The dark-red spider mite, Tetranychus ludeni Zacher (Acari: Tetranychidae), is a highly polyphagous species and an important pest of economic plants belonging to the families Cucurbitaceae, Malvaceae, Fabaceae and Solanaceae, and growing in tropical and subtropical regions. In the Western Palaearctic, its distribution reports have recently come mostly from the Mediterranean Basin, i.e. Portugal, Spain, Italy and Israel. In a survey conducted in Serbia 2019-2021 (comprising 159 sampling locations), T. ludeni was found at 89 locations on 27 plant species of the families Rosaceae (8), Solanaceae (6), Cucurbitaceae (4), Fabaceae (2), Amaranthaceae (2), Asteraceae (2), Apiaceae (1), Convolvulaceae (1) and Poaceae (1). The dark-red spider mite was found in mixed populations with other spider mites (mostly Tetranychus urticae and T. turkestani) in around half of the sampling locations. Heavy infestation and visible symptoms of injury were observed in several locations. Three Rosaceae plant species, plum (Prunus domestica), blackthorn (Prunus spinosa) and crab apple (Malus sylvestris) were its new hosts. Serbian records of T. ludeni from locations situated at latitudes between 42?N and 46?N were the northernmost distribution records of this species in the Western Palaearctic.

The COVID-19 pandemic has changed the way people live on the planet. The global economy suffered the biggest blow. The fashion industry has been forced to implement significant changes in their value chains. The subject of the research carried out in this work is to look at the specifics of marketing logistics activities that companies operating in the fashion industry were forced to implement in order to adapt to the business conditions that arose as a result of the COVID-19 pandemic. The aim of the work is to point out the most important specifics of marketing logistics in the fashion industry in the conditions of the COVID-19 pandemic, using the example of the Zara company, which effectively and quickly implemented numerous adjustments, which enabled it to reduce the negative impact of the crisis event.

The history of Afghanistan is abundant in crises, coups, assassinations, political intrigues, as well as invasions and conquests. The last 40 years have been marked by long crises and conflicts: Soviet invasion 1979-1989, the civil war 1989-2001, the American invasion 2001-2021 with disastrous consequences for the country and the people. The invasion carried out in the name of ‘war on terrorism’, ‘bringing democracy’ and ‘freedom’, as a matter of fact, led to instability, turmoil, sectarian wars, deaths of tens of thousands of civilians and the formation of new terrorist organizations in the country, rather than peace and stability. War has become commonplace in Afghanistan. Once seen as the ‘shining star’ of Central Asia, Afghanistan is now known as the country exporting terrorism, drugs and refugees. The paper aims at showing causes and consequences of two decades long American presence in Afghanistan that left lasting imprint on Afghan society.

Agricultural production has benefited a lot from herbicides; however, the use of herbicides caused many environmental problems. Herbicide application can affect the biodiversity of an ecosystem by killing non-target organisms. Microorganisms in the soil are important factors for plant growth; they represent the biological factor of soil fertility. Herbicides can have a beneficial effect on the development of some microorganisms and a negative on others, leading to depletion of microbial diversity in soil. The objective of this work is to determine microbial activity in the soil and to isolate herbicide-resistant bacteria after the use of the "Stomp" herbicide. Agar plate method was used for the determination of microbial prevalence in the soil. The results showed an increase in the total number of bacteria, ammonifiers, fungi, and actinomycetes. Nine isolates, mostly Gram-positive spore-forming rods, showed an ability to grow in the mineral salt medium with different concentrations of "Stomp" herbicide. Isolates G1/1 and G1/2, showed high level of tolerance at the initial pendimethalin concentration of 25 mg/l. Those isolates have the potential to be used to decontaminate herbicide affected ecosystems.

In the last decade, there have been many reports on the negative impact of wildfires on various ecosystems. Unfortunately, wildfires have been intensifying as global temperatures, droughts, and other instances of extreme weather events rise around the world. These circumstances are forcing communities to vigorously address the uncontrolled spread of wildfires, where the ultimate goal is the protection of wildlife. At the same time, many disaster prevention and monitoring methods, based on image processing and computer vision, have been developed. In this paper, we present a new unsupervised method based on RGB color space for the early detection of wildfires from still images. From the analysis of existing state-of-the-art methods, it is evident that different methods explore different color spaces for the extraction of flame features. Our motivation was to use only RGB color space and thus eliminate the time-consuming task of color space conversion. The proposed method consists of several new image processing techniques used to efficiently extract flame features. It outperforms the existing methods, where an increase of 3% and 2% is recorded in the F1 score and Matthews correlation coefficient, respectively. Such performance demonstrates the merits of the proposed method for flame segmentation and detection.

The line graph L(G) of a graph G is defined as a graph having vertex set identical with the set of edges of G and two vertices of L(G) are adjacent if and only if the corresponding edges are incident in G. Higher iteration L i(G) is obtained by repeatedly applying the line graph operation i times. Wiener index W(G) of a graph G is defined as the sum of distances which runs over all pairs of vertices in G. The problem of establishing the extremal values and extremal graphs for the ratio W(L i(G))/W(G) was proposed by Dobrynin and Melnikov [Mathematical Chemistry Monographs, Vol. 12, 2012, pp. 85-121]. In this paper we establish the maximum value and characterize the extremal graphs for i = 1. In doing so, we derive unexpectedly an interesting relation that involves the Gutman index and the first Zagreb index.