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Ethnobotanical and ethnomedical knowledge of the Malays could be known either through oral sources or documented sources. The traditional sources of Malay medicine are useful for traditional and modern pharmaceuticals development in Malaysia and for conservation of biodiversity. This study aims to extract and categorise the ethnobotanical and ethnomedical contents documented in the medical chapter of Tajul Muluk, in the Malay ancient text. Transliteration and data extraction were carried out in order to identify and classify the information in the text. The manuscript has 292 medical interventions for 56 different diseases such as cough, fever, and mental health issues. There are descriptions available for different medical formulations using 209 plant-based materials, 12 animal-based materials and 40 other types. Many of the name and use of the materials are now rare or not well-known in modern today’s society. Medical descriptions listed in Tajul Muluk will be a documented proof of herbs used by local Malay population utilised as ethnobotanical and ethnomedical resources. Hence retrieving useful ancient documental knowledge should be explored in finding useful cures and alternatives therapeutics for various diseases.

The research carried out in three types of urban plantings of Pennsylvania ash in the northeast of Moscow. The surviving trees damaged by Agrilus planipennis in 2005-2012 studied. Half of the damaged trees show the ability of partial overgrowing of the dry side on around the old larval gallery. The size of the cambium roller around the dry side indicates the viability of the tree. Trees with single longitudinal bark cracks on larval gallery retain viability for more than 10 years. Trees with cracks and dry sides covering up to 1/3 of the trunk circumference live for at least seven years (9.37+2.32). Trees with cracks and dry sides from 1/3 to 2/3 of the trunk circumference and partial bark fall live for at least five years (6.73 + 1.21). Trees with cracks and the absence of more than 2/3 of the bark along the circumference of the trunk of the categories "severely weakened" die within 1-2 years. The first appearance of shoots in the butt part of the trunk of seeming healthy trees is a sign the attack of larval gallery 2 years ago. Keywords: GREEN ASH, EMERALD ASH BORER

Before the emergence of Abrahamic religion, the population in the past experienced both economic calamity and humanitarian crisis as a result of usury practices. Various historical studies reveal that the Babylonian period was an era where human civilization showed dreadful facts as a result of usury praxis. This study focuses on Islamic and Christianity views of usury in economic activities. This paper aims to examine usury starting from semantic discussions to usury practices which are closely related to economic activity from both an Islamic and Christianity perspective. The method used in this paper is a qualitative method with a literature study approach taken from various national and international sources, namely books and journals and citing explanations from the Bible and Qur’an. The results of this research reveal that in Christianity, the study and prohibition of usury practices are mostly discussed in the Old Testament in Deuteronomy, Exodus dan Leviticus, while the New Testament tends to discuss things that need to be done to avoid usury practices. Associated with the economy in general in Christianity refers to the practice of lending money (loans) to those in need without asking for interest or additional returns as a form of profit. Meanwhile, in Islam, the discourse of usury can be found in al-Baqarah, al ‘Imran, al-Nissa‘, al-Rum and the kind of prohibited Usury in is Riba Nasiah, Fadhl and Jahiliyyah which related to purchases and loans.

Differentiations in the habitat and resource utilisation lead to segregation and specialisation of niches for bats within the structurally complex tropical rainforest in Malaysia. This research aims to characterise chiropterans’ assemblages found in two different habitat types in Tasik Kenyir (dipterocarp forest) and Setiu (oil palm plantation). A total of 48 sampling nights were conducted within two years period from March 2017 to March 2019 which covered four sampling sites in Tasik Kenyir and four sites at Setiu. Two standard four-bank harp traps and 10 mist nets were deployed throughout the study at every site to capture bats at understory levels. This makes a total of 576 sampling efforts for both areas. Song Meter SM2bats and Echo Meter Touch from Wildlife Acoustic were used to record the echolocation of insectivorous bats. The total number of individuals and species observed were used to determine species diversity, richness, and evenness. Paleontological statistic software was used to generate the rank abundance and species accumulation curves. Bray-Curtis similarity index was used to generalise the index that represents the relative abundance of the sampling sites. A total of 835 individuals comprising 31 species from six families were captured at both study areas. Out of 835 individuals, 695 were captured within Tasik Kenyir comprising 27 species from six families (H = 2.381) while 140 individuals were captured in Setiu comprising 20 species from five families (H = 2.40). The diversity of bats in Tasik Kenyir was hypothesised to be higher than in Setiu as the habitat possess a larger undisturbed forest. However, the result showed the opposite in which no significant difference was detected from the diversity index calculated between these two areas. Detailed studies need to be conducted to determine if some areas are used as transient habitats for bats.

Wild and underutilized vegetables are important sources of food, nutrition, and income for rural communities and indigenous people. Cultivation of high-yielding hybrid varieties, change in food habits, climate change and over-harvesting have resulted in genetic erosion of these vegetables. In addition to this, their availability, distribution and uses are poorly documented. This study aims to document the wild, neglected, and underutilized vegetable species in Jaimini Municipality of Baglung District, Western Nepal. Complete information on wild and underutilized vegetables were collected using semi-structured interviews, guided field walks, and field observation. We recorded 64 species of wild and underutilized vegetables belonging to 27 different families in the study area. Leaf was the most used plant part (26 species) and majority of the plants species were herbs (33 species). Most of these vegetables were consumed in rainy and summer seasons and their availability decreased during winter season. Knowledge regarding their utilization, cultivation, and conservation were also gradually disappearing. Therefore, consumer awareness, evaluation of their nutritional value, and promotion for their commercial use should be emphasized for the inclusion of these vegetable species in our daily diet.

Urban green spaces (public gardens, parks, urban and peri-urban forests) offer multiple-use opportunities and spaces for recreational activities and played a key role in supporting mental and physical health of dwellers during covid-19 pandemic, being ones of few places where outdoor and social activities where allowed. This study was conducted in Brașov city (also known as Kronstadt, by its German name), the second largest metropolitan area of Romania and surrounded by a significant area of peri-urban forests in Transylvania. Brașov city own just 5.62 sqm of urban green space/inhabitant, one of the lowest in the country, so the presence of a large peri-urban forest area become very valuable for locals and tourists visiting the area. Due to its importance and because understanding visitors' expectations and perceptions is a key element to support decision-makers and ensure proper management of these forests, the Brașov’s forests administrator (Kronstadt Local Public Forest District – RPLPK) decided to investigate how dwellers generally interact with the peri-urban forests and to identify opportunities for improving the capacity of forests in providing social and recreational services. Data were collected through the administration of CAWI (computer assisted web interview) to 314 respondents at beginning of 2021, at exactly one year distance after the pandemic lockdown was imposed all around the country. Analyzing the participants responses, a surprising fact become evident: the use of peri-urban forest is not gender equal, women being less able than men to access these green natural spaces and, therefore, to uptake the benefits provided by the peri-urban forests.

The largest peatland in Malaysia is in Sarawak with approximately 1.66 million ha (13%) of total area, distributed widely in Sibu division followed by Sri Aman, Miri, Kota Samarahan, Sarikei and Bintulu. Despite being the most diverse animal species, the study of insects in peat swamp forest, particularly beetles, is still in the incipient stage. Therefore, this study aimed to provide recent information on the beetle species composition in a peat swamp forest of Real Living Lab, UNIMAS (RLL) located in Kota Samarahan. Beetles were sampled for five consecutive days and nights within a seven-day sampling trip in August 2020. Three sampling methods were employed in this study, namely handpicking method (HPM), modified Pennsylvanian light trap (MPLT) and pitfall trapping (PFT). A total of 15 families representing 37 species and morphospecies with 185 individuals were successfully collected. The most speciose family from the beetle assemblages in RLL is Scarabaeidae with eight species collected (21.62%), followed by Curculionidae with six species (16.22%) and Staphylinidae with five species (13.51%). The most abundant family was also represented by Scarabaeidae with 64 individuals (34.59%), followed by Scolytidae with 27 individuals (14.59%) and Carabidae with 23 individuals (12.43%), respectively. This suggests that these families are good candidates as biodiversity indicator of peat swamp forests. This study is still in its preliminary stage; hence it is important to conduct further beetle samplings in future to better understand the potential of beetle as a bioindicator in the peat swamp habitat as an effort to conserve and protect the habitat and the biodiversity that came along with it.

The fact that arable land is not increasing in proportion to the ever-increasing population will increase the need for food in the coming years. For this reason, it is necessary to increase the yield of crops to make optimum use of arable land. One of the most important reasons for the decrease in yield and quality of crops is weeds. Herbicides are generally preferred for weed management. Due to deficiencies in herbicide application methods, only 0.015-6% of herbicides reach their target. The use of herbicides, which is an important part of the agricultural system, is an issue that needs to be emphasized, considering the risk of residue and environmental damage. In parallel with the rapid development of electronic and computer technologies, artificial intelligence applications have had the opportunity to develop. In this context, the use of artificial intelligence for plant detection in the subsystems of herbicide application machines will contribute to the development of precision agriculture techniques. In this study, the plant detection performances of single-stage and two-stage Convolutional Neural Network (CNN)-based deep learning (DL) models are evaluated. In this context, a dataset was created by taking images of Zea mays, Rhaponticum repens (L.) Hidalgo, and Chenopodium album L. plants in agricultural lands in Konya. With this dataset, the training of the models was carried out by the transfer learning method. The evaluation metrics of the trained models were calculated using the error matrix. In addition, training time and prediction time were used as quantitative metrics in the evaluation of the models. The plant detection performance, training time, and prediction time of the models were 85%, 8 h, 1.21 s for SSD MobileNet v2 and 99%, 22 h, 2.32 s for Faster R-CNN Inception v2, respectively. According to these results, Faster R-CNN Inception v2 is outperform in terms of accuracy. However, in cases where training time and prediction time are important, the SSD MobileNet v2 model can be trained with more data to increase its accuracy.