variety of purposes including alternatives assessment and the prioritization of chemicals for further assessment. A new framework was developed to compile and integrate chemical hazard data for several human health and ecotoxicity endpoints from public online sources including hazardous chemical lists, Globally Harmonized System hazard codes (H-codes) or hazard categories from government health agencies, experimental quantitative toxicity values, and predicted values using Quantitative Structure–Activity Relationship (QSAR) models. QSAR model predictions were obtained using EPA’s Toxicity Estimation Software Tool. Java programming was used to download hazard data, convert data from each source into a consistent score record format, and store the data in a database. Scoring criteria based on the EPA’s Design for the Environment Program Alternatives Assessment Criteria for Hazard Evaluation were used to determine ordinal hazard scores (i.e., low, medium, high, or very high) for each score record. Different methodologies were assessed for integrating data from multiple sources into one score for each hazard endpoint for each chemical. The chemical hazard assessment (CHA) Database developed in this study currently contains more than 990,000 score records for more than 85,000 chemicals. The CHA Database and the methods used in its development may contribute to several cheminformatics, public health, and environmental activities.Graphic abstract

Revision in Harmonized System (HS) and its impact of rules of origin (RoO) are matters of immense importance in international trade policy discourse due to its far reaching economic and trade implications. In this article, we analyse the impact of HS amendments on RoO, based on the change in tariff classification (CTC) by examining India’s trade agreements with South Korea and Japan. Findings of the article show that the revision in HS impacts 42% of subheadings with CTC rules in case of India- South Korea Comprehensive Economic Partnership Agreement (CEPA) and 28% in case of India- Japan CEPA, thereby potentially affecting up to 48% and 16% share of their total trade, respectively. Harmonized System, Rules of Origin, Trade Policy, Free Trade Agreements, WCO

Text, voice, images and videos can express some intentions and facts in daily life. By understanding these contents, people can identify and analyze some behaviors. This paper focuses on the commodity trade declaration process and identifies the commodity categories based on text information on customs declarations. Although the technology of text recognition is mature in many application fields, there are few studies on the classification and recognition of customs declaration goods. In this paper, we proposed a classification framework based on machine learning (ML) models for commodity trade declaration that reaches a high rate of accuracy. This paper also proposed a symmetrical decision fusion method for this task based on convolutional neural network (CNN) and transformer. The experimental results show that the fusion model can make up for the shortcomings of the two original models and some improvements have been made. In the two datasets used in this paper, the accuracy can reach 88% and 99%, respectively. To promote the development of study of customs declaration business and Chinese text recognition, we also exposed the proprietary datasets used in this study.

This study aims to provide a new methodology using the Globally Harmonized System (GHS) and the Mahalanobis–Taguchi System (MTS) that can be used to assess the overall hazard of a chemical using GHS information. Previously, hazardous chemicals were designated and managed by the Chemical Management Act, but many more chemicals are now in use. Damage prediction modeling programs predict the extent of damage and proactively manage high-risk chemicals, but the lack of physical and chemical characterization information relating to chemicals has limitations that cannot be modeled. To overcome such limitations, a new method of chemical management prioritization was developed using the GHS and Mahalanobis–Taguchi System (MTS). For effective management, the risk of a chemical can be ranked according to a comprehensive risk assessment and calculated through multivariate analysis using the GHS. Relative hazards are then identified using MTS multivariate analysis with GHS information, even when there is insufficient information about the chemical’s characteristics, and the method can be applied to a large number of different chemicals.

The aim of the article is to study the principles of interaction of classifications and groupings in the process of statistical estimation of products of the sector of information and communication technologies. The main statistical classifications of products that function at the present stage at the international (world), multinational (European), and national levels are considered. The general principles on which the determination of ICT products is based are laid out. Changes in the determination and classifications of statistical information related to products of the ICT sector issued by WPIIS and harmonized with European and national classifications with the passage of time are analyzed. There given an example of statistical determination of ICT products according to the classification under the Harmonized Commodity Description and Coding System (HS) – HS 1996, HS 2002, HS 2007, HS 2012, HS 2017 and harmonization with the Central Product Classification – CPC Rev.2 and the Ukrainian Classification of Goods for Foreign Economic Activity – UCGFEA. The determination of the list of products in the ICT sector is realized as a result of generalization of the work carried out by international organizations (OECD, Eurostat, and UN) as well as unification of concepts and harmonization of methodologies at the international level.

In many low and middle income countries (LMIC), workers’ and consumers’ only access to risk and hazard information in relation to the chemicals they use or work with is on the chemical label and safety data sheet. Recall of chemical hazard information is vital in order for label warnings and precautionary information to promote effective safety behaviors. A literature review, therefore, was conducted on determinants of chemical hazard information recall among workers and consumers globally. Since comprehension and recall are closely linked, the determinants of both were reviewed. Literature was reviewed from both online and print peer reviewed journals for all study designs and countries. This review indicated that the level of education, previous training and the inclusion of pictograms on the hazard communication material are all factors that contribute to the recall of hazard information. The influence of gender and age on recall is incongruent and remains to be explored. More research is required on the demographic predictors of the recall of hazard information, the effect of design and non-design factors on recall, the effect of training on the recall among low literate populations and the examining of different regions or contexts.

A clinical thermometer is a device that tests the temperature of a person’s body. Thermometers are now commonplace not only in hospitals and clinics, but even in offices, institutes, and even several households. Though the invention of digital thermometer and other temperature measuring have been launched, sold in the market, and shrink the local and global demand, still Galileo’s Mercurian is wanted by a specific market. In this article, a detailed analysis is performed about India’s export and import of clinical thermometer for select countries.

Manual assessment of the correctness of Harmonized System codes of goods is very error-prone and time demanding task taking into account the dramatically growing amounts of cross-border trade. The paper provides an automated solution to this problem by applying machine learning methods to assess the correctness of Harmonized System codes. We use machine learning for providing predictions and recommendations of Harmonized System codes on the basis of a model learned from the textual descriptions of the products. In order to assess the correctness Harmonized System codes of goods we introduce a novel combined similarity measure based on cosine similarity of texts and semantic similarity of Harmonized System codes calculated according to their taxonomy. We also present and prove the properties of this new similarity measure. We test our method on the real open source data set of Bill of Lading Summary 2017.

It is important for firms to undertake product innovation since this will enable them to incorporate additional value to its market offer and, consequently, will increase their international competitiveness. Thus, the aim of this article is to develop a new index, the Export Product Innovation Index (EPII), a metric that associates product innovation to export activity according to the value of new export products / goods traded abroad at a single company level. The proposed index is built on official export data and based on the Harmonized System Codes. Therefore, the EPII may be widely generalized and calculated for every export firm all over the world for which export shipping data is available, enabling benchmarks for companies, international comparative studies and policy making. This article uses data on Chilean fruit exporters to illustrate EPII calculation and use. Through the comparison of this new index with some previous ones measuring product innovation overall population of Chilean fruit exporters, it is demonstrated that the EPII provides more accurate information to appraise a firm´s export product innovation performance.