Dollars In Losses Research Articles

The legal concept of the rights of consumers of virtual services protection

The article explores the legal aspects of consumer protection in the context of virtual assets (VAs) in Ukraine. The rapid growth of cryptocurrencies and blockchain technologies highlights the need for legislation aligned with the positive experiences of the EU and the UK. Ukrainian legislation, particularly the «Law on Virtual Assets,» is still under development, making it essential to integrate international best practices, such as the EU’s Markets in Crypto-Assets Regulation, which ensures high consumer protection standards. Safeguarding consumer rights should be a cornerstone of the new legislation, as virtual asset users face risks such as fraud, financial pyramids, and gambling addiction. A key regulatory challenge is the need to clearly differentiate between crypto-assets functioning as financial instruments and those with characteristics akin to gambling. The study of international experience in the field of regulation of virtual assets, currently, almost ignores institutions for the protection of consumer rights, at the same time, when the market of virtual assets suffers the most from fraud, theft of assets, activities of illegal casinos, financial pyramids that harm market subjects and lead to multibillion dollar losses. The importance of highlighting the concept of protecting the rights of consumers of virtual assets in Ukraine is also connected with the negative experience in the regulation of three major banking crises that affected the entire population of Ukraine. Leveraging international experience will help protect consumers’ interests and foster the development of a stable and transparent cryptocurrency market in Ukraine. Particular attention in the article is devoted to distinguishing the mechanisms of state regulation of gambling and the study of this issue in the context of the regulation of investment offers to individuals from crypto market subjects. The existing draft laws and the general trend of development of the regulation of virtual assets in Ukraine, without proper strict regulation of consumer rights protection, may lead to financial crises and abuses in the markets, which will lead to negative consequences in the economy.

The Importance of Credit Card Fraud Detection in the Digital Age

It is true that credit card transactions pave part of daily life in today’s digital economy. Also, it is undeniable that this assurance comes at a cost: it has inadvertently opened the floodgate on one of the most daunting challenges to financial safety-credit card fraud. Credit card fraud causes billions of dollars in losses annually, which is brought about by unauthorized transactions carried out using information related to stolen or cloned credit cards. As such, fraud is very difficult to trace and prevent because advanced technologies and strategies are involved.

Matrix matters: How extracellular substances shape biofilm structure and mechanical properties

Biofilms possess unique mechanical properties that are vital to their stability and function. Biofilms are made of extracellular polymeric substances (EPS) secreted by microorganisms and comprise polysaccharides, proteins, extracellular DNA (eDNA), and lipids. EPS is the primary contributor and driver of the biofilm structure and mechanical properties such as stiffness, cohesion, and adhesion. EPS enhances the elasticity and viscosity of biofilms, allowing them to withstand mechanical stresses, shear forces, and deformation. Therefore, biofilms are notoriously difficult to remove and can result in billions of dollars in losses for various industries due to their adverse effects, such as contamination, pressure loss, and corrosion. As a result, it is essential to comprehend the mechanical properties of biofilms to control or remove them in various scenarios. We undertook a fundamental study to determine the relationship between individual EPS components and biofilm mechanical properties. In this study, a CDC biofilm reactor was used to grow pure culture biofilms (Staphylococcus epidermidis) which were treated with six EPS modifier agents (Ca2+, Mg2+, periodic acid, protease K, lipase, and DNAase I) to modify or cleave specific EPS components. The mechanical properties (Young's Modulus) of treated biofilms were subsequently tested using atomic force microscopy (AFM), the biofilm EPS functional groups were measured via the Fourier transform infrared (FTIR) spectroscopy, and biofilm structural characteristics using confocal imaging. The FTIR results showed that EPS modifier agents successfully reduced their target EPS components. Similarly, the confocal microscopic analysis results showed that most of these modifier agents (except lipase) significantly reduced (P-value <0.05) the biovolume and thickness of treated biofilms. Conversely, most of these modifier agents (except protease K) significantly increased (P-value <0.05) the roughness coefficient of the biofilms. Finally, data from AFM showed that biofilm mechanical properties (Young’s modulus) significantly (P-value <0.05) changed with their EPS composition. These results have significant ramifications for biofilm management and control in myriad scenarios.

Planning and Preparation of Cybersecurity

In today's digital environment characterized by fast-evolving adversaries, expanded attack surfaces, and complex IT environments, having a formidable plan and being prepared could create a world of difference when faced with a potential cyber-attack. Cyber threats are growing risks to everyone and any institution. Cybercriminals target individuals and companies of all sizes. Today's attacks are agile and sophisticated. Ransom demands are elevating and advancing rapidly while attackers drill down their focus to specific victims like critical infrastructure businesses, which can spend millions of dollars in losses from cyber disasters since such companies have less tolerance for downtime. The evolution of artificial intelligence technology, which is more interesting and scarier at the same time, is impacting the field of cybersecurity. The negative side of AI is that it has enabled threat actors to blend new data theft-based extortion techniques into ransomware. Attackers can steal companies' sensitive data or even encrypt the data and demand ransom for the decryption key failure, to which they threaten the company to expose the data to the public or even trade in the dark web. The intelligent techniques and tactics utilized by threat actors are a clarion call for organizations to proactively plan and prepare adequately by developing a cybersecurity strategy as a countermeasure. A cybersecurity strategy is a comprehensive plan that stipulates an organizational approach to secure its IT infrastructure against cyber threats. The common cybersecurity strategy various organizations use to plan and prepare for inevitable attacks is the incidence response plan. Incidence response is the processes and technologies organizations use to detect and respond to cyber threats, security breaches, or cyberattacks within an organization. Developing and implementing a formal incident response plan allows organizations to minimize and prevent damage. This research paper focuses on the primary goal of the incident response of preventing cyberattacks prior to occurring and reducing the cost and business disruption emanating from cyberattacks that happen. Keywords – incident response, threats, Artificial intelligence, cybersecurity, threat attacks, plan, preparation.

Malpractice rates are lower for women physicians compared to men physicians

Background Previous literature has shown that women physicians are less likely to be involved in medical malpractice litigation than male physicians. Methods This study sought to examine the differences in malpractice experience by provider gender by using closed medical malpractice claims from 2011 through 2020. Results We found that after adjusting for the number of claims and dollar losses per full time equivalents worked, female physicians experienced fewer and less costly claims than male physicians ( p &lt; .001). Specific specialties had a significant relationship between claim frequency and provider gender, which included general surgery ( p = .01), obstetrics ( p = .001), gynecology ( p = .04), internal medicine and family general practice ( p &lt; .001). Conclusion The results from this analysis support the prior findings that male physicians experience a higher rate of malpractice claims. Therefore, there is an opportunity to learn how women providers achieve lower malpractice risk to inform clinical practice recommendations.

Leak detection and localization in underground water supply system using thermal imaging and geophone signals through machine learning

The underground water pipeline system is a crucial infrastructure that largely remains out of sight. However, it is the source of a clean and uninterrupted flow of water for our everyday lives. Various factors, including corrosion, material degradation, ground movement, and improper maintenance, cause pipe leaks, a silent crisis that causes an estimated 39 billion dollars of loss every year. Prompt leakage detection and localization can help reduce the loss. This research investigates the potential of two machine learning models as supporting tools for surveying extensive areas to identify and pinpoint the location of underground leaks. The presented combined approach ensures the speed and accuracy of the leakage survey. The first machine learning model is a hybrid ML model that employs thermal imaging to identify subterranean water leakage. It relies on detecting thermal anomalies and distinctive signatures associated with water leakage to identify and locate underground water leakage. The developed model can detect up to 750 mm underground leakage with 95.20 % accuracy. The second model uses binaural audio from geophones to localize the leakage position. The model utilizes interaural time difference and interaural phase difference for localization purposes, and the 1D-CNN network delivers an angle in twenty-degree increments with an accuracy of 88.19 %. Large-scale implementation of the proposed model could be a powerful catalyst to reduce water loss in the water supply system.

Pharmaceutical serialization dynamics to restrain illicit trade and counterfeiting of drugs

Every individual has a fundamental entitlement to healthcare access. It falls upon governments to guarantee the delivery of high-quality healthcare services and infrastructure to their populace.. Over the past few decades, both governments and healthcare industries have been grappling with the challenge of minimizing the adverse effects on public health caused by counterfeit medicines. The World Health Organization has estimated that 40 % medicines in developing and impoverished countries are either counterfeit or potentially adulterated. The global economy suffers billions of dollars in losses due to counterfeit drugs, which also divert funds away from research and development (R&amp;D) initiatives. In the United States, the Food and Drug Administration (FDA) has devised a 10-year roadmap to implement drug traceability measures. The Healthcare Distribution Alliance (HDA) has been tasked with mandating the printing of multiple barcodes and human-readable data on product packaging. Additionally, the FDA is actively involved in pilot projects with leading pharmaceutical manufacturers and wholesalers to leverage blockchain technology within interoperable digital networks for secure data transfer and traceability among authorized trading partners. Preventing counterfeit medicines from infiltrating the supply chain remains a significant challenge for governments and regulatory authorities. Consequently, there is a growing emphasis on implementing stringent guidelines to deter criminals and counterfeiters from distributing fake medicines in the market. The healthcare industry requires robust regulations and secure technologies to ensure the delivery of safe and authentic drugs to patients.

Penguatan Pengetahuan Kesiapsiagaan Terhadap Bahaya Bencana Gempa Bumi dan Tsunami bagi Siswa SMAN I Lhoknga, Kabupaten Aceh Besar

Earthquakes and tsunamis are natural disasters that can occur anywhere and anytime. Knowledge about the dangers of natural disasters needs to be imparted to the community so that they can understand the types and levels of danger that may arise. This is necessary to enhance the community's capacity to deal with disasters. Reflecting on the occurrence of the 2004 Aceh Earthquake and Tsunami, which claimed hundreds of thousands of lives and caused hundreds of millions of US dollars in losses, increasing knowledge and understanding of disaster hazards needs to be continuously pursued. The repetition of these activities aligns the history of disaster events passed down through generations with the advancements in scientific knowledge and technological progress. Increasing knowledge of earthquake and tsunami hazards can be achieved, in part, through socialization efforts. One appropriate segment of society to receive reinforcement of knowledge through socialization activities is high school students, particularly the students of SMAN 1 Lhoknga, Aceh Besar Regency. Students are the younger generation whose roles can be agents of change within the wider community. Therefore, their role in the realm of disaster management needs to be supported by a good and competent capacity enhancement. Thus, students of SMAN 1 Lhoknga can understand the factors causing and the impacts arising from earthquake and tsunami disasters and actively participate in such events.

The keys to success of bull breeding soundness exams

Bull breeding soundness exams are one of the most important tasks that we perform as bovine veterinarians. This exam is de­signed to identify subfertile and infertile bulls which if used in a breeding scenario can result in loss of dollars for the produc­er. This loss of income comes from reduction in calves hitting the ground, a longer calving season, and in total less pounds of calf at the time of weaning.

240 Impact of structural traits on semen collection training and lesion characteristics in Duroc boars

Abstract Rising incidence of lameness in boar stud contributes to increased morbidity and mortality, affecting longevity and likely semen output. Lameness is not unique to the boar and affects the swine industry as a whole, contributing to millions of dollars in losses every year. Hypothesized contributors to lameness incidence are body, feet, and leg structure. In the boar stud lameness affects the ability of the boar to mount the dummy and can cause pain-related stress which can impact reproductive function. Lameness is also often accompanied by skin lesions or wounds which can lead to infection and further semen production. Our objectives were to evaluate the relationship between boar structural traits and semen collection training traits and determine if structural traits influence presence and severity of skin lesions. Structural traits of developing Duroc boars (n = 82; 190 ± 10.3 d of age) were assessed at arrival to the stud and 6 wk later. Structural traits assessed included front and rear leg set, foot shape, chest width, and hip width (1 = poor; 5 = ideal). An overall structure score for each boar was determined by adding all structural trait scores. Lesions were assessed on a zero to three scale (0 = no lesions; 3 = severe lesions). Based on overall structure score, boars were categorized into one of three groups (poor, intermediate, or ideal) to determine if structural traits affected the presence and severity of lesions. All boars were subjected to semen collection training 1 wk after arriving at the stud and considered trained when successful mounting and ejaculation occurred. Pearson’s correlation coefficients were determined between total structure score, lesion severity, and semen collection training characteristics. The GLIMMIX procedure of SAS was used to assess lesion presence differences between structure groups. Structure score and lesion severity were not significantly correlated (-0.017; P = 0.91) with number of attempts to train, time to mount, or time to collection of ejaculates. Upon arrival at the stud, boars in the poor structure group displayed a greater (P &amp;lt; 0.01) incidence of lesions than intermediate and Ideal structure groups but did not have greater lesion severity (P = 0.74). After 6 wk in the boar stud, there were no differences (P = 0.83) in lesion presence or severity between structure groups, suggesting the lameness issues are more likely caused by housing environment or other factors than structural traits.

Comparative analysis of Spodoptera frugiperda (J. E. Smith) (Lepidoptera, Noctuidae) corn and rice strains microbiota revealed minor changes across life cycle and strain endosymbiont association.

Spodoptera frugiperda (FAW) is a pest that poses a significant threat to corn production worldwide, causing millions of dollars in losses. The species has evolved into two strains (corn and rice) that differ in their genetics, reproductive isolation, and resistance to insecticides and Bacillus thuringiensis endotoxins. The microbiota plays an important role in insects' physiology, nutrient acquisition, and response to chemical and biological controls. Several studies have been carried out on FAW microbiota from larvae guts using laboratory or field samples and a couple of studies have analyzed the corn strain microbiota across its life cycle. This investigation reveals the first comparison between corn strain (CS) and rice strain (RS) of FAW during different developmental insect stages and, more importantly, endosymbiont detection in both strains, highlighting the importance of studying both FAW populations and samples from different stages. The composition of microbiota during the life cycle of the FAW corn and rice strains was analyzed through high-throughput sequencing of the bacterial 16S rRNA gene using the MiSeq system. Additionally, culture-dependent techniques were used to isolate gut bacteria and the Transcribed Internal Spacer-ITS, 16S rRNA, and gyrB genes were examined to enhance bacterial identification. Richness, diversity, and bacterial composition changed significantly across the life cycle of FAW. Most diversity was observed in eggs and males. Differences in gut microbiota diversity between CS and RS were minor. However, Leuconostoc, A2, Klebsiella, Lachnoclostridium, Spiroplasma, and Mucispirilum were mainly associated with RS and Colidextribacter, Pelomonas, Weissella, and Arsenophonus to CS, suggesting that FAW strains differ in several genera according to the host plant. Firmicutes and Proteobacteria were the dominant phyla during FAW metamorphosis. Illeobacterium, Ralstonia, and Burkholderia exhibited similar abundancies in both strains. Enterococcus was identified as a conserved taxon across the entire FAW life cycle. Microbiota core communities mainly consisted of Enterococcus and Illeobacterium. A positive correlation was found between Spiroplasma with RS (sampled from eggs, larvae, pupae, and adults) and Arsenophonus (sampled from eggs, larvae, and adults) with CS. Enterococcus mundtii was predominant in all developmental stages. Previous studies have suggested its importance in FAW response to B. thuringensis. Our results are relevant for the characterization of FAW corn and rice strains microbiota to develop new strategies for their control. Detection of Arsenophonus in CS and Spiroplasma in RS are promising for the improvement of this pest management, as these bacteria induce male killing and larvae fitness reduction in other Lepidoptera species.

First report of Phytophthora infestans genotype US17 causing late blight on potato and tomato in British Columbia, Canada

Potato and tomato are grown in all Canadian provinces and contribute billions of dollars in exports and sales. Late blight, caused by Phytophthora infestans, is a destructive disease of potato and tomato worldwide and is responsible for millions of dollars in losses annually. Changes in pathogen strains were reported to be associated with late blight epidemics in several regions and pose challenges to late blight management. In British Columbia (BC), diverse strains of P. infestans were reported. Using multiplex microsatellite or simple sequence repeat (SSR) markers, we identified the new genotype US17 of P. infestans from samples of potato and tomato with late blight in BC. All isolates were of the A1 mating type. One, five, and one isolates were sensitive, moderately resistant, and highly resistant to metalaxyl-m, respectively. This is the first report of the occurrence of the US17 genotype in BC and Canada. The US17 strain was also able to cause tuber rot and foliar blight symptoms in potato in pathogen-inoculated assays.

Water-deficit stress induces prenylated stilbenoid production and affects biomass in peanut hairy roots: Exploring the role of stilbenoid prenyltransferase downregulation

The peanut plant is one of the most economically important crops around the world. Abiotic stress, such as drought, causes over five hundred million dollars in losses in peanut production per year. Peanuts are known to produce prenylated stilbenoids to counteract biotic stress. However, their role in abiotic stress tolerance has not been elucidated. To address this issue, hairy roots with the capacity to produce prenylated stilbenoids were established. An RNA-interference (RNAi) molecular construct targeting the stilbenoid-specific prenyltransferase AhR4DT-1 was designed and expressed via Agrobacterium rhizogenes-mediated transformation in hairy roots of peanut cultivar Georgia Green. Two transgenic hairy roots with the RNAi molecular construct were established, and the downregulation of AhR4DT-1 was validated using reverse transcriptase quantitative PCR. To determine the efficacy of the RNAi-approach in modifying the levels of prenylated stilbenoids, the hairy roots were co-treated with methyl jasmonate, hydrogen peroxide, cyclodextrin, and magnesium chloride to induce the production of stilbenoids and then the stilbenoids were analyzed in extracts of the culture medium. Highly reduced levels of prenylated stilbenoids were observed in the RNAi hairy roots. Furthermore, the hairy roots were evaluated in a polyethylene glycol (PEG) assay to assess the role of prenylated stilbenoids on water-deficit stress. Upon PEG treatment, stilbenoids were induced and secreted into the culture medium of RNAi and wild-type hairy roots. Additionally, the biomass of the RNAi hairy roots decreased by a higher amount as compared to the wild-type hairy roots suggesting that prenylated stilbenoids might play a role against water-deficit stress.

The audit of banks in the USA: Has it changed since the financial crisis?

The most recent financial crisis exposed to the auditors the risk associated with the audit engagement of their banking clients. Because many banking clients failed and investors suffered trillions of dollars in losses, auditors are now defendants in numerous shareholder and regulatory lawsuits. There is consensus that the financial crisis was created by an abundance of credit, excessive risk taking through complex financial instruments, weak corporate structures, and ineffective regulatory mechanisms. In this study, we examine how the financial crisis has affected the audit engagements of banking clients. We examine audit fees, audit report lag, and auditor changes before and after the financial crisis with respect to specific bank risks like credit risk, interest rate risk, and liquidity. Overall, we find that auditors are more responsive to bank risks in the post-financial crisis period compared to the pre-financial crisis period.

A fractional stochastic SPEIQR epidemic model in switching network for COVID-19

The rapid spread of COVID-19 globally is the cause of panic and billions of dollars in losses and some public policies have been implemented to contain the spread of the virus. It is highly significant to establish mathematical models to describe the spread of the pandemic. In this paper, a fractional stochastic susceptible–protected–exposed–infected–quarantined–recovered (SPEIQR) epidemic model in switching network is proposed to investigate COVID-19 and other diseases in the future, in which the switching connections in the propagation network of viruses based on a Bernoulli random variable are given to represent the policy change during COVID-19. The effects of environmental fluctuations are also considered by introducing the multiplicative noise terms into the disease transmission coefficient to obtain a more realistic mathematical model. Furthermore, the Riemann–Liouville fractional derivative is used to describe the dynamics of disease transmission process which is dependent on the history information of the stochastic system. Some qualitative properties of the model are derived and some sufficient conditions are obtained to ensure the local extinction with probability one of the disease. Finally, we use the epidemic data of three countries (Italy, Germany and Switzerland) and three cities in China (Hubei, Hunan and Henan) from January 22 to July 20 to demonstrate the validity of the derived results and the availability of the proposed models. This work provides some theoretical results to deeply understand the dynamics of COVID-19 and regulate the disease dynamics.

Overexpression of GmPAL Genes Enhances Soybean Resistance Against Heterodera glycines.

Soybean cyst nematode (Heterodera glycines, soybean cyst nematode [SCN]) disease adversely affects the yield of soybean and leads to billions of dollars in losses every year. To control the disease, it is necessary to study the resistance genes of the plant and their mechanisms. Isoflavonoids are secondary metabolites of the phenylalanine pathway, and they are synthesized in soybean. They are essential in plant response to biotic and abiotic stresses. In this study, we reported that phenylalanine ammonia-lyase (PAL) genes GmPALs involved in isoflavonoid biosynthesis, can positively regulate soybean resistance to SCN. Our previous study demonstrated that the expression of GmPAL genes in the resistant cultivar Huipizhi (HPZ) heidou are strongly induced by SCN. PAL is the rate-limiting enzyme that catalyzes the first step of phenylpropanoid metabolism, and it responds to biotic or abiotic stresses. Here, we demonstrate that the resistance of soybeans against SCN is suppressed by PAL inhibitor l-α-(aminooxy)-β-phenylpropionic acid (L-AOPP) treatment. Overexpression of eight GmPAL genes caused diapause of nematodes in transgenic roots. In a petiole-feeding bioassay, we identified that two isoflavones, daidzein and genistein, could enhance resistance against SCN and suppress nematode development. This study thus reveals GmPAL-mediated resistance against SCN, information that has good application potential. The role of isoflavones in soybean resistance provides new information for the control of SCN. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Understanding the battleground of identity fraud

Identity fraud has rapidly expanded into one of the fastest-growing white-collar crimes in the US. Beyond its substantial economic toll, resulting in billions of dollars in losses to the economy, identity fraud inflicts significant financial losses and mental distress upon its victims. With increasing online activity and the growing frequency of significant data breaches, the complexity and scale of identity fraud continue to grow. However, most academic research in this space has been focused on identifying cognitive behaviors and interventions at the individual level. Addressing a complex, multifaceted social issue like identity fraud necessitates a more comprehensive understanding of its underlying drivers at a broader macro level. We employed statistical methodologies to examine and analyze the factors influencing identity fraud in the US across a wide spectrum of variables using data from 2005 to 2021. A total of 12 explanatory variables, including macroeconomic indicators, sociodemographic factors, and criminal behavior, were analyzed. We identified the statistically significant variables associated with identity fraud through multiple linear regression, ANOVA, and multicollinearity analysis. Our analysis supported the hypothesis that the national unemployment rate, online banking usage, and incidence of fraud-related offenses were statistically significant variables in explaining identity fraud. Although not statistically significant, the increasing occurrence of data breaches and cyber-attacks and their implications for data security and privacy may warrant further attention. The overarching objective of this study was to establish a macro-level framework to understand identity fraud better, thereby fostering subsequent research and intervention efforts at both the individual and societal levels.

PhishTransformer: A Novel Approach to Detect Phishing Attacks Using URL Collection and Transformer

Phishing attacks are a major threat to online security, resulting in millions of dollars in losses. These attacks constantly evolve, forcing the cyber security community to improve detection systems. One major problem with current detection systems is that they cannot detect new phishing attacks, such as Browser in the Browser (BiTB) and malvertising attacks. These attacks hide behind legitimate Uniform Resource Locators (URLs) and can evade detection systems that only analyze a web page URL without exploring the page content. To address this problem, we propose PhishTransformer, a deep-learning model that can detect phishing attacks by analyzing URLs and page content. We propose only using URLs embedded within a webpage, such as hyperlinks and JFrames, to train PhishTransformer. This helps reduce the number of features that need to be extracted from the page content, which makes training the model more efficient. PhishTransformer combines convolutional neural networks and transformer encoders to extract features from website URLs and page content. These features are then used to train a classifier that can distinguish between phishing attacks and legitimate websites. We tested PhishTransformer on a dataset of 10,000 URLs. Our results show that PhishTransformer can achieve an F1-score of 99%, precision of 99%, and recall of 99%. This result suggests that PhishTransformer is a promising new approach to phishing detection.

Permethylation as a strategy for high-molecular-weight polysaccharide structure analysis by nuclear magnetic resonance-Case study of Xylella fastidiosa extracellular polysaccharide.

Current practices for structural analysis of extremely large-molecular-weight polysaccharides via solution-state nuclear magnetic resonance (NMR) spectroscopy incorporate partial depolymerization protocols that enable polysaccharide solubilization in suitable solvents. Non-specific depolymerization techniques utilized for glycosidic bond cleavage, such as chemical degradation or ultrasonication, potentially generate structural fragments that can complicate complete and accurate characterization of polysaccharide structures. Utilization of appropriate enzymes for polysaccharide degradation, on the other hand, requires prior structural knowledge and optimal enzyme activity conditions that are not available to an analyst working with novel or unknown compounds. Herein, we describe an application of a permethylation strategy that allows the complete dissolution of intact polysaccharides for NMR structural characterization. This approach is utilized for NMR analysis of Xylella fastidiosa extracellular polysaccharide (EPS), which is essential for the virulence of the plant pathogen that affects multiple commercial crops and is responsible for multibillion dollar losses each year.

Network security in multiple threats: A critical study

Any organization nowadays needs a secure network. High-speed wireless networks and internet services are becoming increasingly unsafe as a result of the daily rise in security threats. Threats to information security come from within the company, in close to 80% of cases. With the latest trend of mobility (portable devices such as laptops and smartphones etc.), ubiquitous 3G connectivity and this trend increases but as more web-based applications are manufactured and available over the Internet, the instances of insider threats have been rising at an alarming rate. Current or former workers, contractors, or business partners who have permission to access the organization's network and servers are typically the source of insider threats. Confidential information is frequently stolen for monetary gain or wellful harm. Access to hacking tools via the Internet, USB drives, and wireless connectivity make break-ins simple. Here, Millions of dollars in losses in the event of IP theft, and customer / individual information theft are yet too considered. This article provides insight into Insider dangers, attackers, and their rationales and recommendations for organizational-level mitigation methods.