Specific Date Research Articles

Reviewing the Evidence Base for Topical Steroid Withdrawal Syndrome in the Research Literature and Social Media Platforms: An Evidence Gap Map.

Within the dermatological community, topical steroid withdrawal syndrome (TSWS) is a medically contested condition with a limited research base. Published studies on TSWS indicate that it is a distinct adverse effect of prolonged use of topical corticosteroids, but there is a paucity of high-quality research evidence. Among the "patient community," awareness has been increasing, with rapid growth in social media posts on TSWS and the introduction of online communities such as the International Topical Steroid Awareness Network. This evidence gap map (EGM) was developed in response to recent calls for research to better understand TSWS and aims to be an important resource to guide both researchers and clinicians in the prioritization of research topics for further research. This study aims to identify the range, extent, and type of evidence on TSWS in the research literature and social media platforms using an EGM. The MEDLINE and Embase (Ovid), CINAHL (EBSCOhost), and ProQuest Dissertations & Theses and Conference Proceedings Citation Index (CPCI-Science and CPCI-Social Science & Humanities via Web of Science) databases were searched. The final search was run in November 2023. Study titles, abstracts, and full texts were screened by 2 reviewers, and a third was consulted to resolve any differences. Blogging sites WordPress, Medium, and Blogspot and Google were searched; Instagram and Reddit were searched for the 100 most recent posts on specific dates in February 2023. Blog titles, Instagram posts, and Reddit posts were screened for relevance by 2 reviewers. A data extraction tool was developed on EPPI-Reviewer, and data extraction was undertaken by one reviewer and checked by a second; any inconsistencies were resolved through discussion. We did not undertake quality appraisal of the included studies. EPPI-Reviewer and EPPI-Mapper were used to generate the interactive EGM. Overall, 81 academic publications and 223 social media posts were included in the EGM. The research evidence mainly addressed the physical symptoms of TSWS (skin), treatments, and, to a lesser extent, risk factors and disease mechanisms. The social media evidence primarily focused on the physical symptoms (skin and nonskin), mental health symptoms, relationships, activities of everyday living, beliefs and attitudes, and treatments. The EGM shows that research evidence is growing on TSWS but remains lacking in several important areas: longer-term prospective observational studies to assess the safety of prolonged use of topical corticosteroids and to prevent addiction; qualitative research to understand the lived experience of TSWS; and longitudinal research on the patient's "TSWS journey" to healing. The inclusion of social media evidence is a methodological innovation in EGMs, recognizing the increased presence of #topicalsteroidwithdrawal on social media and how it can be used to better understand the patient perspective and ultimately, provide better care for people with TSWS.

Intertemporal Pricing with Resellers: An Empirical Study of Product Drops

Product drops occur when a retailer releases a limited-edition product line on a specific date for a short period of time. Due to limited inventory of the product and the short sales horizon, a resale market emerges where products may resell at higher prices once the firm stocks out. The firm faces a central tradeoff: pricing too high may lead to a longer stockout time and future markdowns; pricing too low may lead to transfer of profits to resellers. Any firm in this position may ask, “How do resellers impact my profit?” To answer this question, we build a dynamic structural model that captures customer decisions to consume or strategically resell, as well as the firm’s intertemporal pricing decision in the presence of resellers. We estimate our model using a unique data set from a retailer of baby clothing with weekly product drops, where customers engage in a resale marketplace through Facebook groups. We find resale data collection and analysis is valuable to incorporate into pricing as firm profit increases by 8.8%, and reseller presence reduces firm profit by 5.8% even if resale data are used in pricing. These impacts are magnified by resale market growth, demonstrating that managers need to take action as resale markets gain wider adoption. This paper was accepted by Victor Martínez-de-Albéniz, operations management. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.04152 .

Years matter: the role of memory and place attachment in remote Nordic areas facing natural hazards

Remembrance, commemoration, and specific dates play an important role in many societies and cultures. They can be about positively connotated events with societal impacts, such as reunifications or the gaining of independence, but also disastrous or other devastating events on a national or international scale. In disaster risk areas, there are various ways such events are addressed. While for some communities they are an active part of the local history and the living memory, other communities tend to neglect or disregard such events. By applying a classification system, building on the ideas of Assmann (2011) and Halbwachs (1992), we identify active and passive forms of remembering in five case study areas in the Nordic countries. We investigate the possible positive and negative outcomes of the collective and cultural memory and how they relate to place attachment as well as capacity building. An example of positive outcomes is an even closer-knit community, exhibiting place-protective behavior, that learns from past events and is better prepared for future disasters. A negative example at the local scale is willful blindness and the neglect of any risk. However, the society outside an affected settlement is also important in the creation and manifestation of the collective and cultural memory: stigmatization and ascription can be negative side effects. Small and remote communities may be recognized by society at large for only one point in time—a year and a disaster—thus sidelining the positive attributes of such communities.

How text message reminders increase COVID-19 booster vaccine uptake: Two randomized controlled trials

BackgroundVaccines are effective and affordable health prevention measures to prevent vaccine-preventable diseases, but achieving sufficient vaccine uptake population-wide is challenging. In this work, we assess the impact of various text messages reminders on COVID-19 booster uptake and the extent to which the effect of messages holds over time. Additionally, we analyse whether people's self-reported vaccination intentions (measured in response to message prompts) corresponds to actual vaccine uptake and whether this relationship differs between message variants. MethodsWe performed two large sequential randomized controlled trials (RCTs) in the Netherlands (N = 140.973), with the design of RCT2 building on the findings of RCT1. We 1) analyzed the effect of various text messages on COVID-19 booster uptake; 2) assessed the extent to which these effects hold over time; and 3) tested whether a positive response to message prompts moderates the effect of message variant on vaccine uptake. ResultsFirst, the results of RCT1 demonstrate that text messages with an ownership frame (“your [vaccine] is ready for you”) result in highest vaccine uptake (e.g., compared to no text message: OR = 1.28 [99 % CI 1.03–1.59]). RCT2 showed that text messages with an ownership frame and a specific date, time and location result in highest vaccine uptake (e.g., compared to no text message: OR = 2.10 [99 % CI 1.85–2.38]). Second, most message effects hold over a longer period of time (e.g., ‘date, time, location’ message versus no message: OR = 2.10 [99 % CI 1.85–2.38] on day 6 and OR = 1.36 [99 % CI 1.25–1.48] on day 50). Third, we find that participants who received our most effective text and replied that they will take the vaccine, are more inclined to actually take the vaccine compared to the message with broad opening hours OR = 2.86 [99 % CI 2.14–3.82]. ConclusionText message reminders are able to increase vaccine uptake. From the tested variations, messages with an ownership frame providing a specific date, time and location are most effective. Because text messages demonstrate no notable disadvantages, we advise Public Health authorities to include this effective intervention in their vaccination campaign strategies.

College Campus Tour using AR/VR

This project focuses on developing an immersive 360° virtual campus tour using augmented and virtual reality (AR/VR) technologies to enhance accessibility and engagement for prospective students, alumni, and visitors. Integrated into the college's official website, this virtual tour enables users to explore key campus locations, view event-based images and information by selecting specific dates, and experience campus life from a remote setting. By leveraging high-definition 360° video and interactive elements, the project addresses challenges in accessibility, engagement, and marketing faced by traditional static campus presentations. The system architecture includes modules for video capture, interactive feature integration, and seamless website embedding, utilizing advanced technologies like WebGL, A-Frame, and machine learning algorithms for content retrieval and event-based data integration. The project aims to increase the institution's digital presence and support recruitment and alumni engagement

Mass incarceration as a driver of the tuberculosis epidemic in Latin America and projected effects of policy alternatives: a mathematical modelling study

Tuberculosis incidence is increasing in Latin America, where the incarcerated population has nearly quadrupled since 1990. We aimed to quantify the impact of historical and future incarceration policies on the tuberculosis epidemic, accounting for effects in and beyond prisons. In this modelling study, we calibrated dynamic compartmental transmission models to historical and contemporary data from Argentina, Brazil, Colombia, El Salvador, Mexico, and Peru, which comprise approximately 80% of the region's incarcerated population and tuberculosis burden. The model was fit independently for each country to incarceration and tuberculosis data from 1990 to 2023 (specific dates were country dependent). The model does not include HIV, drug resistance, gender or sex, or age structure. Using historical counterfactual scenarios, we estimated the transmission population attributable fraction (tPAF) for incarceration and the excess population-level burden attributable to increasing incarceration prevalence since 1990. We additionally projected the effect of alternative incarceration policies on future population tuberculosis incidence. Population tuberculosis incidence in 2019 was 29·4% (95% uncertainty interval [UI] 23·9-36·8) higher than expected without the rise in incarceration since 1990, corresponding to 34 393 (28 295-42 579) excess incident cases across countries. The incarceration tPAF in 2019 was 27·2% (20·9-35·8), exceeding estimates for other risk factors like HIV, alcohol use disorder, and undernutrition. Compared with a scenario where incarceration rates remain stable at current levels, a gradual 50% reduction in prison admissions and duration of incarceration by 2034 would reduce population tuberculosis incidence by over 10% in all countries except Mexico. The historical rise in incarceration in Latin America has resulted in a large excess tuberculosis burden that has been under-recognised to date. International health agencies, ministries of justice, and national tuberculosis programmes should collaborate to address this health crisis with comprehensive strategies, including decarceration. National Institutes of Health.

Finding The Relationship between Pulsation Motion and Hα Emission Lines on γ Cas using Photometric and Spectroscopic Data

Abstract Pulsating stars show variability in brightness due to changes in their volume. There are two types of pulsation/oscillation: radial and non-radial. Radial oscillation keeps the symmetrical shape of the star, while non-radial oscillation does not. We study a pulsating star: γ Cas, classified as a B0.5 IVe variable star because of its pulsations and also an emission star due to the emission lines in its spectra. When a star pulsates, its atmosphere expands and contracts, potentially leading to the formation of shock waves. Observational features such as discontinuities in the radial velocity curve and emission lines support this phenomenon. In this study, we analyse the relationship between pulsation motion and the H α emission lines of γ Cas using photometric and spectroscopic data. Photometric data is obtained from the BRIght Target Explorer (BRITE) catalog, while spectroscopic data comes from the Be Star Spectra (BeSS) catalog. Both datasets cover the same observational dates: August 28 to October 26, 2015. Confirming the pulsation period of γ Cas at 1.21 days, we also discover an added pulsation period of 10 days from photometric data. To confirm this, we examine spectroscopic data from three specific dates: August 28, September 7, and 27, 2015. Notably, the relative flux of the H α emission lines continue to increase, leading us to conclude that these lines are indeed caused by the pulsation of γ Cas.

ChronoBak: Automated cost-effective incremental backup software for large-scale data

Background: Data backup is an important component of data protection and management. It is especially imperative to back up large-scale data to guard against losses due to hardware failure, unauthorized access, software/system malfunction, and unintended deletion. However, businesses and organizations suffer from the financial investment required for data backup and recovery systems. Health-care systems suffer from data breaches and hacking incidents, which increase annually. Therefore, a cost-effective and highly secure backup approach is necessary. Methods: Seven different backup scripts were written in bash within Linux, and Crontab was used as the core chronological scheduler to execute the backup scripts on specific dates and times. These bash scripts, together with Crontab as their scheduler, were used to implement automated incremental backups on a Unix/Linux-based system. Results: ChronoBak is a collection of bash scripts that are compiled and executed through Crontab, which is a standard Unix/Linux function used to schedule hourly, daily, weekly, and monthly maintenance routines using Linux scripts. This strategy enabled us to implement cost-effective incremental backups within any time range. Conclusion: We developed ChronoBak software, which executes an automated incremental backup that is scheduled efficiently and systematically using standard and hidden directories, thereby providing an additional layer of security against cyber threats and system malfunctions.

Due date-oriented picker routing, an efficient exact solution algorithm, and its application to pick-from-store omnichannel retailing

The advent of e-commerce and omnichannel retailing has sparked renewed interest in picker routing in warehouses. This paper presents two significant methodological advances in this well-established field. First, it is a well-known fact that the parallel-aisle layout of warehouses, as opposed to general graphs, allows for polynomial-time solutions of the Traveling Salesman Problem. We show that the parallel-aisle structure can also be exploited when pickers are tasked with visiting storage positions associated with specific due dates. We establish that picker routing in warehouses, subject to soft due date constraints, is a binary NP-hard problem. We also present an exact branch-and-bound algorithm with pseudo-polynomial time complexity. This algorithm effectively solves instances with up to 60 picking positions and five cross aisles within a few seconds while guaranteeing optimality. Second, for even larger pick lists, we demonstrate the successful integration of our algorithm into a real-time framework. This approach allows us to avoid extended solution times that would otherwise delay the picker’s departure, without compromising the quality of the solution. To illustrate the practical relevance of these two methodological innovations, we apply our routing algorithm to the context of pick-from-store omnichannel retailing. By assigning due dates to critical products, we significantly reduce stockout occurrences for online customers. These stockouts occur when the stock level, initially deemed sufficient to confirm an online order, is depleted by walk-in customers before the picker reaches the relevant shelf.

Using the Observed Variations of the Start Date of the Rainy Season over Central America for Its Reliable Seasonal Outlook

Abstract We introduce a simple method to define the start and the end of the rainiest part of the year as the first and the last day of the year when the daily rain rate is more or less than the annual mean climatological rain rate for a region or at a given grid point of the rainfall analysis, respectively. A novelty of this work is the adoption of a perturbation technique to generate a total of 1001 ensemble members to account for observational and analysis uncertainties. This allows for a probabilistic estimate of the start and retreat dates of the rainy season at the granularity of the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG), version 6, rainfall analysis over Central America. The seasonal cycle of the IMERG rainfall analysis is also found to verify with in situ observations in the region. Many large-scale climate drivers affect regional rainfall, often with complex interactions that affect the onset date, retreat date, and magnitude of the seasonal rainfall cycle, making it difficult to predict the length or total quantity of seasonal rainfall using climate drivers alone. Once an onset date is established, however, this metric alone can be more indicative of both the length and total seasonal rainfall anomaly than predicting how the climate drivers will interact to affect the quantity and duration of upcoming seasonal rainfall. The local relationships of the start date with seasonal length and rainfall anomaly are leveraged to produce effective seasonal outlooks of the rainy season for the region by just monitoring the start date variations. Significance Statement The start date and retreat date of the rainy season in Central America are defined every year, precisely to a specific date from our proposed definition of it. This is possible because the region exhibits a strong seasonality of the rainfall. As a result, the year-to-year (interannual) variation of the seasonal rainfall during the rainy season is also determined by the variations in the length of the season that are usually overlooked in fixed calendar seasons. We define the start or retreat date of the rainy season as the first or the last day of the year when the daily rain rate exceeds or falls below the average daily rainfall from 2001 to 2022, respectively. We also find that both start and retreat date variations independently influence the length and total seasonal rainfall of the rainy season. Consequently, these relationships are leveraged to provide an outlook of the forthcoming rainy season from the diagnosis of the variations of its onset date, which is shown to be an effective predictor with significant useful seasonal prediction skills.

Innovation and Patenting Activities During COVID-19 and Advancement of Biochemical and Molecular Diagnosis in the Post- COVID-19 Era.

The COVID-19 pandemic is to escalate globally and acquire new mutations quickly, so accurate diagnostic technologies play a vital role in controlling and understanding the epidemiology of the disease. A plethora of technologies acquires diagnosis of individuals and informs clinical management of COVID. Some important biochemical parameters for COVID diagnosis are the elevation of liver enzymes, creatinine, and nonspecific inflammatory markers such as C-reactive protein (CRP) and Interleukin 6 (IL-6). The main progression predictors are lymphopenia, elevated D-dimer, and hyperferritinemia, although it is also necessary to consider LDH, CPK, and troponin in the marker panel of diagnosis. Owing to the greater sensitivity and accuracy, molecular technologies such as conventional polymerase chain reaction (PCR), reverse transcription (RT)-PCR, nested PCR, loop-mediated isothermal amplification (LAMP), and xMAP technology have been extensively used for COVID diagnosis for some time now. To make so many diagnostics accessible to general people, many techniques may be exploited, including point of care (POC), also called bedside testing, which is developing as a portable promising tool in pathogen identification. Some other lateral flow assay (LFA)-centered techniques like SHERLOCK, CRISPR-Cas12a (AIOD-CRISPR), and FNCAS9 editor limited uniform detection assay (FELUDA), etc. have shown auspicious results in the rapid detection of pathogens. More recently, low-cost sequencing and advancements in big data management have resulted in a slow but steady rise of next-generation sequencing (NGS)-based approaches for diagnosis that have potential relevance for clinical purposes and may pave the way toward a better future. Due to the COVID-19 pandemic, various institutions provided free, specialized websites and tools to promote research and access to critically needed advanced solutions by alleviating research and analysis of data within a substantial body of scientific and patent literature regarding biochemical and molecular diagnosis published since January 2020. This circumstance is unquestionably unique and difficult for anyone using patent information to find pertinent disclosures at a specific date in a trustworthy manner.

Accurately identifying incident cases of venous thromboembolism in the electronic health record: Performance of a novel phenotyping algorithm

BackgroundAccurate identification of incident venous thromboembolism (VTE) for quality improvement and health services research is challenging. The purpose of this study was to evaluate the performance of a novel incident VTE phenotyping algorithm defined using standard terminologies, requiring three key indicators documented in the electronic health record (EHR): VTE diagnostic code, VTE-related imaging procedure code, and anticoagulant medication code. MethodsRetrospective chart reviews were conducted to assess the performance of the algorithm using a random sample of phenotype(+) and phenotype(−) diagnostic encounters from primary care practices and acute care sites affiliated with five hospitals across a large integrated care delivery system in Massachusetts. The performance of the algorithm was evaluated by calculating the positive predictive value (PPV), negative predictive value (NPV), sensitivity, and specificity, using the phenotype(+) and phenotype(−) diagnostic encounters sample and target population data. ResultsBased on gold-standard manual chart review, the algorithm had a PPV of 95.2 % (95 % CI: 93.1–96.8 %), NPV of 97.1 % (95 % CI: 95.3–98.4 %), sensitivity of 91.7 % (95 % CI: 90.8–92.6 %), and specificity of 98.4 % (95 % CI: 98.1–98.6 %). The algorithm systematically misclassified a low number of specific types of encounters, highlighting potential areas for improvement. ConclusionsThis novel phenotyping algorithm offers an accurate approach for identifying incident VTE in general populations using EHR data and standard terminologies, and accurately identifies the specific encounter and date of diagnosis of the incident VTE. This approach can be used for measurement of incident VTE to drive quality improvement, research to expand the evidence, and development of quality metrics and clinical decision support to improve the diagnostic process.

Digital tax reform in Indonesia: Perspective on tax policy development

In Indonesia tax reform has undergone multiple revisions in recent years, all within a brief timeframe. Digital tax reform in Indonesia began with significant milestones in recent years to adapt to the digital economy’s challenges. The specific start date for digital tax reform in Indonesia can be traced back to the passing of the Tax Regulations Harmonization Law on 7th October 2021, which officially became Law No 7/2021 on 29th October 2021. This law marked a crucial step in Indonesia’s journey towards modernizing its tax system to address the implications of the digital economy. The provisions of this law have varying effective dates, such as for income tax purposes from the 2022 fiscal year and for VAT purposes from 1st April 2022. These changes under the Tax Regulations Harmonization Law are extensive and wide-reaching, signifying a pivotal moment in Indonesia’s digital tax reform efforts. This shows that the Indonesian government intends to radically overhaul the tax system, yet there are inconsistent approaches to deciding on the long-term course of tax policy. It is critical to investigate the concept of tax legislation in Indonesia in order to provide legal clarity on digital tax reform. Normative juridical research methodology is employed, together with a qualitative research strategy and descriptive-analytical research specifications. The findings suggest that the Indonesian government’s efforts to establish strict policies governing taxes on digital activity are inadequate and uneven. In order to apply to digital platform enterprises, the definition of permanent establishment as outlined in a number of national regulations must incorporate a substantial economic presence criterion. Legislative progress toward the establishment of a framework for digital tax collection is necessary to mitigate the possible income loss of states in this area, which could result from the rapid advancement of information technology. The OECD consensus is still in the process of drafting an international tax reform that will require adjustments from national tax reform. Therefore, it is imperative that the Indonesian government establish a thorough framework for tax regulation that can ensure robustness, economic efficiency, fairness, against motivation compatibility, administrative ease, and avoidance.

Exploring the Influence of Date Palm Cultivars on Soil Microbiota

Plants thrive in diverse environments, where root-microbe interactions play a pivotal role. Date palm (Phoenix dactylifera L.), with its genetic diversity and resilience, is an ideal model for studying microbial adaptation to different genotypes and stresses. This study aimed to analyze the bacterial and fungal communities associated with traditional date palm cultivars and the widely cultivated “Deglet Nour” were explored using metabarcoding approaches. The microbial diversity analysis identified a rich community with 13,189 bacterial and 6442 fungal Amplicon Sequence Variants (ASVs). Actinobacteriota, Proteobacteria, and Bacteroidota dominated bacterial communities, while Ascomycota dominated fungal communities. Analysis of the microbial community revealed the emergence of two distinct clusters correlating with specific date palm cultivars, but fungal communities showed higher sensitivity to date palm genotype variations compared to bacterial communities. The commercial cultivar “Deglet Nour” exhibited a unique microbial composition enriched in pathogenic fungal taxa, which was correlated with its genetic distance. Overall, our study contributes to understanding the complex interactions between date palm genotypes and soil microbiota, highlighting the genotype role in microbial community structure, particularly among fungi. These findings suggest correlations between date palm genotype, stress tolerance, and microbial assembly, with implications for plant health and resilience. Further research is needed to elucidate genotype-specific microbial interactions and their role in enhancing plant resilience to environmental stresses.

The Oral History of “Pandemic Time”: Students’ Lives Through the Global COVID-19 Pandemic

ABSTRACT This article offers a reflective account of student memories of the first years of the COVID-19 pandemic in both the Czech Republic and Israel. By comparing the narratives of students from these nations, we introduce the notion of “pandemic time” to describe the ways in which personal experiences of time rest betwixt and between objective historical events and individual meaning-making. In this way, we argue that university students narrated the crisis inherent in pandemic time on two overlapping levels. On the one hand, students’ memories revolved around the broader objective timeline of the COVID-19 pandemic (to include specific dates of lockdowns, university closures, openings, etc.). On the other hand, our student informants in both countries appeared to experience these events in ways that diverged from this objective timeline. Specific events in both countries that appeared to supersede the health threat posed by the pandemic shaped how they recounted their experiences of the pandemic. Using narrative analysis, we identified several key themes to explore student perspectives about pandemic time: how social isolation impacted an understanding of time, both referentially (when things happened in relation to each other) and temporally (within the overall span of the pandemic); how our narrators perceived the pandemic overall; broad and intimate experiences with COVID-19; how long remote learning lasted; and when narrators perceived the pandemic as having ended. By exploring this concept of pandemic time, we show how an international focus on oral history across national and cultural boundaries makes it possible to tease apart diverging experiences of time, memory, and crisis and to demonstrate how that relates directly to oral history theory and methodology.

Assessing the long-term economic impact of wheezing episodes after severe RSV disease in children from Argentina: a cost of illness analysis

IntroductionThere is lack of available data on the economic burden of wheezing episodes after severe respiratory syncytial virus (RSV) infection. This study aimed to assess the cost incurred for wheezing...

Myths and Realities: How Different Forms of Superstitious Beliefs Create Good and Bad Luck for People in Pakistan through an Anthropological Lens

The present research explores various forms of superstitious beliefs that are commonly practiced, despite being inconsistent with rational thought and known laws of nature. These beliefs are often followed by individuals in their daily routines, in the hope of attracting good luck and avoiding bad luck. The study was conducted in the Lal Qala District of Dir Lower, Malakand Division, Khyber Pakhtunkhwa, Pakistan. Data was collected from 23 participants using purposive sampling, through in-depth interviews and participant observation. A qualitative approach was employed, and primary information was supplemented with empirical data to analyze the different forms of superstitious beliefs and their underlying themes. Thematic analysis revealed that various superstitious beliefs, such as stepping below a ladder, encountering cat with black color passing one's path, considering specific dates like the 13th of March as unlucky, and beliefs related to weddings and colors, are widely practiced to either attract or avoid future occurrences of good or bad luck. However, it is suggested that eliminating these superstitious beliefs from society can be achieved through proper religious training, the spread of education, the dissemination of positive and scientific knowledge, and the constructive role of media.

A revised radiocarbon calibration curve 350-250 BCE impacts high-precision dating of the Kyrenia Ship.

The Kyrenia Ship, found off the north coast of Cyprus, is a key vessel in the history of scientific underwater excavations and in the history of Greek shipbuilding. The first volume of the site's final publication appeared in 2023 and provides detailed archaeological information tightly constraining the dating of the ship. A very specific date range is proposed: ca. 294-290 BCE, but is based on a less than certain reading of one coin recovered from the ship. While there is clear benefit to finding high-precision dates for the Kyrenia Ship and its rich assemblage using independent scientific dating (combined with Bayesian chronological modeling), efforts to do so proved more challenging and complex than initially anticipated. Strikingly, extensive radiocarbon dating on both wooden materials from the ship and on short-lived contents from the final use of the ship fail to offer dates using the IntCal20 calibration curve-the current Northern Hemisphere radiocarbon calibration curve at the time of writing-that correspond with the archaeological constraints. The issue rests with a segment of IntCal20 ca. 350-250 BCE reliant on legacy pre-AMS radiocarbon data. We therefore measured new known-age tree-ring samples 350-250 BCE, and, integrating another series of new known-age tree-ring data, we obtained a redefined and more accurate calibration record for the period 433-250 BCE. These new data permit a satisfactory dating solution for the ship and may even indicate a date that is a (very) few years more recent than current estimations. These new data in addition confirm and only very slightly modify the dating recently published for the Mazotos ship, another Greek merchant ship from the southern coast of Cyprus. Our work further investigated whether ship wood samples impregnated with a common preservative, polyethylene glycol (PEG), can be cleaned successfully, including a known-age test.

Flower Forcing: A Review

In the modern floricultural industry, scheduling plant production is essential due to fluctuating market demands. Flower forcing, which stimulates flowering at specific dates or during off-season periods, is a key technique employed. The manipulated flowering dates resulting from flower forcing may deviate from the plant's natural schedule, occurring either earlier or later than the standard flowering dates. This can be achieved by adjusting factors affecting flowering such as temperature, photoperiod, and irradiance etc. Implementation of special practices like pruning, leaf trimming, dormancy breaking helps in forcing operation in certain plants. Utilization of chemicals such as plant hormones like gibberellin and ethylene, growth retardants and some fertilizers also play an important role in forcing. Employing mechanical methods can be considered as a sustainable and environment friendly practice. Advancements in plant physiology, photomorphogenesis, metabolism, and greenhouse technologies have led to the development of multiple strategies to finely regulate the rate of plant growth and development across various crops.

Developing agricultural pest management strategies with reduced-risks to surface water: An economic case study of California's Central Coast region

Pesticides are critical for protecting agricultural crops, but the off-site transport of these materials via spray drift and runoff poses risks to surface waters and aquatic life. California's Central Coast region is a major agricultural hub in the United States characterized by year-round production and intensive use of pesticides and other chemical inputs. As a result, the quality of many waterbodies in the region has been degraded. A recent regulatory program enacted by the Central Coast Regional Water Quality Control Board set new pesticide limits for waterways and imposed enhanced enforcement mechanisms to help ensure that water quality targets are met by specific dates. This regulatory program, however, does not mandate specific changes to pest management programs. In this study, we evaluate the economic, environmental, and pest management impacts of adopting two alternative pest management programs with reduced risks to surface water: 1) replacing currently used insecticide active ingredients (AIs) that pose the greatest risk to surface water with lower-risk alternatives and 2) converting conventional arthropod pest management programs to organic ones. We utilize pesticide use and toxicity data from California's Department of Pesticide Regulation to develop our baseline and two alternative scenarios. We focus on three crop groups (cole crops, lettuce and strawberry) due to their economic importance to the Central Coast and use of high-risk AIs. For Scenario 1, we estimate that implementing the alternative program in the years 2017–2019 would have reduced annual net returns on average by $90.26 – $190.54/ha, depending on the crop. Increased material costs accounted for the greatest share of this effect (71.9%–95.6%). In contrast, Scenario 2 would have reduced annual net returns on average by $5,628.12 – $18,708.28/ha during the study period, with yield loss accounting for the greatest share (92.8–97.9%). Both alternative programs would have reduced the associated toxic units by at least 98.1% compared to the baseline scenario. Our analysis provides important guidance for policymakers and agricultural producers looking to achieve environmental protection goals while minimizing economic impacts.