We construct a novel family of summation-integral type hybrid operators in terms of shape parameter $\alpha\in \lbrack 0,1]$ in this paper. Basic estimates, rate of convergence, and order of approximation are also studied using the Korovkin theorem and the modulus of smoothness. We investigate the local approximation findings for these sequences of positive linear operators utilising Peetre's K-functional, Lipschitz class, and second-order modulus of smoothness.

Increasing the quality factor (Q) of an optical resonator device has been a research focus to be utilized in various applications. Higher Q-factor means light is confined in a longer time which will produce a shaper peak and higher transmission. In this paper, we introduce a novel technique to increase further the Q-factor of a one-dimensional photonic crystal (1D PhC) cavity device by using an end loop-mirror (ELM). The technique utilizes and recycles the light transmission from the conventional 1D PhC cavity design. The design has been proved to work by using the 2.5D FDTD simulation with Lumerical FDTD and MODE softwares. By using the ELM technique, the Q- factor of a 1D PhC design has been shown to have increased up to 79.53 % from the initial Q value without the ELM. This novel design technique can be combined with any high Q-factor and very high Q-factor designs to increase more the Q-factor value of a photonic crystal cavity devices or any other suitable optical resonator devices. The experimental result shows that the device is measurable by adding a Y-branch component to the one-port structure and able to get the high-Q result.

In this paper we introduce the hypo-q-norms on a Cartesian product of algebras of bounded linear operators on Hilbert spaces. A representation of these norms in terms of inner products, the equivalence with the q-norms on a Cartesian product and some reverse inequalities obtained via the scalar reverses of Cauchy-Buniakowski-Schwarz inequality are also given. Several bounds for the norms δ_p, ϑ_p and the real norms η_r,p and θ_r,p are provided as well.

The genus Strophantus belongs to the Apocynaceae family of flowering plants which grows primarily in tropical Africa. The plants are widely used in traditional herbal medicine. S. sarmentosus, in particular, is used for the treatment of, e.g., joint pain and rheumatoid arthritis, wound infections, head lice, diarrhoea, snake bite, and eye conditions. Despite the widespread use, dedicated research characterizing bioactive plant components is scarce. Investigations focussed mainly on the cardenolides, because of their cardioactivity and historical use as cardiotonic. There are also studies concerning the antibacterial, antioxidant and anti-inflammatory activity of plant extracts. This review summarizes the present knowledge about the biochemical and analytical reserach on Strophantus, in general, and S. sarmentosus, in particular, and describes the current state-of-the-field based on the available sientific literature.

We study L_2-approximation problems in the weighted Hilbert spaces in the worst case setting. Three interesting weighted Hilbert spaces appear in this paper, whose weights are equipped with two positive parameters $\ga_j$ and $\az_j$ for $j=1,\,2,\dots,\,d$. We consider the worst case error of algorithms that use finitely many arbitrary continuous linear functionals. We discuss the exponential convergence-(t,s)-weak tractability (EC-(t,s)-WT) of these L_2-approximation problems under the absolute or normalized error criterion. In particular, we obtain the sufficient and necessary conditions for EC-(1,1)-WT and EC-(t,1)-WT with t

In this paper we investigate some properties of square-free numbers. In particular, we study a function that counts the number of square-free numbers no larger than the given number n. We show that this function has asymptotics consistent with the predictions of the Riemann hypothesis and use this to obtain new and better estimates of the density of square-free numbers. Finally, we present a well-known generalization of the concept of a square-free number to monoids and research on square-free factorizations.

The implementation of management systems has become a strategic advantage in achieving business goals, especially in industrial organizations, but the implementation of social responsibility requirements is especially ethical. Large multinational companies have long been developing and, in particular, implementing their own codes of conduct, which include their suppliers, to demonstrate their commitment to Corporate Social Responsibility (CSR). The compliance with CSR requirements from stakeholders is thus extended or intertwined with requirements in established management systems (MSs). The objectives of the study were to (1) analyze the different approaches to CSR in internationally recognized cross-industry and industry-specific standards and codes in different industries; (2) select the most appropriate framework for assessing the degree of applicability of CSR in the selected management systems and develop a methodology for its assessment; (3) apply the proposed methodology (referred to as SRIMS) in the selected areas: automotive industry, research organization, and metallurgical industry; (4) through ANOVA, validate its use for assessing the overall level of CSR applicability in an organization's established management systems. The application of the Bonferroni method confirmed the hypotheses that the developed SRIMS model is a sufficiently appropriate tool for assessing the overall level of applicability of CSR requirements to established MSs.

Understanding the motor patterns underlying the movement of people with Parkinson's disease (PD) is fundamental to the effective targeting of non-pharmacological therapies. This study aims to analyze the gait pattern in relation to the evolutionary stage between I-II and III-IV according to the Hoehn and Yahr scale (H&Y) in people affected by PD. The study was conducted with the participation of 37 PD patients, with a mean age of 70.09±9.53 years, and of whom 48.64% were women. The inclusion criteria were: 1. To be diagnosed with PD; 2. To be in an evolutionary stage of the disease of between I and IV and; 3. To be able to walk independently and without any assistance. Kinematic and spatial-temporal parameters of the gait were analyzed. The results show differences in speed of movement, cadence, stride length, support duration, swing duration, step width, walking cycle duration and double support time between the stages analyzed. These results confirm the differences in PD gait pattern between stages I-II and III-IV. Different behaviors of the same variable were recorded depending on whether the right or left sides were affected by PD.

Micro-combs [1-4] - optical frequency combs generated by integrated micro-cavity resonators – offer the full potential of their bulk counterparts [5,6], but in an integrated footprint. The discovery of temporal soliton states (DKS – dissipative Kerr solitons) [4,7-11] as a means of mode-locking micro-combs has enabled breakthroughs in many fields including spectroscopy [12,13], microwave photonics [14], frequency synthesis [15], optical ranging [16,17], quantum sources [18,19], metrology [20,21] and more. One of their most promising applications has been optical fibre communications where they have enabled massively parallel ultrahigh capacity multiplexed data transmission [22,23]. Here, by using a new and powerful class of micro-comb called “soliton crystals” [11], we achieve unprecedented data transmission over standard optical fibre using a single integrated chip source. We demonstrate a line rate of 44.2 Terabits per second (Tb/s) using the telecommunications C-band at 1550nm with a spectral efficiency – a critically important performance metric - of 10.4 bits/s/Hz. Soliton crystals exhibit robust and stable generation and operation as well as a high intrinsic efficiency that, together with a low soliton micro-comb spacing of 48.9 GHz enable the use of a very high coherent data modulation format of 64 QAM (quadrature amplitude modulated). We demonstrate error free transmission over 75 km of standard optical fibre in the laboratory as well as in a field trial over an installed metropolitan optical fibre network. These experiments were greatly aided by the ability of the soliton crystals to operate without stabilization or feedback control. This work demonstrates the capability of optical soliton crystal micro-combs to perform in demanding and practical optical communications networks.

Monolayered MoS₂ is energetically most stable when it has a 1H phase, but 1H to 1T phase transition (1H→1T) is easily realized by various ways. Even though magnetic moment is not observed during 1H1T, 0.049 µB/MoS₂ is obtained in local 1T phase; 75% 2H and 25% 1T phases are mixed in (2×2) supercell. Furthermore, non-negligible magnetocrystalline anisotropy (MCA) energy is occured. Most magnetic moment as well as MCA are originated by 1T phased Mo atom5 in the supercell, while electronic structures of other atoms are similar to non-magnetic. Due to this, magnetic/non-magnetic boundary is created in the monolayered MoS2. Our result suggests that MoS₂ can be applied for spintronics such as a spin transistor.

In this paper we define a continuous wavelet transform of a Schwartz tempered distribution $f \in S^{'}(\mathbb R^n)$ with wavelet kernel $\psi \in S(\mathbb R^n)$ and derive the corresponding wavelet inversion formula interpreting convergence in the weak topology of $S^{'}(\mathbb R^n)$. It turns out that the wavelet transform of a constant distribution is zero and our wavelet inversion formula is not true for constant distribution, but it is true for a non-constant distribution which is not equal to the sum of a non-constant distribution with a non-zero constant distribution.

Abstract: Efforts for carbon emission reduction have been identified as a major climate change mitigation target in the Paris Agreement. The 26th Conference of Parties to the United Nations Framework Convention on Climate Change highlighted the worldwide effort for cleaner and greener mining, urging the mineral industry to embrace greener operational emissions reduction technologies and strategies. Ghana pledged at the Paris Conference to reduce CO2 emissions by 15% and increase renewable energy share to 10% of the national energy mix. Here the fundamental question is how Ghana’s mining industry can contribute to CO2 emission reduction efforts. This paper investigates barriers to low-carbon emission policy implementation among mining companies in Ghana. The questionnaire survey was conducted among Ghana’s four large-scale gold mining companies. As the sample number of available companies is limited, we used a descriptive analysis to assess the responses. The results show that the companies expressed widely different ways to respond to the issues of cost, a government policy/regulations for carbon emission reduction, and the adoption/acquisition of low-carbon technologies. Those companies that are relatively less prepared for this endeavor emphasized the uncertainties of securing sufficient energy in case of using low-carbon technologies. They also expressed a need for more trained workers to handle low-carbon technologies. All companies agreed with a expected high cost of adopting low-carbon options. There was a communication gap with the relevant government ministry about low-carbon mining options where the government should be able to facilitate the involvement of othe low technology providers, such as solar PV installation.

This study analyzes the relationship between economic policy uncertainty (hereinafter EPU) and corporate value, and verifies the differential effects of EPU on corporate value according to corporate social responsibility (hereinafter CSR) activities. The study period was from 2010 to 2020, and the EPU indexes measured by Baker et al. (2016)'s method and Hexun's CSR scores for companies listed on the Chinese stock market were used. Hexun is one of the three major evaluation agencies in China, and the CSR scores evaluated by this agency have been widely used in previous studies as a representative indicator of Chinese companies' CSR performance. The results of this study are as follows. First, EPU and corporate value were found to have a negative (-) relationship. Second, active CSR activities relieved the negative (-) relationship between EPU and corporate value. Finally, companies were divided into groups according to CSR activity scores to analyze the relationship and according to the result, the negative (-) relationship between EPU and corporate value was greater in the groups with low CSR activity scores than in the groups with high CSR activity scores. A lag model was applied to control endogeneity, and the results were consistent with the main results above. Previous studies have mainly focused on microscopic factors to investigate factors affecting corporate value. This study focused on macroeconomic policies and paid attention to the effects of changes in the macroenvironment caused by economic policy uncertainty on corporate value. In addition, this study is meaningful in that it expanded previous studies related to CSR activities by confirming that active CSR activities can be an advantageous tool for overcoming EPU.

Inclusive education recognizes the diverse needs of students and ensures that each student is pro-vided with equal opportunities to learn and succeed. The Dubai government has implemented an inclusive education policy aimed at promoting equity and inclusivity in schools. This study aimed to investigate school leaders' understanding, implementation, and perspectives on the Dubai Inclusive Education Policy Framework (DIEPF). To gather data, a qualitative research study was conducted using semi-structured interviews with ten school leaders from private schools located in Dubai, United Arab Emirates (UAE). The findings show that school leaders have a strong understanding of the policy and deem it to be significant. The study also found evidence of effective strategies implemented by school leaders to promote inclusive education. However, there are challenges in the UAE that resonate with those worldwide such as inadequate funding, high student-teacher ratios, shortage of specialized staff, and limited training opportunities for teachers. These findings emphasize the significance of ongoing professional development and training of educators who are involved in inclusive education. Implications for practice and suggestions for future research are provided.

This study aimed to investigate the current status of the Sustainable Workplace Equality Policy (SWEP) in an emerging country—Kuwait—and how it impacts firms’ financial and market performance. The study included companies listed in the Kuwait Boursa (Boursa Kuwait is the operator of the Kuwait Stock Exchange) in the period between 2012 and 2020. A disclosure index was prepared for SWEP based on guidelines provided by a combination of various sources and standards such as the Global Reporting Initiatives (GRI) standard, S&P global corporate sustainability assessment, Dow Jones sustainability index, United Nations global compact, and KPMG sustainability reporting standards. Time series regression analysis was used to examine the study hypotheses. The analysis revealed a strong positive relationship between the SWEP disclosure and firm measures of financial performance. The results indicate that SWEP is value-relevant and affects firms’ market value, suggesting that investors should consider firms’ disclosure of the SWEP when making investment decisions. The results of the current study are of interest to several stakeholders, especially investors and policymakers. Specifically, the study is relevant to the Kuwaiti Government, which has defined a clear path for sustainable growth with the Vision 2035/New Kuwait that is aimed at transforming the country into a financial and commercial hub for the region by 2035.

Autonomous shuttles have been used as end mile solutions for smart mobility in smart cities. The urban driving conditions of smart cities with many other actors sharing the road and the presence of intersections have posed challenges to the use of autonomous shuttles. Round intersections are more challenging as it is more difficult to perceive the other vehicles in and near the intersection. Thus, this paper focuses on decision making of autonomous vehicles for handling round intersections. The round intersection is introduced first, followed by introductions of the Markov Decision Process (MDP), the Partially Observable Markov Decision Process (POMDP) and the Object Oriented Partially Observable Markov Decision Process (OOPOMDP) which are used for decision making with uncertain knowledge of the motion of the other vehicles. The Partially Observable Monte-Carlo Planning (POMCP) algorithm is used as the solution method and OOPOMDP is applied to decision making for autonomous vehicles in round intersections. Decision making is formulated first as a POMDP problem, and the penalty function is formulated and set accordingly. This is followed by improvement of decision making with policy prediction. Augmented objective state and policy-based state transition are introduced and simulations are used to demonstrate the effectiveness of the proposed method for collision free handling of round intersections by the ego vehicle.

The COVID-19 pandemic, has underscored the critical importance of sustainability across various sectors, particularly within the global economy and corporate responses to pandemic-induced challenges. Companies worldwide have grappled with unprecedented financial and operational hardships, pushing some to the brink of closure. A crucial dimension of sustainability in this context pertains to corporate financing policies. Analyzing how the pandemic has impacted these policies reveals significant insights. Government support has been instrumental in mitigating pandemic-induced disruptions, but often proved insufficient for severely affected companies. Companies, seeking financial resilience, turned to state-guaranteed lines of credit as a lifeline. Additionally, moratoriums on existing credits provided temporary relief, but long-term consequences, particularly regarding corporate indebtedness. As companies adapted financing strategies, corporate indebtedness increased. Coupled with rising interest rates in late 2022, corporate financing costs surged, emphasizing the need for sustainable financial approaches addressing both short-term crises and long-term stability. In conclusion, corporate sustainability during the ongoing COVID-19 pandemic necessitates a comprehensive approach. Governments must provide adequate support, companies should pursue sustainable financing solutions, and a careful consideration of the long-term consequences of financial policy changes is essential. Prioritizing sustainability in the corporate sector prepares businesses for future crises while safeguarding global economic stability.

In several Indonesian tropical cities, such as Makassar City, frequent flooding during the peak rainy season poses a significant challenge. This study seeks to address this issue by devising effective policies to reduce flood exposure. The main obstacle lies in accurately determining the flood inundation area. To overcome this, the study utilizes multiple satellite data sources on a cloud platform, integrating them with land use data, and DEM data, aligning these with the local government's urban land use plan and existing drainage networks. The research aims to quantify the affected area, identify the predominant inundated land cover, and assess the efficiency of Makassar's drainage system and urban land use plan. The study reveals that an uncoordinated drainage system in the Tamalanrea, Biringkanaya, and Mangala sub-districts results in severe flooding, encompassing a total area of 35.28 km². The most affected land use type is cultivation, constituting approximately 43.5% of the flooded area. Furthermore, 82.26% of the urban land use plan, covering 29.02 km², is submerged. It is imperative for the local government and stakeholders to prioritize the enhancement of drainage systems and urban land use plans, particularly in low-lying and densely populated regions

Entrepreneurship education in South Africa holds significant promise in empowering the youth and fostering economic growth. This article explores the impact of entrepreneurship education on youth empowerment, focusing on case studies of successful young entrepreneurs, evaluation of entrepreneurial skills development, and analysis of employment and economic outcomes. While effective models of entrepreneurship education emphasize experiential learning and collaboration with local businesses, resource constraints and infrastructure gaps pose challenges. Moreover, socio-cultural perceptions and gender disparities influence youth's willingness to engage in entrepreneurship, hindering inclusivity. Evaluating the long-term impact remains challenging, requiring robust monitoring and evaluation mechanisms. The article concludes with recommendations to enhance the impact of entrepreneurship education, including increasing funding, challenging stereotypes, fostering collaboration, and developing evaluation mechanisms to support South Africa's youth in realizing their entrepreneurial potential.

Globally, inequalities in educational provision are prevalent between genders, various geographical regions, and among different socio-economic backgrounds. Consequently, this study set-out to assess the level of disparity among the Federal Regional States of Ethiopia using Gini-coefficient and Lorenz curve from the statistical data of MoE. Moreover, data were collected from 656 respondents found in the sample regions. The result of the Gini-coefficient indicated that disparity in educational provision has been reduced over the past couple of decades both at primary (0.145 to 0.032) and secondary levels (0.277 to 0.126). Emerging regions are by far lagging behind the central and established regions. The sources of variation were mainly the demand-side variables, especially the economic and contextual related issues like drought and conflicts. Therefore, educational policies designed at the central level are advised to consider the strategies to bridge the existing inequalities through equitable provision of the education system to its citizen.

While the scientific community has focused on documenting environmental degradation and developing scenarios that help identify the operational margins for system Earth, less attention has been given to the mental models of decision-makers that underpin environmental policies. We suggest that global efforts to stop deforestation and biodiversity loss are failing in part due to a critical blind spot in the analysis—human agency. To address this weakness, we propose to formulate mental models and translate them into strategy games. This will increase the representation of agency in scenario development and create spaces for deliberation between different worldviews. We claim that personal transformation can be achieved through transparent democratic dialogues that identify, challenge, and respond to the human and social limitations inherent to decision-making and we present empirical examples that validate that claim. Their transformation through gaming gives decision-makers access to the experience of consciousness: “what is it like being a stakeholder?”. Such experience will help to break free of established norms in science and political processes.

The last half of the 20th century was characterized by the most impactful ecosystem changes throughout regulations and guidelines minimalizing environmental harms. Many of them emphasize the importance of enterprise sustainability for renewable energy policy. When dealing with numerous alternatives for the implementation of renewables-based policy, decision-makers need to analyze their impacts on environmental, economic, and social dimensions from a long-term perspective. The aim of this paper is to highlight a challenge to apply the multi-criteria sustainability decision-making framework (MDCA) to mainstream energy policy. The integrative framework covers an approach for the needs of analyzing factors influencing the energy technology selection. In this study, the MDCA-approach combines lifecycle-based methods, Analytical Hierarchy Process, PESTEL (Political, Economic, Social, Technological, Environment and Legal). To demonstrate the applicability and usability of the method three photovoltaic technologies are assessed. The results showed that string ribbon technology is the most sustainable along its life cycle, with a 0.503 sustainability score. The study highlighted the need to embody robust methodologies assessing sustainability-oriented technologies, not used anymore for supporting energy policies. This challenge regarding example evidence can give energy decision-makers a tool to realize their energy policy and in consequence, enhance enterprise sustainability.

Statistical management policy and system plays significant role in development of any nation as it guides the planner to analyze the gaps, design programs and allocate budget in efficient manner. Globally, design and usage of statistical management system varies relying on country specific ability and resources availability. Government of Nepal has been managing database in individual as well as thematic manner. Policy wise, thematic database is in operation based on Statistics Act 1958 and individual database is in operation based on Birth, Death and Other Personal Related Events Registration Act 1976. Though civil registration related policies have been either updated or newly formed, sectoral statistic management related policy has not been updated since its first promulgation period (1958). With no policy supporting the consolidated statistical management system, government as well as non-government agencies has been investing millions of dollars annually to collect, compile and analyze individual related data and fulfill their respective objectives. It has forced the government services and performance to be paper-based, time-consuming and tedious thus creating dis-trust among citizen each passing day. Though, formulation of legal instrument promoted digital movement and mandated shift towards e-government modality, the process has been low. Theoretically, Technology Acceptance Model (TAM) state the need of having advanced and efficient technology to be in place in current setting to improve governance, efficiency, accountability, transparency and trust. Also, the same theory state the requirement of strong willingness and motivation from the users (government, non-government and citizen) to adopt the technology based policy and system. As the integrated statistical management policy emphasizes on technology-based system or digital system, the perspectives of Technology Acceptance Model also termed as Information System Theory aid in understanding the context, conceptualizing and addressing the needs with an establishment and implementation of digital system or technology based system. This policy paper applied the Technology Acceptance Model (TAP) to examine the underlying opportunities and challenges associated with an integrated statistical management policy. With existing gaps in existing policy, system and practice alongside an overview of opportunities and challenges, this paper recommends the need of stand-alone integrated statistical management policy to consolidate sectoral as well as civil related information through single system based on recommended policy.

The evaluation was conducted to find out whether the stipulated objectives of the policy are being followed, and at the same time find out whether the envisioned results of implementing such policy system have been achieved so far. The evaluation was expected to provide an opportunity for mending shortfalls of the whole system that would affect its sustainability and usefulness.A total of 33 participants were interviewed in this study and came from the study area (Nkhotakota District Council Office). Purposive sampling was used to select the participants. All study respondents were purposively selected where respondents considered having relevant information and they were interviewed to obtain wide range of perspectives.Seven themes were identified; knowledge on policy, limited stakeholder involvement, poor HIV and AIDS programming, ethical issues, future perspective of the policy, Other Recurrent Transaction (ORT) allocation, and availability of HIV and AIDS Committee. On knowledge on policy, the sub-themes included; objectives well outlined, and poor updates on the policy. On limited stakeholder involvement, the sub-themes were; lack of ownership, ignorance of involvement, and not involved/limited involvement. On the Poor HIV and AIDS programming theme, sub-themes identified were; exclusion of activities in the District Implementation Plan (DIP) and lack of funds. There was one sub-theme on ethical issues and future perspective.We found that the Nkhotakota District Council HIV and AIDS at workplace policy is not functioning properly due to poor coordination and lack of funding. However, there are some positives identified such as existence of the coordinating committee and allocation of funds through ORT. Although the system has been functional for some years in well-established structures, lack of participation by some stakeholders, non-inclusion of HIV and AIDS activities in the DIPs underpin its sustainability

A scenario-based approach to the impacts of land use and climate change can help in identifying future policy directions. This study models the impacts of different land use and climate change scenarios on the forest ecosystems of South Korea to identify national-scale forest policy options. Climatically suitable forest areas for 1,031 climate vulnerable plant species were identified for current time and for 2050. We calculated change in species richness under four climate projections. We built forest conversion models and created four 2050 forest scenarios: (1) forest loss continues at current rates; (2) similar loss, but with conservation in areas with suitable future climates; (3) a reduction of loss by 50%; and (4) a combination of preservation and overall reduction of loss by 50%. We then crossed the forest conversion models with the climate-driven change in species richness, and categorized current forest areas into four classes to offer forest policy alternatives. By deploying the scenarios which preserve climatically suitable forests, the average species richness where forests converting to other land uses reduced significantly. We suggest conserving forests with suitable climates for biodiversity conservation and the establishment of forest plantations targeted to areas where species richness will decline based on our results.

Globally, humans are struggling with the double threat of communicable and non-communicable diseases, which are presenting new challenges to public health. Public health problems are generally studied and addressed at primary, secondary and tertiary levels. Most effective results are seen with primary interventions. Public health is becoming more aware of the importance of environment-gene interactions in the ontology of health and disease using epigenetics. Epigenetics is the study of altered gene expression without change in base pairs. Be it physical, social, behavioral, or economic factors; they all influence quality of life and health of individuals and populations. That environments are changing the human health phenotype and these changed phenotypes are heritable is of concern for the future of the human race. Knowing the causes of non-communicable human diseases using epigenetics will contribute to the development of new policies to encourage prevention using primary public health initiatives. Research and application of epigenetics shows great promise for improving population health. Continued advances in epigenetics will enhance how we understand and address the way environments are affecting the human health phenotype. For some time, health systems have been and continue to be tertiary in nature. Epigenetic changes can provide information necessary to better understand how social determinants of health can be used to build societies focused on equitable health for all people, rather than continuing to focus on treatment of diseases in the tertiary phase that leads to health disparities. Understanding mechanisms of social determinants of disease, will allow society to evolve in a health-oriented rather than a disease-oriented world. For this reason, we must enhance and apply epigenetics (physical, social, behavioral, economic) research to policy development. We will discuss how bringing social determinants together with biology can be used as new tools for public health policy.

Euler’s product formula over the primes and Euler’s zeta function equate to enshrine the Fundamental Theorem of Arithmetic that every integer > 1 is the product of a unique set of primes. The product formula has no zero, and with a domain ≤1 Euler’s zeta diverges. Dirichlet’s eta function η(s), negates alternate terms of zeta, permitting convergence when s∈C and Re(s) < 1, and its non-trivial zeros {ρ}, have a deep relationship with the distribution of the primes. The Riemann Hypothesis is that all the non-trivial zeros have Re(ρ) = 1/2. This work examines the symmetries in a partial Euler’s zeta series with a complex domain equating it to the difference between two finite vector series whose matched terms have mirror-image arguments, but whose magnitudes differ when Re(s) ≠ 1/2. Analytical continuation generates a modified eta series η_l(s), in which every l^th term is multiplied by (1-l). If the integer l is appropriately determined by the Im(s), similar paired finite vector series have a difference that closely follows η_l (s) and their terminal vectors intersect in a unique way permitting zeros only when Re(s) = 1/2. Furthermore, those vectors tracking the derivatives of the series, have a special relationship permitting zeros of the differential only when Re(s) > 1/2.

It was the aim of this study to examine whether the usage of the vaccine COXEVAC® (Ceva Santé Animale) could reduce the consumption of antibiotics in Q-fever-positive dairy farms. Additionally, the effects of other herd-level factors on the consumption of antibiotics were investigated. In this longitudinal cohort study, 36 farms with vaccination and 13 farms without vaccination participated. In all herds, Coxiella burnetii had been directly or indirectly diagnosed. To compare the treatment frequency of antibiotics between the vaccinated group and the non-vaccinated group, the consumption of antibiotics for each farm was collected using the veterinary documents about the application and delivery of antibiotics. To gather detailed information about herd data, nutrition, milking management, housing, and animal health, the farmers were interviewed with the help of a questionnaire. The results suggest that there might be an association between the vaccination against Q fever and a reduced consumption of antibiotics. Neither herd size nor milk yield level influenced the consumption of antibiotics in the study herds. Type of flooring and udder cluster disinfection while milking were associated with a lower and higher therapy frequency, respectively. Further studies are necessary to elucidate the cause-effect relationship between vaccination and the consumption of antibiotics.

In this work, we propose an approach for the autonomous navigation of mobile robots using fusion of sensor data by a Double Deep Q-Network with collision avoidance by detecting moving people via computer vision techniques. We evaluate two data fusion methods for the proposed autonomous navigation approach: Interactive and Late fusion strategy. Both are used to integrate mobile robot sensors through the following sensors: GPS, IMU and, an RGB-D camera. The proposed collision avoidance module is implemented along with the sensor fusion architecture in order to prevent the autonomous mobile robot from colliding with moving people. The simulation results indicate a significant impact on the success of completing the proposed mission by the mobile robot with the fusion of sensors, indicating a performance increase (success rate) of 27% in relation to navigation without sensor fusion. With the addition of moving people in the environment, deploying the people detection and collision avoidance security module has improved about 14% the success rate when compared to that of the autonomous navigation approach without the security module. Video was developed with robot navigation using the DDQN-Late Fusion https://www.loom.com/share/684afa6a5b0148afadc9a200ab9f3483.

Firstly, we present a more explicit formulation of the complete system $D(N)$ of representatives of Manin's symbols over $\mathbb{Q}$, which was initially given by Shimura. Then we establish a bijection between $D(M)\times D(N)$ and $D(MN)$ for $(M,N)=1$, which reveals a recursive structure between Manin's symbols of different levels. Based on Manin's complete system $\Pi (N)$ of representatives of cusps on $X_0(N)$ and Cremona's characterization of the equivalence between cusps, we establish a bijection between a subset $C(N)$ of $D(N)$ and $\Pi (N)$, and then establish a bijection between $C(M)\times C(N)$ and $C(MN)$ for $(M,N)=1$. We also provide a recursive structure for elliptical points on $X_0(N)$. Based on these recursive structures, we obtain recursive algorithms for constructing Manin symbols over $\mathbb{Q}$, cusps and elliptical points on $X_0(N)$. This gives rise to a more efficient algorithms for modular elliptic curve. As direct corollaries of these recursive structures, we present a recursive version of the genus formula and an elementary proof of formulas of the numbers of $D(N)$, cusps and elliptical points on $X_0(N)$.

Tuning fork gyroscopes (TFGs) are promising for potential high-precision applications. This work proposes and experimentally demonstrates a novel high-Q dual mass tuning fork microelectro-mechanical system (MEMS) gyroscope utilizing three-dimensional (3D) packaging techniques. Except for two symmetrically-decoupled proof masses (PM) with synchronization structures, a symmetrically-decoupled lever structure is designed to force the antiparallel, antiphase drive-mode motion and basically eliminate the low-frequency spurious modes. The thermoelastic damping (TED) and anchor loss are greatly reduced by the linearly-coupled, momentum- and torque-balanced antiphase sense mode. Besides, a novel 3D packaging technique is used to realize high Q-factors. A composite substrate encapsulation cap, fabricated by through-silicon-via (TSV) and glass-in-silicon (GIS) reflow processes, is anodically bonded to the sensing structures at wafer scales. A self-developed control circuit is adopted to realize loop control and characterize gyro-scope performances. It is shown that a high-reliability electrical connection together with a high-air-impermeability package can be fulfilled with this 3D packaging technique. Furthermore, the Q-factors of the drive and sense modes reach up to 51947 and 49249, respectively. This TFG realizes a wide measurement range of ±1800° /s and a high resolution of 0.1° /s with a scale-factor nonlinearity 720 ppm after automatic mode-matching. Besides, the long-term zero-rate output (ZRO) drift can be effectively suppressed by temperature compensation, inducing a small angle random walk (ARW) of 0.923°/√h and a low bias instability (BI) of 9.270°/h.

In this paper we present experimental results concerning Acoustic Emission (AE) recorded during cyclic compression tests on two different kinds of brittle building materials, namely concrete and basalt. The AE inter-event times were investigated through a non-extensive statistical mechanics analysis which shows that their decumulative probability distributions follow q-exponential laws. The entropic index q and the relaxation parameter q  1=Tq, obtained by fitting the experimental data, exhibit systematic changes during the various stages of the failure process, namely (q; Tq) linearly align. The Tq = 0 point corresponds to the macroscopic breakdown of the material. The slope, including its sign, of the linear alignment appears to depend on the chemical and mechanical properties of the sample. These results provide an insight on the warning signs of the incipient failure of building materials and could therefore be used in monitoring the health of existing structures such as buildings and bridges.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of corona-virus disease 19 (COVID-19) and employs angiotensin-converting enzyme 2 (ACE2) as the recep-tor. Although the expression of ACE2 is crucial for cellular entry, we found that the interaction of ACE2 with the Spike (S) protein in the same cells led to its downregulation through degradation in the lysosomal compartment via the endocytic pathway. Interestingly, the ability of the S protein from previous variants of concern (VOCs) to downregulate ACE2 was variant-dependent and correlated with disease severity. The S protein from the Omicron variant, associated with milder disease, exhibited a lower capacity to downregulate ACE2 than that of the Delta variant, which is linked to a higher risk of hospitalization. Chimeric studies between the S proteins from the Delta and Omicron variants revealed that both the receptor-binding domain (RBD) and S2 subunit played crucial roles in the reduced ACE2 downregulation activity observed in the Omicron var-iant. In contrast, three mutations (L452R/P681R/D950N) located in the RBD, S1/S2 cleavage site, and HR1 domain were identified as essential for the higher ACE2 downregulation activity ob-served in the Delta variant than that in the other VOCs. Our results suggested that dysregulation of the renin-angiotensin system due to the ACE2 downregulation activity of the S protein of SARS-CoV-2 may play a key role in the pathogenesis of COVID-19.

Several studies in computer vision have examined specular removal, which is crucial for object detection and recognition. This research has traditionally been divided into two tasks: specular highlight removal, which focuses on removing specular highlights on object surfaces, and reflection removal, which deals with specular reflections occurring on glass surfaces. In reality, however, both types of specular effects often coexist, making it a fundamental challenge that has not been adequately addressed. Recognizing the necessity of integrating specular components handled in both tasks, we constructed a Specular-Light (S-Light) DB for training single-image-based deep learning models. Moreover, considering the absence of benchmark datasets for quantitative evaluation, the Multi-Scale Normalized Cross Correlation (MS-NCC) metric, which considers the correlation between specular and diffuse components, was introduced to assess the learning outcomes.

Switched model predictive control (S-MPC) and recurrent neural network with long short-term memory (RNN-LSTM) are powerful control methods that have been extensively studied for energy management in microgrids (MGs). These methods are complementary in terms of constraint satisfaction, computational demand, adaptability, and comprehensibility, but typically one method is chosen over the other. The S-MPC method selects optimal models and control strategies dynamically based on the system’s operating mode and performance objectives. On the other hand, integration of auto-regressive (AR) with these powerful control methods improves prediction accuracy and system conditions’ adaptability. This paper compares the two approaches to control and proposes a novel algorithm called Switched Auto-regressive Neural Control (S-ANC) that combines their respective strengths. Using a control formulation equivalent to S-MPC and the same controller model for learning, the results indicate that pure RNN-LSTM cannot provide constraint satisfaction. The novel S-ANC algorithm can satisfy constraints and deliver comparable performance to MPC while enabling continuous learning. Results indicate that S-MPC optimization increases power flows within the MG, resulting in efficient utilization of energy resources. By merging the AR and LSTM, the model’s computational time decreased by nearly 47.2%. Also, this study evaluated our predictive model’s accuracy: (i) R-squared error is 0.951, indicating strong predictive ability, and (ii) mean absolute error (MAE) and mean square error (MSE) values of 0.571 indicate accurate predictions with minimal deviations from actual values.

A simulation test system for the two-dimensional (2D) fuze overload loading process was designed to address the loading issues of recoil overload and centrifugal overload in fuze safety and arming (S&amp;A) devices. By incorporating centrifuge rotation energy storage, impact acceleration simulation, and equivalent centrifugal rotation simulation, a block equipped with a fuze S&amp;A device was accelerated instantly upon being impacted by a centrifuge-driven impact hammer, simulating recoil overload loading. The impact hammer was retracted instantaneously by adopting an electromagnetic brake, which resulted in the centrifugal rotation of the block around its track, to simulate the centrifugal overload loading. The dynamic equations of the simulation test system and the equations of impact hammer motions were established, whereby the rotation speed of the centrifuge and the braking force of the electromagnetic brake were calculated and selected. A dynamic model of the collision between the impact hammer and block was established using ANSYS/LS-DYNA software for simulation analysis. The acceleration curves of the recoil overload and centrifugal overload with variations in the centrifuge speed, cushion material, and buffer thickness were obtained, which verified the feasibility of the proposed loading simulation method. 2D overload loading simulation tests were performed using the developed simulation system, and the acceleration curves of the recoil overload and centrifugal overload were measured. The test results indicated that the proposed system can accomplish 2D overload loading simulations for a recoil overload of several 10000 g and centrifugal overload of several 1000 g.

One of the most frequent brain diseases, Alzheimer's is defined by poor cognitive function brought on by the build-up of Beta Amyloid plaques and the gradual death of neurons. Glucose metabolism and the development of amyloid plaques are being studied together. Under physiologically normal circumstances, glucose is the primary substrate for the adult human brain. The prodromal phases of AD are significantly influenced by glucose hypometabolism. Hypometabolism of glucose in the brain is a clear sign of mitochondrial dysfunction and bioenergetic system impairment. By regulating energy synthesis and cell death, mitochondria play a crucial role in the functioning of cells. Increased formation of reactive oxygen species (ROS) and oxidative stress are a result of mitochondrial dysfunction, which also accelerates the development of Alzheimer's disease. For the maintenance of balance, autophagy is crucial because it selectively destroys damaged mitochondria. AD affects this route for mitochondrial breakdown. Targeting specific mitochondrial ligands by interventions along this pathway might be a useful therapeutic approach. Due to a number of biological obstacles, this method has significant limitations. As a result, many nanocarriers have been created to improve drug delivery effectiveness. All potential nanotechnology-based treatments for AD have been examined in this study, with a particular emphasis on medication delivery to the mitochondria

ABSTRACT Two years after first patients approached the emergency rooms of hospitals in Wuhan becouse of respiratory distress,thousend of SARS-CoV-2 infected persons continue to die every day worldwide.SARS-CoV-2-infected patients undergo a process of dehydration and malnutrition before they develop respiratory problems and approach the emergency room of a hospital.This is,in many cases, the consequence of high fever which causes massive loss of fluids. In addition loss of appetite, is responsible for the deficit of protein intake.Most of the virus-infected patients admitted to the emergency room are therefore hypovolemic and hypoproteinemic and suffer of respiratory distress accompanied by ground grass opacities at CT-scan of the lungs.Critically ill patients are treated following the guidelines for treatment of septic shock but with „conservative“ fluid replacement and administration of diuretics to assure sufficient hourly urine production. The combination of conservative fluid administration with reduced protein content in the enterally administered diet, together with administration of diuretics, has severe hemodynamic consequenses in mostly aged,dehydrated,critically ill patients. Many of them will develop acute kidney injury in the next 24 hours.In most of the cases, patients continue to loose weight by loosing skeletal muscle mass. Ischemic damage in the lung capillaries is responsible for the acute respiratory distreass syndrome (ARDS) and for the hallmark of autoptic findings,diffuse alveolar damage (DAD) characterized by hyaline membrane formation,fluid invasion of the alveoli recruitment of some inflammatory cells and progressive arrest of blood flow in the pulmonary vessels.The consequence is progressive congestion , increase of lung weight and progressive hypoxia (progressive severity of ARDS).Sequestration of blood in the lungs worsen hypovolemia and ischemia in different organs.This is most probably responsible for recruitment of inflammatory cells and for persistance of elevated serum levels of positive acute-phase markers and of hypoalbuminemia. Autoptic studies have been performed mostly in patients who died in the ICU after SARS-CoV-2-infection because of progessive ARDS.In those patients, tubulus epithelium necrosis in the kidney is a frequent finding as it has been the case in the first SARS-CoV-1 pandemic.In the death certification charts, many times weeks after first symptoms have started ,cardiac arrest is the cause of death after respitatory insufficiency.Replacement therapy with sufficient amount of fluid and albumin should be part of the early individualized life-saving supportive measures avoiding mechanical ventilation.

Lipid metabolism is clearly associated to Parkinson´s disease (PD). Although lipid homeostasis has been widely studied in multiple animal and cellular models as well as in blood derived from PD individuals, the cerebrospinal fluid (CSF) lipidomic profile in PD remains largely unexplored. In this study, we have characterized the CSF lipidomic imbalance between neurologically intact controls (n=10) and PD subjects (n=20). The combination of dual extraction with ultra-performance liquid chromatography-electrospray ionization quadrupole-time-of-flight mass spectrometry (UPLC-ESI-qToF-MS/MS) allowed to monitor 257 lipid species across all samples. Complementary multivariate and univariate data analysis pointed out that glycerolipids (mono-, di-, and triacylglycerides), saturated and mono/polyunsaturated fatty acids, primary fatty amides, glycerophospholipids (phosphatidylcholines, phosphatidylethanolamines), sphingolipids (ceramides, sphingomyelins), N-acylethanolamines and sterol lipids (cholesteryl esters, steroids) were significantly increased in the CSF of PD compared to control group. These results, despite the limitation of being obtained in a small population, demonstrate and extensive CSF lipid remodelling in PD, shedding new light on the deployment of CSF lipidomics as a promising tool to identify potential lipid markers as well as discriminatory lipid species between PD and other atypical parkinsonisms.

We report world record high data transmission over standard optical fiber from a single optical source. We achieve a line rate of 44.2 Terabits per second (Tb/s) employing only the C-band at 1550nm, resulting in a spectral efficiency of 10.4 bits/s/Hz. We use a new and powerful class of micro-comb called soliton crystals that exhibit robust operation and stable generation as well as a high intrinsic efficiency that, together with an extremely low spacing of 48.9 GHz enables a very high coherent data modulation format of 64 QAM. We achieve error free transmission across 75 km of standard optical fiber in the lab and over a field trial with a metropolitan optical fiber network. This work demonstrates the ability of optical micro-combs to exceed other approaches in performance for the most demanding practical optical communications applications.

In this article, the new Hermite–Hadamard type inequalities are studied via generalized s-convexity on fractal sets. These inequalities derived on fractal sets are shown to be the generalized s-convexity on fractal sets. We proved that the absolute values of the first and second derivatives for the new inequalities are the generalization of s-convexity on fractal sets.

In this article, the new Hermite–Hadamard type inequalities are studied via generalized s-convexity on fractal sets. These inequalities derived on fractal sets are shown to be the generalized s-convexity on fractal sets. We proved that the absolute values of the first and second derivatives for the new inequalities are the generalization of s-convexity on fractal sets.

The declining and aging population, as well as the downsizing of households, poses problems for the simultaneous occurrence of vacant houses and the construction of new housing units. The objective of this study was to examine countermeasures for the future occurrence of vacant houses. The relationship between population, households, vacant houses, and newly constructed housing was reviewed according to prefecture, and the occurrence of vacant houses and distribution of newly constructed housing were mapped out. The results revealed that the increase in the number of elderly single-person households is a source of vacant houses, while middle-aged single households tend to promote the construction of new housing due to the lack of housing stock. In Setagaya ward, Tokyo, one of the reasons for the increase in new housing construction may be that many of the elderly single households have old wooden detached houses facing qualitative problems. In Wakayama central city, it was inferred that old, detached houses built for households with children during an economic growth period do not meet the needs of middle-aged single households, due to factors such as age, size, and floor plan, which has promoted vacancy and new construction, resulting in a stagnation of the housing cycle.

A novel reinforcement learning deep deterministic policy gradient agent-based sliding mode control (DDPG-SMC) approach is proposed to suppress the chattering phenomenon in the attitude control for quadrotors, in the presence of external disturbances. First, the attitude dynamics model of the studied quadrotor is derived and the attitude control problem is described by formulas. Second, a sliding mode controller including its sliding mode surface and reaching law is selected for the nonlinear dynamic system, and the stability of the designed SMC system is supported by Lyapunov stability theorem. Third, a reinforcement learning (RL) agent based on deep deterministic policy gradient (DDPG) is trained to adjust the switching control gain adaptively. During the training process, the input signals of agent are the actual and desired attitude angles, and the output action is the time-varying control gain. Finally, the above trained agent is applied to the SMC as a parameter regulator, to implement the adaptive adjustment of the switching control gain related to reaching law, and the simulation results verify the robustness and effectiveness of the proposed DDPG-SMC method.

The meaning of a good social outcome in land use transport policy/planning has been relatively underdeveloped, compared to economic and environmental sustainability goals, but this is now changing. Cities are increasingly prioritizing reducing social exclusion, with the allied intent of providing all residents with equitable access to the benefits of their city. However, in jurisdictions that use cost-benefit analysis to guide government decision-making, this poses a challenge: monetization of the benefits of reducing social exclusion is poorly developed. An evaluation gap thus confronts benefit-cost based assessment of initiatives intended to reduce social exclusion, compared to initiatives directed towards societal economic and environmental goals. This is a particular problem for public transport services that primarily enable people at risk of mobility-related social exclusion to access more opportunities in their society (social transit). The benefits of reducing social exclusion associated with these services have not been monetized, so social transit initiatives are poorly placed to argue their merits against competing initiatives where benefit monetization is more advanced (e.g., mass public transport and roads). The paper summarizes Australian research that has developed monetized measures for the value of increased trip making, bridging/bonding social capital, sense of community and several conceptions of wellbeing, and of reducing neighbourhood disadvantage, as these contribute to reducing social exclusion. New Singaporean research on the value of trip making to support reduced exclusion is also presented, affirming the Australian trip values. Trip values are then used in case study examples to show they can make a material difference to the societal worth of initiatives intended to reduce exclusion. Using these trip values, and other pathway values linked to reducing social exclusion, closes or at least substantially reduces the evaluation gap confronting social goal achievement in land use transport policy and planning, strengthening the case for reducing exclusion. These values will assist jurisdictions that are seeking to provide their residents with more equitable access to the benefits of their city.

The inherent dependency of deep learning models to labeled data is a well-known problem and one of the barriers that slows down the integration of such methods into different fields of applied sciences and engineering, in which experimental and numerical methods can easily generate a colossal amount of unlabeled data. This paper proposes an unsupervised domain adaptation methodology that mimics the peer review process to label new observations in a different domain from the training set. The approach evaluates the validity of a hypothesis using domain knowledge acquired from the training set through a similarity analysis, exploring the projected feature space to examine the class centroid shifts. The methodology is tested on a binary classification problem, where synthetic images of cubes and cylinders in different orientations are generated. The methodology improves the accuracy of the object classifier from 60% to around 90% in the case of a domain shift in physical feature space without human labeling.

The most potential renewable energy source for global emissions reductions is green hydrogen production. Iraq is looking into several sources of alternative energy to lessen its dependency on fossil fuels and to considerably cut its carbon dioxide emissions. This research examined the conceptual framework for the production and consumption of green hydrogen in Iraq. On the basis of accessible official and public data from government agencies, the potential capabilities of renewable energy resources are assessed, and certain fair assumptions are also established for a full study and evaluation of a possible hydrogen production in the country. The data presented here demonstrate conclusively that the contributions of renewable energy to the production of green hydrogen are substantial, giving the country prominence in the area of green hydrogen production. A pathway for a green hydrogen economy in the country by 2050 is proposed by this research based on its analysis. It is distributed in three stages: green hydrogen as a fuel for industry; using green hydrogen for fuel cells; and hydrogen commercialization. On the other hand, the research found a number of challenges to the implementation of a green hydrogen production that can be used in Iraq and other developing countries, including technological, economic, and social problems in addition to the related policy consequences.

This paper presents the behavior of decision makers, the possible choices and the strategies 1 resulting from the uncertainties related to the integration of renewable energies. Its uncertainties 2 are the risks associated with the volatility of renewable sources, the dynamics of energy production 3 as well as the planning and operation of the electricity grid. The goal is to model the risk-averse 4 decision-maker’s behavior and the choice of integrating renewable energies into the electrical system. 5 Following a bibliographic approach, we expose a methodology to model the decision-maker’s 6 behavior(risk aversion and predilection for risk) to risk taking. The risk-averse decision maker may 7 adopt nonlinear utility functions. Risk aversion is a behavior that reflects the desire to avoid risk 8 decisions and thus reduces the risk of adverse consequences. A decision support tool is provided to 9 the decision-maker to choose a best-fit strategy based on his preferences. The rational and risk-averse 10 decision-maker would seek to maximize a concave utility function instead of seeking to minimize its 11 cost. Taste or aversion to risk can be modeled by a thematic function of utility.

With increased participation in telework expected to continue, to support emerging hybrid work models in the aftermath of the Covid-19, it is important to consider the long-term impact this practice could have on sustainability outcomes. This paper describes a systematic review of 113 academic journal articles and identifies associations between telework and sustainability, explored by previous researchers. Those associations were categorized and discussed, based on their contributions to different United Nations Social Development Goals. Most of research was found to focus on countries classified as having a very high human development index status, and regions with a low, medium or high human development index, largely ignored. The SWOT matrix technique was used to illustrate the strengths and weaknesses identified in the current literature as well as threats and opportunities for future work. This can help to ensure policy coherence and that strategies to promote one outcome, such as economic productivity improvements, does not undermine another, such as improved health. Practical implications and potential research opportunities were identified across a range of SDG impact areas, including good health and well-being, gender equality, reduced inequality, climate mitigation, sustainable cities and resilient communities. On the whole, our impression is that increased rates of telework present an important opportunity to improve sustainability outcomes, however, it will be important that integrated and holistic policy is developed that mitigates key risks.

Motorcycles can be considered a new form of smart vehicle when taking into account their small and modern structure and due to the fact that nowadays they are used in the new role of ambu-lance to rapidly reach emergency patients in large cities with traffic congestion. However, there is no study regarding the measuring of access time for motorcycle ambulances in large cities of Thailand. Therefore, this study aims to compare access times to patients between motorcycle ambulances and conventional ambulances, including analysis of the use of AED installed on motorcycle ambulances to contribute to the sustainable development of public health policies. In two hundred and seventy-one operations, it was found that the times from dispatch to vehicle (ambulance and motorlance) being en route and times from the 1669 center (center for com-mand-and-control EMS in Thailand) call receipt to arrival on scene (response time) of motorcycle ambulances was shorter than that of a conventional ambulance and the use of AED on a motor-cycle ambulance can increase the chances of survival for patients with cardiac arrest outside the hospital in public places where AEDs are not available and in all cases where access to an AED was less than eight minutes.

There exists a compelling need to better understand the temporal dynamics of public sentiment towards COVID-19 vaccines in the US on a national and state-wise level for facilitating appropriate public policy applications. Our analysis of social media data from early February of 2021 and late March of 2021 shows that in spite of overall strength of positive sentiment, and increasing numbers of Americans being fully vaccinated, negative sentiment about COVID-19 vaccines still persists among sections of people who are hesitant towards the vaccine. In this study, we performed sentiment analytics on vaccine tweets, studied changes in public sentiment over time, conducted vaccination sentiment validation using actual vaccination data from the US CDC and Household Pulse Survey (HPS), explored influence of maturity of Twitter user-accounts and generated geographic mapping of sentiments by location of Twitter users. Furthermore, we leverage the emotion polarity based Public Sentiment Scenarios (PSS) framework which was developed for COVID-19 sentiment analytics, to systematically analyze directions for public policy processes to potentially improve the administration of vaccines. Application of the PSS framework provides important time sensitive insights for state and federal government agencies and associated organizations to better implement public policy processes for healthcare management, communication, transparency, motivation and societal operational policies such as social distancing. These insights are expected to contribute to processes that can expedite the vaccination program and move closer to the cherished herd immunity goal.

The COVID-19 pandemic is placing unprecedented stress on healthcare systems around the world. Although Radiation Oncology Departments are not at the frontline of fighting this infectious disease, it is important to implement COVID-19 policies to reduce risk of staff and patient exposure, and to limit the risk of department shutdown or downtime. This brief report describes the policy implemented at George Washington University Radiation Oncology to manage the risks of COVID-19. This includes a General Statement related to the priorities of the Radiation Oncology department, a screening procedure for new and follow-up patients, management policies for critical and non-critical patients with COVID-19 or under quarantine, a policy for the management of patients currently under treatment who are diagnosed or placed in quarantine, a clinical escalation action plan, guidelines for staff meetings and travel, and procedure management. This policy was implemented at George Washington University Radiation Oncology after the first case of COVID-19 was reported in Washington DC on March 7, 2020.

An adequate number of waste management facilities is the key element to meet circular economy goals. Using empirical data taken from official sources the research framework bases on an econometric model to compare the elasticity of cost on quantity of different alternatives such as waste-to-energy facilities, mechanical biological facilities and landfills impact on waste management cost. Results suggest that both waste-to-energy facilities (-0.278%) and landfills (-0.38%) concur to lower the cost while the higher the percentage of waste sent to mechanical biological treatment facilities, the higher the cost (0.788%). This figure deserves to be examined in more details as such facilities represent an intermediary step in the chain which efficiency depends on the industrial organization of the chain.

Energy and Environment Tax is used globally as a means of environment policy. Energy and Environment tax plays an important role as a driving force for the conversion to environmentally friendly energy. The basic tax principles considered in the design of energy and environmental taxation increases the efficiency of policy instruments. The purpose of this study is to evaluate South Korea’s energy and environmental taxation based on tax principles, namely, equity, efficiency, simplicity, flexibility, and accountability and to suggest directions for improvement. This study applied a methodology that provides policy implications, such as reviewing existing literature and comparing energy and environmental taxes. Results of this study show that South Korea’s energy and environmental taxation is negative in terms of equity, simplicity, and accountability. South Korea’s current energy and environmental tax is regressive to income classes and complex tax structures and it does not objectively measure the impact of energy and environmental taxation. However, energy and environmental taxation is evaluated positively in terms of efficiency and flexibility because it meets the greenhouse gas reduction policy and operates a flexible tax rate. The results of this analysis provide policy implications for reorganizing South Korea’s energy and environmental taxation

In 2014, the International Union for Conservation of Nature adopted the Red List of Ecosystems (IUCN RLE) criteria as the global standard for assessing risks to terrestrial, marine, and freshwater ecosystems. Identifying and quantifying the impacts of biodiversity assessments on the status of nature is key to justifying continued investment in assessments and enabling strategic planning to maximize future impact. In this policy perspective, we use an established impact evaluation framework to identify the impacts of the IUCN RLE since its inception. To date, 1,397 ecosystem units in 100 countries have been assessed following the IUCN RLE protocol. Systematic assessments are complete or underway in more than 25 countries and two continental regions (the Americas and Europe). Countries with established ecosystem red lists have already used them to inform legislation, land-use planning, protected area expansion, monitoring and reporting, and ecosystem management. IUCN RLE indices based on systematic assessments have high potential to inform global biodiversity reporting for the Aichi Targets and the United Nations Sustainable Development Goals. Expanding the coverage of IUCN RLE assessments, building capacity to undertake them, and establishing stronger policy instruments to manage red-listed ecosystems will be key to maximizing conservation impacts over the coming decades.

Urbanization and industrialization processes in Mongolia have been significant and rapid for the last half-century. During this period, changes in political and economic systems, growth in the population, and the occasional harsh climate conditions were subject to fluctuations in the natural resource usage. The total Ecological Footprint (EF) in Mongolia has increased from 6.8 million global hectares (gha) in 1961 to 14.6 million gha in 2012. However, Biocapacity (BC) has decreased from 50.6 million gha in 1961 to 39.0 million gha in 2012. The study shows that grazing land Footprint and carbon uptake land Footprint are the two major contributors of the recent intensified use of biological resources. To ensure stable economic development and sustainable use of natural resources, environmental planning is required to consider both the population’s pressure on the environment and the ecosystem’s regeneration capacity, simultaneously. We have proposed a few possible strategies for sustainable utilization of grazing land Footprint and carbon Footprint. For grazing land Footprint, efficient management of both herding practice and number of animals should be considered. In case of carbon Footprint, it is estimated that with the improved combustion efficiencies of coal-based power plants and the maximum use of renewable energy, carbon dioxide (CO₂) emissions in Mongolia can be reduced up to 30% compared to the base line business as usual case in 2030.

China combines green energy and industrial policy in its power market reform with various policy initiatives, including price support scheme for electricity from renewable sources and subsidies in the push for broader use of greener energy. This study focuses on the impacts of power market reform on the stock price volatility of listed power companies: 1) we use the Iterative Cumulative Sums of Squares (ICSS) algorithm to identify structural break points in stock prices; 2) we analyze the characteristics of stock price volatility based on the GARCH model; 3) we report the impact of power regulation on stock price fluctuations based on the Autoregressive Distributed Lag (ARDL) model. The result suggests three structural breaks in China’s power stock price volatility were related to the promulgation of power market reform policies. We find that industrial policies promote the reduction of power stock price fluctuations and its impact on power stock price volatility is consistent in the long run. However, our study also indicates the recent policies related to renewable energy do not have a very significant impact on the power stock market.

Arctic feedbacks will accelerate climate change and could jeopardise mitigation efforts. The permafrost carbon feedback releases carbon to the atmosphere from thawing permafrost and the sea ice albedo feedback increases solar absorption in the Arctic Ocean. A constant positive albedo feedback and zero permafrost feedback have been used in nearly all climate policy studies to date, while observations and models show that the permafrost feedback is significant and that both feedbacks are nonlinear. Using novel dynamic emulators in the integrated assessment model PAGE-ICE, we investigate nonlinear interactions of the two feedbacks with the climate and economy under a range of climate scenarios consistent with the Paris Agreement. The permafrost feedback interacts with the land and ocean carbon uptake processes, and the albedo feedback evolves through a sequence of nonlinear transitions associated with the loss of Arctic sea ice in different months of the year. The US’s withdrawal from the current national pledges could increase the total discounted economic impact of the two Arctic feedbacks until 2300 by $25 trillion, reaching nearly $120 trillion, while meeting the 1.5 °C and 2 °C targets will reduce the impact by an order of magnitude.

. Manufacturers are increasingly adopting mixed-flow manufacturing models to meet the growing customized, diverse, and dynamic customer demand. In such an environment, material distribution scheduling optimization is vital for smooth operations and is integral to production management. However, manufacturers frequently encounter problems like disordered and delayed material distribution. Traditional scheduling methods suffer from problems like inadequate transparency, delayed decision directives, and suboptimal results, impacting performance. To this end, this study proposes a dynamic material distribution scheduling optimization model and strategy based on digital twin (DT) to address these problems. Firstly, we introduce workstation satisfaction and establish a material distribution path optimization model minimizing total distribution cost while maximizing workstation satisfaction. Subsequently, we present a cloud-edge computing-based decision framework and explain the DT-based material distribution system's components and operation. Furthermore, a dynamic material distribution scheduling optimization mechanism based on DT is designed. By incorporating a savings method and incentive, penalty strategies, improvements are made to the path node selection probabilities and the information pheromone update rules of the traditional ant colony optimization (ACO) algorithm. Finally, a numerical case study, using real data from collaborating enterprises, validates the proposed algorithm and strategy. This research offers valuable insights into logistics management and algorithm design in smart manufacturing environments.

Epithelial-mesenchymal transition (EMT) networks are essential in acquiring the drug resistance and cancer malignant features in cancer stem cells (CSCs). In this regard, gene expression profiles in diffuse- and intestinal-type gastric cancer (GC) have been analyzed to reveal the network pathways in EMT and CSCs, since the diffuse-type GC has much more mesenchymal features than intestinal-type GC that has the intestinal features. The study results revealed that the activation state of several canonical pathways related to cell cycle regulation was altered. The canonical pathway on Cell cycle: G1/S checkpoint regulation was activated in diffuse-type GC, and canonical pathways on Cell cycle control of chromosomal replication and Cyclins and cell cycle regulation were activated in intestinal-type GC. Canonical pathway related to Role of BRCA1 in DNA damage response was activated in intestinal-type GC, where BRCA1, which is related to G1/S phase transition was up-regulated in intestinal-type GC. Several microRNAs (miRNAs), including mir-10, mir-17, mir-19, mir-194, mir-224, mir-25, mir-34, mir-451, and mir-605, were identified to have direct relationships of RNA-RNA interaction in Cell cycle: G1/S checkpoint regulation pathway. Additionally, cell cycle regulation may be altered in EMT conditions. The alterations in activation states of the pathways related to cell cycle regulation in diffuse- and intestinal-type GC would indicate the significance of cell cycle regulation in EMT.

Epithelial-mesenchymal transition (EMT) plays an important role in the acquisition of cancer stem cell (CSC) feature and drug resistance, which are the main hallmarks of cancer malignancy. Although previous findings have shown that several signaling pathways are activated in cancer progression, the precise mechanism of signaling pathways in EMT and CSCs are not fully understood. In this study, we focused on the intestinal and diffuse-type gastric cancer (GC), and analyzed the gene expression of public RNAseq data to understand the molecular pathway regulation in different subtypes of gastric cancer. Network pathway analysis was performed by Ingenuity Pathway Analysis (IPA). Total 2815 probe set IDs were significantly different between intestinal- and diffuse-type GC data in cBioPortal Cancer Genomics. The 10 genes including male-specific lethal 3 homolog (Drosophila) pseudogene 1 (MSL3P1), CDC28 protein kinase regulatory subunit 1B (CKS1B), DEAD-box helicase 27 (DDX27), golgi to ER traffic protein 4 (GET4), chromosome segregation 1 like (CSE1L), translocase of outer mitochondrial membrane 34 (TOMM34), YTH N6-methyladenosine RNA binding protein 1 (YTHDF1), ribonucleic acid export 1 (RAE1), par-6 family cell polarity regulator beta (PARD6B), and MRG domain binding protein (MRGBP) were found to have difference in gene expression in intestinal- and diffuse-type GC. Total 463 direct relationships with 3 molecules (MYC, NTRK1, UBE2M) were found in the biomarker-filtered network generated by network pathway analysis. The networks and features in intestinal- and diffuse-type GC have been investigated and profiled in bioinformatics. Our results revealed the signaling pathways networks in intestinal- and diffuse-type GC, bringing new light for the elucidation of drug resistance mechanisms in CSCs.

The recently discovered Gaia BH1 binary system, a Sun-like star and a dark object (presumably a black hole), may significantly change our understanding of the population of low-q binaries. The paper presents the components mass ratio distributions of binary systems of different observational classes. They all demonstrate a significant shortage of low-q systems. It is shown that this shortage can be filled with the help of search and study of objects like Gaia BH1.

Reinforcement learning (RL) is an extensively applied control method for the purpose of designing intelligent control systems to achieve high accuracy as well as better performance. In the present article, the PID controller is considered as the main control strategy for brushless DC (BLDC) motor speed control. For better performance, the fuzzy Q-learning (FQL) method as a reinforcement learning approach is proposed to adjust the PID coefficients. A comparison with the adaptive PID (APID) controller is also performed for the superiority of the proposed method, and the findings demonstrate the reduction of the error of the proposed method and elimination of the overshoot for controlling the motor speed. MATLAB/SIMULINK has been used for modeling, simulation, and control design of the BLDC motor.

A second order rational difference equation $$x_{n+1}=px_{n}+\frac{q}{x_{n-1}^2}$$ with the parameters $p$ and $q$ which lies in $(0,1)$, is studied. The dynamics of the equilibrium is characterized through the trichotomy of the parameter $p<\frac{1}{2}$, $p=\frac{1}{2}$ and $p>\frac{1}{2}$. It is found that there is no periodic solution of period $2$ and $3$ but there exists periodic solutions with only periodic solution $5$ and $10$ are achieved computationally.

The proliferation of mobile and IoT devices, coupled with the advances in the wireless communication capabilities of these devices, have urged the need for novel communication paradigms for such heterogeneous hybrid networks. Researchers have proposed opportunistic routing as a means to leverage the potentials offered by such heterogeneous networks. While several proposals for multiple opportunistic routing protocols exist, only a few have explored fuzzy logic to evaluate wireless links status in the network to construct stable and faster paths towards the destinations. We propose FQ-AGO, a novel Fuzzy Logic Q-learning Based Asymmetric Link Aware and Geographic Opportunistic Routing scheme that leverages the presence of long-range transmission links to assign forwarding candidates towards a given destination. The proposed routing scheme utilizes fuzzy logic to evaluate whether a wireless link is useful or not by capturing multiple network metrics, the available bandwidth, link quality, node transmission power, and distance progress. Based on the fuzzy logic evaluation, the proposed routing scheme employs a Q-learning algorithm to select the best candidate set toward the destination. We implement FQ-AGO on the NS-3 simulator and compare the performance of the proposed routing scheme with three other relevant protocols: AODV, DSDV, and GOR. For precise analysis, we consider various network metrics to compare the performance of the routing protocols. Our simulation result validates our analysis and demonstrates remarkable performance improvements in terms of total network throughput, packet delivery ration, and end-to-end delay.

Soft-Core architecture for Analogue to Digital Converter (ADC) sampling is useful for mixed signal applications. Soft-core architecture for cutting edge odd or even ADC sampling with interface to block RAM memory has not been found. Soft-core architecture as a concept has become popular due to the advantage of customization for different applications as compared to general-core architecture suited for single application. The latest generation of piece wise sampling is odd sampling and was introduced in the second decade of the 20th century. Odd and even order sampling techniques are analogue in nature driven by a tuned (tuned for odd or even) mixer. This paper proposes a third-generation piece wise sampling with soft-core architecture that enables an option to select both odd and even while interfacing to memory mapping. The proposed odd/even has superior SNR performance of 6 dB as compared to existing architecture such as Mod-∆ which recorded worst performance of 18 dB. Advances in soft-core technology have allowed a niche odd/even switching field to be identified and studied, the study has also been extended to include memory architecture.

The viewpoint and reaction of a country towards climate change are shaped by its political, cultural, and scientific backgrounds, in addition to the distinct characteristics of its evolving climate and the anticipated and actual consequences of the phenomenon in the times ahead. A region's climate has a significant impact on how water is managed and used, mostly in the primary sector (agroforestry systems, livestock, and agriculture), and both the distribution of ecosystem types and the amount and spreading of species on Earth. As a result, the environment and agricultural practices are affected by climate, so evaluating both distribution and evolution is extremely pertinent. Towards this aim, the climate distribution and evolution in the S. Francisco River basin (SFRB) is assessed in three periods (1970−2000, 1981−2022) in the past and 20412060 in the future from an ensemble of GCMs under two SSPs (Shared Socioeconomic Pathways), SSP2-4.5 and SSP5-8.5. The Köppen-Geiger (KG) climate classification system is analyzed, and climate change impacts are inferred for this watershed located in central-eastern Brazil, covering an area equivalent to 8% of the country. Results predict the disappearance of the hot-summer (Csa) and warm-summer (Csb) Mediterranean climates, and a reduction/increase in the tropical savanna with dry winter (Aw)/dry summer (As). A striking increase in the semi-arid hot (BSh-steppe) climate is predicted with a higher percentage (10%) under SSP5-8.5. The Source and the mouth of SFRB are projected to endure the major impacts of climate change that is followed by a predicted increase/decrease in temperature/precipitation. Future freshwater resource availability, and quality for human use will all be impacted. Consequences on ecosystems, agricultural and for the socioeconomic sectors within the SFRB might deepen the current contrasts between regions, urban and rural areas, and even between population groups, thus translating to a larger extent, the inequality that still characterizes Brazilian society. Maps depicting land use and cover changes in the São Francisco River basin from 1985 to 2022 highlight tendencies such as urbanization, agricultural expansion, deforestation, and changes in shrubland and water bodies. Urban areas fluctuated slightly, while cropland significantly increased from 33.57% to 45.45%, and forest areas decreased from 3.88% to 3.50%. Socioeconomic data reveals disparities among municipalities: 74.46% with medium Human Development Index (HDI), 0.59% with very high HDI, and 9.11% with low HDI. Most municipalities have a Gross Domestic Product (GDP) per capita below US$ 6,000. Population distribution maps show a predominance of small to medium-sized urban and rural communities, reflecting the basin's dispersed demographic and economic profile. To build routes towards a shared sustainable goal—namely, to adapt and reduce the expected climate change impacts in SFRB—it is imperative that integrated measures be conducted with the cooperation of stakeholders, local population, and decision-makers.

The intricate mechanisms of the immune response elicited by vaccines and the interplay between the immune system and the central nervous system (CNS) are poorly understood. This review explores these mechanisms, emphasizing the interplay between the immune system and the central nervous system (CNS). A critical aspect is the examination of how vaccine-induced immune responses can interact with the CNS, influencing neuroinflammation and neuroimmune interactions. Furthermore, the link between vaccination and persistent symptoms observed in long-COVID patients is discussed. Vaccination initiates a complex cascade of events, starting with the production of specific proteins, such as S1/S2 spike proteins, leading to robust immune activation in the axillary lymph nodes. The role of macrophages and antigen-presenting cells (APCs) in cytokine production, antigen presentation, and the stimulation of B and T cells highlights the sophistication of the adaptive immune response. The migration of immune cell-derived exosomes to the brain plays a dynamic role in CNS inflammation, neurodegenerative processes and long COVID. On the other hand, the prolonged presence of viral and vaccine-derived spike proteins may contribute to the complex pathophysiology of Long-COVID, shedding light on the delicate balance between beneficial immune responses and possible adverse neurological outcomes of vaccination. It is worth rigorous monitoring and further research to understand the mechanisms of neuroinflammation and the persistence of spike proteins and their long-term effects on the brain, emphasising the importance of a nuanced approach to vaccine safety and efficacy in the context of COVID-19 and beyond.Principio del formulario

A significantly reduced stress concentration effect and a stable deformation behavior are exhibited by the arc-like S-shaped auxetic structure. Analytical works beyond the bar and hinge method to capture structural effects, such as bending, shearing, etc., in the S-structure are scarce in the literature. The deformation pattern of the S-structure is dominated by bending and shearing within the linear elastic region. In this work, Timoshenko beam theory is used to derive closed-form expressions for overall elastic modulus and Poisson’s ratio. This agrees well with the results of finite element simulations. An adjusted R-square value of over 0.99 and almost 0.82 is obtained for elastic modulus and Poisson’s ratio, respectively. From parametric studies, it’s established that under quasi-static transverse load, strut thickness and the angle `α’ are the most important parameters for controlling elastic modulus, specific energy absorption, negative Poisson’s ratio (NPR) effect, and relative density of the entire auxetic structure. Also, it’s found that energy absorption and elastic modulus increase together. Interestingly, the elastic modulus of the structure under transverse load lies in the range from 3 MPa to 250 MPa, which means this structure is compliant enough and can be used in cushioning, packaging, soft robotics applications, etc.

The period from 2019 to 2021 witnessed an enduring and severe drought that impacted southeast South America. Initially characterized as a meteorological drought, its influence later extended across the entire hydrological cycle. This paper explores the application of the S-TRACK method to monitor and characterize the 2019/21 drought in Southern Brazil (SB) and Southeast Brazil (SEB). Monthly precipitation data from reanalyses and satellites, alongside the Standardized Precipitation Index (SPI) for drought quantification, are utilized. Precipitation datasets, validated against rain gauge records, highlight ERA-5 and CHIRPS as having the highest correlation in both SB and SEB, with PERSIANN exhibiting a moderate correlation. The utilization of the S-TRACK method for spatial drought tracking revealed the temporal dynamics of the drought events, with three significant episodes occurring in 2020/2021. Initially, the onset of the drought was observed in the SB region, characterized by intensities ranging from moderate to extreme. Subsequently, the drought extended northward, reaching its maximum intensity at lower latitudes within the SEB region before either dissipating or experiencing a reduction in both its spatial extent and intensity. The prolonged presence of drought-affected areas in the same region over an extended period contributed significantly to the exacerbation of drought severity, particularly during the March to May trimester.

Disorder of S-adenosylhomocysteine hydrolase (AHCY) activity leads to the potentially lethal rare disease AHCY deficiency, first described in 2004 by Baric and co-workers [1]. In order to shed new light on molecular aspects of the disease, in particular changes at transcriptome level, we enabled knock-down of AHCY expression in model systems such as the colon cancer cell line SW480 to simulate the environment occurring in AHCY deficiency patients. Further, we per-formed deep sequencing of mRNA, followed by differential expression and molecular pathway analysis. Fifteen differentially expressed networks were identified, and interestingly, we found a predicted effect of AHCY down-regulation on the expression of the Lymphoidphoid enhanc-er-binding factor 1 (LEF1) gene, indicating changes in the TCF4/LEF1 complex. LEF1, a member of the T-cell Factor (TCF)/LEF1 family of high-mobility group transcription factors, is a down-stream mediator of the Wnt/β-catenin signaling pathway [2]. LEF1 is essential in stem cell maintenance, and especially in its role in epithelial-mesenchymal transition (EMT). Western blot analysis of LEF1 protein expression confirmed our transcriptomic data predictions and revealed significantly increased LEF1 protein in AHCY- deficient cells, providing a novel link between AHCY and cancer cell phenotype.

Background: Alzheimer's disease causes great changes, with the prefrontal cortex be-ing frequently damaged zones, affecting physical and cognitive behavioural and compromising autonomy and quality of life. Objective: To evaluate the effectiveness of feedback-based tech-nology on the improvement of physical-cognitive capacities in Alzheimer. Methods: Forty pa-tients with Alzheimer were recruited from the Santa Elena Alzheimer's Association, Seville, of which 15 ended up being pilot participants, divided randomly into controls (8) and experi-mental (7). They were evaluated with: Cognitive Mini-Examination Scale, Oddball Test and At-tention Network, Berg Scale, Tinetti, Timed up and Go and Geriatric Deterioration Scale. The experimental group was treated with feedback-based technology under the supervision of physiotherapists, during 16 thirty-minute sessions, twice a week. The control group performed their usual care. Result: A significant improvement was observed in the experimental group (Cognitive Mini-Examination and Tinetti). In the group of control, a worsening of physical and motor skills was evidenced because of the degenerative disease. Discussion/Conclusion: This treatment could be a strategy to keep the patient in early stages for longer, and improve quali-ty of life delaying dependency. It creates intergenerational bonds and use at home to promote treatment adherence.

The Eucalyptus genus is the most planted forest crop in the world, with Brazil being one of the countries with the greatest productive potential. However, the occurrence of weeds can cause losses in productivity. Chemical control is widely used, but the efficiency of herbicides depends on factors such as the presence of straw in the soil and the occurrence of rainfall. Due to the scarcity of results regarding the interaction between herbicide, straw, and water depth in the forest sector, the objective of this study is to evaluate the efficiency of S-metolachlor + glyphosate in the control of grasses in different densities of eucalyptus straw and with simulated rain after the application of the product. The experiment was conducted in DBC, factorial 3×3×2, with four replications. The first factor represented 0, 50 and 100% of the commercial dose of S-metolachlor + glyphosate, the second 0, 5, and 10 ton ha-2 of straw, and the third 25 and 50mm of water depth applied in soil with a mix of grasses previously sowed. The rainfall simulation was performed 24 hours after herbicide application on each straw volume. The fresh mass of the aerial part of the grasses was collected 43 days after sowing and dried in an oven to determine the dry mass. Visual analyzes of the percentage of control were performed with scales ranging from 0 to 100, where 0 represents no control and 100 efficient control. The fresh and dry mass and the grasses' dry mass/water ratio decreased with increasing herbicide dosage and straw density. The dosage of 2.12 + 1.59 kg i.a. ha-1 of S-metolachlor + glyphosate resulted in greater control of grasses, and the treatments without straw and with the application of the herbicide had the highest percentages of control. Applying different water depths (25 mm or 50 mm) did not influence the control. Despite the control of grasses, the efficiency of the herbicide mixture was affected by the presence of vegetation cover.

Nanoporous carbons were prepared by chemical and physical activation from mangosteen peel-derived chars. The removal of atrazine was studied due to the bifunctionality of the N-groups. Pseudo-first-order, pseudo-second order and intraparticle pore diffusion kinetic models were analyzed. Adsorption isotherms were also analyzed according to Langmuir and Freundlich models. Results obtained were compared against two commercial activated carbons with comparable surface chemistry and porosimetry. The highest uptake was found for the carbons with higher content of basic surface groups. The role of the oxygen-containing groups on the removal of atrazine was estimated experimentally by the surface density. Results were compared with the adsorption energy of atrazine theoretically estimated on pristine and functionalized graphene with different oxygen-groups using periodic DFT methods. The energy of adsorption follows the same trend observed experimentally, namely the more basic the pH the more favored is the adsorption of atrazine. Micropores play an important role in the uptake of atrazine at low concentration but the presence of mesoporous is also required to inhibit the pore mass diffusion limitations. The present work contributes to the understanding of the interactions between triazine-based pollutants and the surface functional groups on nanoporous carbons in the liquid-solid interface.

This article presents the integration of lean 6S methodologies and hazard analysis and critical control points (HACCP) in the food production sector. Through the study, it is seen that non-food industrial production is not very different from that of food and, in many cases, it assimilates protocols and ideas that are already working in the food industry; Such is the case of risk analysis, critical control points or hygiene, which are part of the food production protocol and, increasingly, of the industry in general. After the integrative analysis, the article proposes a common lean 6S - HACCP model, which can be used both in food production and in non-food industrial production.

Advertising is a very important tool in influencing the customer´s buying behaviour. However, customers tend to have various levels of understanding and decoding advertising messages. Even though children do not have purchasing power themselves, they still create a key customer segment that can influence the purchase decision of the whole family. The paper focuses on how media usage by children and their attitudes towards advertisements determines their buying behavior. We analyze the development of their advertising literacy and the most important predictors of this development. The empirical study was carried out by designing a questionnaire which was filled by Slovak children between the age of 11 and 15. We evaluated the impact of advertising and the degree of influence of the selected types of advertising media on children's consumer behavior. We also evaluated the degree of the disruptive effect of the selected types of advertising media on children and the perception of a selected medium within gender. We identified the most and the least influential type of media and we found out that there is no significant difference within gender in the case of advertising media perception by children. According to the results, we can state that children´s buying behaviour is mostly influenced by advertising on social media platforms. Therefore, the study recommends for marketers also take into account children as consumers when they employ an advertising strategy on social media.

During the night between 9 and 10 September 2017, multiple flash floods associated to a heavy-precipitation event affected the town of Livorno, located in Tuscany, Italy. Accumulated precipitation exceeding 200 mm in two hours, associated with a return period higher than 200 years, caused all the largest streams of the Livorno municipality to flood several areas of the town. We used the limited-area Weather Research and Forecasting (WRF) model, in a convection-permitting setup, to reconstruct the extreme event leading to the flash floods. We evaluated possible forecasting improvements emerging from the assimilation of local ground stations and X- and S-band radar data into the WRF, using the configuration operational at the meteorological center of Tuscany region (LaMMA) at the time of the event. Simulations were verified against weather station observations, through an innovative method aimed at disentangling the positioning and intensity errors of precipitation forecasts. By providing more accurate descriptions of the low-level flow and a better assessment of the atmospheric water vapour, the results demonstrate that assimilating radar data improved the quantitative precipitation forecasts.

Adaptive Sliceable-Bandwidth Variable Transceivers (S-BVTs) are key enabler for future optical networks. In particular, those based on Discrete MultiTone (DMT) modulation and Direct Detection (DD) can be considered a flexible solution suitable to address the cost efficiency requirement of optical metro networks. In this paper, we propose to use this cost-effective S-BVT option/implementation in optical metro networks adopting switching nodes based on Semiconductor Optical Amplifier (SOA) technology. Bit loading (BL) and power loading (PL) algorithms are applied to the Digital Signal Processing (DSP) modules, to maximize the performance and/or the capacity as well as enhance the flexibility and adaptability of the system. Our analysis considers switching nodes based on SOAs with and without filtering elements and fiber spans of 25 km. We present the results up to 100 km, with and without SOA-based nodes. Firstly, we analyze the adaptive BVT transmission using the Margin Adaptive (MA) BL/PL algorithm at a fixed bit rate of 28 Gb/s. The possibility of controlling the SOAs current is a key factor to face the transmission impairments due to the fiber and the filtering elements. We also analyze the system considering Rate Adaptive (RA) transmission at a fixed target BER of 3.8·10⁻³, showing that a maximum capacity above 34 Gb/s can be achieved for a single span of 25 km. Although the cascading of filtering elements still constitutes a limiting factor, we show that an improvement of the net bit rate performance can be obtained thanks to the combined use of S-BVT and SOA technology at the switching nodes, resulting in a promising approach for designing future optical metro networks.

This paper focuses on environmental policies for mitigating the impacts of climate change on the Taj Mahal, an iconic structure built on the banks of the Yamuna River from 1632 to 1653 with a blend of Persian and Indian architectural styles. The Taj Mahal is threatened by damage caused by climate change, including air pollution resulting in acid rain and floods that lead to erosion and discoloration of the main marble material of the Taj Mahal. This study employs a Systematic Literature Review (SLR) of peer-reviewed journal articles with a primary focus on environmental policy, the impacts of climate change, and the preventive measures undertaken by the Indian government. Based on the analysis of 270 papers, it is concluded that out of the total, 30 papers specifically address objectives relevant to this research. The study period spans from 2014 to 2024. The research findings reveal that air pollution has a significantly adverse impact on the Taj Mahal. Furthermore, nine policies are generally identified from the journal literature review aimed at preserving and protecting the Taj Mahal from the negative effects caused by air pollution.

The abstract summarizes the transformative impact of artificial intelligence (AI) on employment in Malaysia, highlighting the need for comprehensive strategies to ensure inclusivity and equitable access to AI-driven opportunities and digital skills training. It addresses the research problem of potential inequalities and marginalization among vulnerable populations due to uneven distribution of AI-related employment opportunities and training. The research objectives focus on developing decentralized strategies tailored to rural communities and marginalized groups, alongside evaluating policy interventions for equitable access. The literature review provides theoretical frameworks emphasizing skill development, understanding structural shifts, fostering inclusive innovation, and promoting collaborative governance. Future research directions include implementing and evaluating strategies in real-world contexts, exploring technological solutions, conducting qualitative research on individuals' experiences, and adopting interdisciplinary approaches. Overall, a multidimensional approach combining theoretical insights, empirical evidence, and stakeholder engagement is essential for developing inclusive and sustainable solutions to harness AI's potential for the benefit of all Malaysians.

The research fills the policy research gap for the women entrepreneurship and sustainability performance for examining key successful factors. Previous women entrepreneurship research fails to offer policy recommendations. The research purpose is to investigate these factors affect women entrepreneurship capabilities and sustainability performance by using SEM analysis and making policy recommendation. This research employs online and mail survey and obtains 175 women entrepreneur sample. The study finds that family support and motivation have positive effect on women entrepreneurship capabilities and sustainability performance. Barriers have no effect on performance. Hopefully, the research can provide the guidance to contribute to women’s entrepreneurship opportunities for achieving SDGs. Policy recommendation and managerial implication are discussed in the article.

Recent crises have highlighted the vulnerabilities of global supply chains and, consequently, a profound need for food system transformation. In this scenario, Local Food Policy and agroe-cology arise as two different but converging paradigms capable of fostering an inclusive and sustainable transition of the food systems, especially in the urban contexts. The purpose of this paper is to strengthen the relationship between these two paradigms by proposing agroecological assessment as a tool for formulating evidence-based Local Food Policies. Considering the city-region food system of Rome (Italy) as a reference context, the paper proposes an adaptation of the TAPE model on a sample of 20 farms to analyze urban agriculture and understand the extent to which it contributes to the transformation of the food system. Data processing shows that, in the city-region context of Rome, agroecological principles are not fully adopted by the majority of farms. In addition, farms with the highest agroecological level are those driven mainly by social factors and have a lower propensity for innovation. This could be read as a constraining aspect because it hinders and slows down the transformation process of food systems. However, these data turn out to be essential to the implementation of Local Food Policy and in identifying pathways toward sustainability.

A recent publication defined lockdown “revisionism” as “the spread of misinformation on lockdowns and other public health measures.” We used this publication to analyze the claim that questioning lockdowns or other public health interventions and mandates amounts to lockdown “revisionism” and “misinformation”. We suggest that the term ‘revisionism’, like the term ‘misinformation’ contained in its definition, were merely labels used to denigrate evidence-based contrary conclusions so as to avoid having to critically appraise the best evidence itself. We aim to describe how, by glossing over topics without fully engaging with the best evidence available, the assertions made do not withstand critical scrutiny. We suggest that, to ensure lessons are learned for the future, we must be willing to engage in rigorous and open debate – calling reasonable critical scrutiny of evidence ‘misinformation’, ‘disinformation’, or ‘revisionism’ is not supportive of this goal. Finally, we suggest that a main lesson from the COVID-19 pandemic is not to have an increased focus on so-called ‘misinformation’ and ‘revisionism’, but rather to re-discover the emergency management process of making decisions that ensure multidisciplinary representation, transparency, cost-benefit analyses of courses open using the best evidence available, and that protects against censorship and groupthink.

This paper is primarily focused on the robust control of an inverted pendulum system based on the policy iteration in reinforcement learning. First, a mathematical model of the single inverted pendulum system is established through a force analysis of the pendulum and trolley. Second, based on the theory of robust optimal control, the robust control of the uncertain linear inverted pendulum system is transformed into an optimal control problem with an appropriate performance index. Moreover, for the uncertain linear and nonlinear systems, two reinforcement-learning control algorithms are proposed using the policy iteration method. Finally, two numerical examples are provided to validate the reinforcement learning algorithms for the robust control of the inverted pendulum systems.

Worldwide, 200 million children experience disability, with the vast majority living in low and middle-income countries. The United Nations Convention on the Rights of the Child (CRC) places great importance on the rights of all children for the opportunities for survival, growth, health, and development. A subsequent document, the UN Convention on the Rights of Persons with Disabilities (CRPD) identifies children with disabilities as rights bearers, who should be considered in all policies and programming worldwide. Nigeria, in 1991 and 2010 ratified the CRC and the CRPD respectively. Nonetheless, knowledge of the extent to which their disability and child-directed policies are considered by these two key conventions remains limited. This study examined the extent to which Nigeria’s current disability and childhood policies have integrated the two normative frameworks from the UN. Using a structured search of databases and Nigerian federal and state government websites, we conducted a policy review to identify their disability and child-related disability policies. We also included the CRC and CRPD reports submitted by the Nigerian government to the United Nations Office of the High Commissioner for Human Rights (OHCHR) (2008 &amp; 2010 cyclical year). A thematic analysis, based on the CRC and CRPD report, identified the following six themes: participation, support systems, awareness-raising, factors associated with adherence to the CRC, laws &amp; rights, and services. The review showed that the available Nigerian disability policies were federal, with some state policies which aligned with the CRC and CRPD. Also identified was the lack of disability policies specific to children and their families. We concluded that, to ensure proper inclusion of the rights of all children, including those with disabilities, in Nigeria there is a need for a more optimal uptake of recommendations of the CRC and CRPD as laid out by the UN.

Tuna species are an important resource to the people of the Pacific, particularly small island countries like Tonga, that have few alternative natural resources. These countries are dependent on this fishery for their nutrition, recreation, government revenue, employment, welfare and culture. Threatening these benefits, however, are global warming and climate uncertainties that affect the presence and distribution of tuna in the Pacific islands countries and territories. There-fore, one of the most important development goals for Tonga involves managing its tuna fish-eries in order to optimize these benefits within the context of climatic impacts. This paper has two main goals. Firstly, we discuss Tonga’s commitment to implement the existing tuna man-agement policies. This commitment permeates through a range of activities to monitoring catch regulations and regulate locally based foreign vessels to fish in the Economic Exclusive Zone of Tonga. This reflects the implementation of an information-based management framework namely, the Tonga National Tuna Fishery Management and Development Plan that is revised every five years. Secondly, the paper identifies key scientific research programs, which form the basis to design more informed future policies towards tuna management. These researches include : i) examining of the bathymetric features of the island nation’s fishing ground, ii) model-ling the spatio-temporal distribution of tuna and, iii) characterizing tuna habitats within an oceanic environment using biophysical oceanographic data within Geographic Information Sys-tem, and iv) impacts of climate change on tuna

This research aims to produce a network structure in the Integrated Urban Farming Program in Bandung City to map the policy actors involved in it as an effort to support food security in the city. This research uses a mixed method with an exploratory sequential strategy involving policy actors from the government, private sector, academia, community, and mass media. To obtain the network structure in integrated urban farming to determine the most important actors, this research uses a social network analysis approach by utilizing the Gephi application. The network structure is based on four dimensions, namely centrality. The results of this study confirm that the actor who has the most connections (degree centrality), as well as the one who holds the best communication control (betweenness centrality), is Parahyangan Catholic University (Academic). While the actor who plays the most important role (eigenvector) is at the lower level of the government Sub-District and Urban Village. This research is useful for explaining the importance of the position of actors in the urban agriculture policy network which is the key to the success of a program.

Given that population COVID-19 vaccination does not appreciably reduce SARS-CoV-2 transmission, instead, the potential to reduce hospitalization has been used to justify coercive vaccine passports. We aim to use a recently published research study as an example in order to demonstrate how data can be misinterpreted and result in deriving misleading ethical and policy implications. Bagshaw et al wrote that unvaccinated patients with COVID-19 in Alberta, Canada “had substantially greater rates of ICU admissions, ICU bed days, and ICU related costs than vaccinated patients did. This increased resource use would have been potentially avoidable had these unvaccinated patients been vaccinated.” The authors in Bagshaw et al then concluded that their findings “have important implications for discourse on the relative balance of increasingly stringent public health protection (restrictions), including mandatory vaccination policies, and the sustainability and function of health system infrastructure and capacity during the ongoing COVID-19 pandemic.” Here we show the following. First, the effect of vaccination on intensive care admissions were grossly over-estimated due to several limitations of this and almost all other vaccine studies. Second, an effect of vaccination on access to acute care and on all-cause excess deaths was grossly over-stated due to several more likely causes being omitted from discussion and from the common narrative. Third, policy implications were overstated and at best unclear due to missing consideration of more relevant aspects required to inform policy. Overall, the data cannot support what Bagshaw et al called “increasingly stringent public health protection (restrictions), including mandatory vaccination policies”.

This paper presents an alternative conceptualization and definition of technology in the context of university technology transfer. The ambiguity regarding the conceptualization of technology is apparent in the technology transfer literature. An expanded conceptualization of technology potentially opens new approaches to researching the topic of technology transfer. It may also cause policymakers to think more comprehensively about what it means to successfully transfer technologies derived from federally funded research to the private sector for use that benefits the public interest. This paper integrates constructs and ideas in the related literature to provide a new perspective of technology that can support future scholarly research and public policy formulation about technology transfer in general, and university technology transfer specifically. Although the paper focuses on university technology transfer to the private sector in the United States, the insights it presents are relevant to technology transfer more broadly and applicable in other geopolitical contexts.

The study uses annual time series data from the South Africa Reverse Bank (SARB) from 1980 to 2020 to examine the effectiveness of fiscal policy on economic growth in South Africa. The Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root tests, as well as the Johansen Co-integration test, Granger causality test, and Vector Auto-Regression (VAR) method, were used in the study. Real GDP per capita (RGDP) is used as proxy of economic growth and gross fixed capital formation (GFCF), government expenditure (GEXP) and government deficit (GOVD) as the proxies of fiscal policy. The ADF test results show that all variables are stationary at the first difference, with the exception of GFCF and GEXP, which are stationary at I(0), whereas the PP test results show that all variables are stationary at I(1), with the exception of GEXP, which is stationary at I(0). At Maximum Eigenvalue, the four variables are not cointegrated. The findings of the Granger causality test demonstrated a unidirectional causation from GOVD to RGDP, as well as a bidirectional causality from RGDP to GFCF and GEXP. Error Correction Model Estimated using VAR shows that GFCF, GEXP have positive effect on RGDP whereas GOVD has a negative effect on RGDP in the short run. The findings also presented that the VAR's residuals are homoscedastic, which means they are normally distributed and have no serial correlation.

Cloud robot is becoming popular and security of cloud robot is important. However, the researches of cloud robot safety are a few. This work develops a security policy to defense DDoS attack of cloud robot. In this policy, complex, but accurate calculation models are deployed on the cloud, simple but efficient calculation models are deployed on the robot. In the cloud, there are master server and standby server. The master server transfers parameters of complex but accurate models to the standby server periodically and the master executes the start-stop backup policy. Specifically, this work proposes and proves an algorithm to dynamically adjust the interval of parameter transfer. According to a PDRA feature of Netflow, when DDoS attacks, the master server sends warning signals to the robot and standby server. The robot runs local models to avoid stopping work until it is connected to the standby server. Then, standby server provides service to the robot until the master server recover. Finally, this work implemented a gesture recognition cloud robot based on convolutional neural network, hidden Markov model and PDRA feature of Netflow to verify the policy. Experiment shows that the security policy to defense DDoS attack for cloud robot is effective.

As the leader of the largest economy, President of the United States has substantive influence on addressing the global climate change problem. However, presidential election is often dominated by issues other than energy problems. This paper focuses on the on-going 2016 presidential election, examining the energy plans proposed by the leading Democrat and Republican candidates. Our data from the Iowa caucus survey in January 2016 suggests that voters are more concerned about terrorism and economic issues than environmental relative issues. We then compare the Democratic and Republican candidate’s view of American’s energy future, and evaluate their proposed renewable energy targets. We find that the view on renewable energy is polarized between Democratic and Republican candidates, while candidates from both parties agree on the need for energy efficiency. Results from our ordinal least squares regression models suggest that Democratic candidates have moderate to ambitious goals for developing solar and other renewable energy. The Republican candidates favor fossil fuel and they neglect to provide any plan for renewable energy. In addition, this trend of polarization has grown more significant when compared with the past three presidential elections. Our observation suggests that energy issues need to be discussed more to draw broader attention to salient issues of diversifying and decarbonizing the nation’s energy system.

The research explores the impact of financial indicators on the credit ratings of companies listed on the S&amp;P 500, employing a Sys-GMM Model to address endogeneity concerns. The study investigated three independent variables categorized as market and survival factors alongside with seven control variables sourced from leverage, liquidity, interest coverage, profitability, market, survival, and macroeconomic domains. The sample comprised 2398 observations from Capital IQ Pro, spanning nine years (2013 to 2021) and encompassing 240 public companies. The findings suggest that neither Tobin's Q (TQ) and Total Shareholder Return (TSR) lack significant correlations with credit ratings, implying that stock market performance and total shareholder return do not directly impact credit ratings. In contrast, the Altman Z-score (AZS) emerged as a significant predictor, indicating its importance in assessing credit risk. These insights enhance understanding of financial indicators' impact on credit ratings, aiding financial institutions and companies in prudent lending and financing decisions.

We examine a linear q-difference differential equation which is singular in complex time t at the origin. Its coefficients are polynomial in time and bounded holomorphic on horizontal strips in one complex space variable. The equation under study represents a q-analog of a singular partial differential equation, recently investigated by the author, which comprises Fuchsian operators and entails a forcing term that combines polynomial and logarithmic type functions in time. A sectorial holomorphic solution to the equation is constructed as a double complete Laplace transform in both time t and its complex logarithm log t and Fourier inverse integral in space. For a particular choice of the forcing term, this solution turns out to solve some specific nonlinear q-difference differential equation with polynomial coefficients in some positive rational power of t. Asymptotic expansions of the solution relatively to time t are investigated. A Gevrey type expansion is exhibited in a logarithmic scale. Furthermore, a formal asymptotic expansion in power scale is displayed, revealing a new fine structure involving remainders with both Gevrey and q-Gevrey type growth.

One third of a person’s life is spent on sleep, therefore the quality and habit of sleep affects health. A single case study indicated that perspiration could serve as a prognostic marker. Diagnosing nocturnal perspiration is common clinical practice, since this serves as a major symptom in many pathologies. Till this day no specific evidence-based approach for diagnosing nocturnal perspiration exists. By introducing the Q-strip, a device which quantitatively measures nocturnal perspiration, this could be acquired. The Q-strip could serve a purpose in diagnosing nocturnal perspiration more efficient without being intrusive. In addition to its health sensing potentials, the Q-strip makes it possible to visualise perspiration patterns. This introduces the possibility to examine the quality of sleep. Future research is recommended to investigate this.

Membranes based on sulfonated synditoactic polystyrene were thoroughly characterized by contrast variation SANS over a wide Q-range in dry and hydrated states. The film samples were prepared by solid-state sulfonation that allowed a uniform sulfonation of only the amorphous phase while preserving the crystallinity of the membrane. The samples were loaded with different guest molecules in either the amorphous (fullerenes) or the crystalline (toluene) regions, in order to vary the neutron contrast or to reproduce the conditions enabling an increased resistance of the membranes to chemical decomposition. The use of uni-axially deformed film samples and contrast variation with different H2O/D2O mixtures allowed for the identification and characterization of different structural levels with sizes between nm and μm, which form and evolve in the membrane morphology in dry and hydrated states and produce scattering features on different detection sectors and at different detection distances after the sample, depending on their size and orientation.

Background: The global pandemic of coronavirus disease 2019 (COVID-19) resulted to many deaths from fulminant respiratory failure. Chronic obstructive pulmonary disease (COPD) is the leading cause of morbidity and mortality worldwide. There has been great concern regarding the impact of COPD on COVID-19 illness. Methods: Data from the Philippine CORONA Study were analyzed to determine the association of COPD and COVID-19 in terms of mortality, disease severity, respiratory failure, mechanical ventilation, and lengths of stay in the intensive care unit (ICU) and hospital. The influence of smoking on COVID-19 disease severity and mortality were also reviewed. Results: A total of 10,881 patients were included in the study and 156 (1.4%) patients had been diagnosed with COPD. Majority of COVID-19 patients with COPD had other existing comorbidities: hypertension, diabetes mellitus, chronic cardiac disease, and chronic kidney disease. COPD patients more commonly present with severe or critical COVID-19. COPD patients with COVID-19 were at higher risk to experience in-hospital mortality, respiratory failure, and to be admitted in the ICU. Smokers were more likely to present with higher COVID-19 severity and experience in-hospital mortality. Conclusion: Our study supports that the growing evidence that COPD among COVID-19 patients is a risk for higher mortality, more severe form of COVID-19, higher ICU admission, and higher respiratory failure needing ventilatory support. Smoking increases risk for developing severe COVID-19 and mortality.

Single-Anastomosis Duodeno-Ileal bypass with Sleeve Gastrectomy (SADI-S) is a modification of the duodenal switch in which only one anastomosis is performed, with a longer common limb and an expected less malabsorptive effect. The present study analyzes presentation and treatment of malnutrition after SADI-S. 258 consecutive patients undergoing SADI-S between May 2007 and September 2017 were included. The common limb length was 200 cm in 50 cases, 250 cm in 156 and 300 in 52. 30 patients were admitted for severe hypoalbuminemia and 16 patients were submitted to revisional surgery and constitute the series of our study. Mean weight before reoperation was 57 kg and mean body mass index (BMI) was 21 kg/m2. Mean number of daily bowel movements was 5,6. Mean time to reoperation was 56 months. Revisional surgery consisted mainly in elongation of the common limb. Mean weight regain was 14 kg and mean final BMI was 26 kg/m2. Daily bowel movements were decreased to 1,3. Factors related to hypoalbuminemia were hypertension, poor controlled diabetes, age over 55 years and a shorter common limb. Although SADI-S is expected to be less malabsorptive than previous biliopancreatic diversions, caution has to be taken with selected patients to avoid postoperative malnutrition.

This review centers on the pivotal role of the oncoprotein FOSL1, within the dimeric AP-1 transcription factor consisting of FOS-related elements. FOSL1 emerges as a key regulator governing invasion and metastatic dissemination, therefore making it a promising target for therapeutic intervention in cancer patients. The review provides a comprehensive survey of the regulatory mechanisms that exert influence over FOSL1. These encompass a spectrum of transcriptional and post-translational modifications. Notably, we unveiled the intricate involvement of diverse non-coding RNAs, specifically microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), in the modulation of FOSL1 expression through targeted interactions with its mRNA transcripts. Furthermore, an exploration into the functional dimensions of FOSL1 unfolds, encompassing apoptosis, proliferation, and migration. This investigation is accompanied by a thorough examination of the elaborate signaling pathways that underpin these multifaced roles. Additionally, emphasis is placed on the role of FOSL1 in orchestrating the stimulation of various cytokines, including TGF-beta, and the initiation of IL-6 and VEGF production in tumor-associated macrophages (TAMs) that transverse into the tumor microenvironment. A distinct focus is dedicated to appraising the prognostic implications associated with FOSL1. Finally, insights emerge into the evolving roles of FOSL1 in the context of mechanisms governing resistance and dependency on targeted therapeutic modalities.

Cissus populnea Guill. & Perr. (Vitaceae) is used in traditional medicine to treat microbial infec-tions, venereal diseases, and infertility, among others. The aim of the research is to isolate and characterize the antimicrobial constituent(s) from the stem of C. populnea. The n-butanol fraction of C. populnea being most active was subjected to silica gel column chromatography which led to the isolation of a white solid and white crystalline substances coded compounds C1 and C4C5, respectively. Spectral analysis (1D & 2D-NMR) of the isolated compounds and comparison with literature data indicated C1 to be Bis-(2-ethyloctyl)-phthalate and C4C5 to be a mixture of stig-masterol and β-sitosterol; C4C5 exhibited zone of inhibition ranging from 24 – 29 mm against the test organisms with Candida albicans being the most sensitive organism while Trichophyton rubrum was the least sensitive organism. The standard drugs, Ciprofloxacin had 27 – 37 mm while Flu-conazole and Fulcin exhibited zone of inhibition ranging from 34 mm and 29 – 32 mm, respec-tively. The MIC and MBC/MFC values for C4C5 ranges from 12.5 – 25.0 µg/cm3 and 25.0 – 50.0 µg/cm3 against MRSA, S. aureus, E. coli, C. albicans, T. rubrum, and T. mentagrophyte, respectively. In conclusion, three bioactive compounds were identified for the first time from the stem of C. populnea