Moral identity can promote people’s well-being, but existing research has paid little attention to the mechanism of the link between the two. The current study proposed that the eudaimonic identity function is a critical mechanism that links moral identity and well-being. Specifically, the quality of identity commitment mediates the link between subjective well-being and the two dimensions of moral identity, namely, internalization and symbolization. We examined these hypotheses in 419 participants, who completed the Self-importance of Moral Identity Questionnaire, Satisfaction with Life Scale, Scale of Positive and Negative Experience, and Questionnaire for Eudaimonic Well-being. Results from the obtained data confirmed our hypotheses: There is a significant correlation between moral identity and subjective well-being. Both the internalization and symbolization dimensions of moral identity promote subjective well-being through the mediating role of identity commitment quality. We discussed these findings with respect to implications and proposed research suggestions for future studies.

The genus Amomum encompasses six medicinal species that are extensively utilized and have a significant historical background. Due to their morphological similarities, however, the presence of counterfeit and substandard products remains a challenge. Accurate plant identification is therefore essential to address these issues. This study utilized 11 newly sequenced samples along with extensive data from NCBI to perform molecular identification of these six species. The plastomes of Amomum displayed a typical quadripartite structure with conserved gene content, yet showed independent variations in the SC/IR boundary shifts at both inter- and intra-specific levels. Our approach incorporated ITS, ITS1, ITS2, complete plastomes, matK, rbcL, and psbA-trnH sequences for molecular identification, which effectively differentiated the six medicinal species within the genus Amomum, as confirmed by distance-based and phylogenetic tree analyses. Among these, the ITS, ITS1, and complete plastomes sequences demonstrated the highest identification success rate (3/6), followed by ITS2, matK, and psbA-trnH (1/6). In contrast, rbcL failed to identify any species. This research successfully established a reliable molecular identification method for Amomum plants, to protect wild plant resources and promote the sustainable use of medicinal plants and restrict the exploitation of these resources.

Role identity theory describes the purpose and meaning in life that comes, in part, from occupying social roles. While robustly linked to health and well-being, this may become, however, when an individual is unable to fulfil the perceived requirements of an especially salient role in the way that they believe they should. Amid high rates of mental illness among public safety personnel, we interviewed a purposely selected sample of 21 paramedics from a single service in Ontario, Canada to explore incongruence between an espoused and able-to-enact paramedic role identity. Situated in an interpretivist epistemology, and using successive rounds of thematic analysis, we developed a framework for role identity dissonance wherein chronic, identity-relevant disruptive events cause emotional and psychological distress. While some participants were able to recalibrate their sense of self and understanding of the role, for others, this dissonance was irreconcilable, contributing to disability and lost time from work. In addition to contributing a novel perspective on paramedic mental health and well-being, our work also offers a modest contribution to the theory in using the paramedic context as an example to consider identity disruption through chronic workplace stress.

Introduction: The association between epilepsy and myasthenia gravis has rarely been reported, and only in small case series. Objective: To report the frequency of epilepsy and myasthenia gravis and to describe a case series of patients with myasthenia gravis and epilepsy, focusing on their clinical characteristics and searching for a possible physiopathological mechanism. Methods: A retrospective, observational, adult center study was conducted in 2022. Patients were recruited from the database of the outpatient clinic of the Myasthenia Gravis unit and Epilepsy unit. Results: Five patients were included. Frequency of epilepsy in the myasthenia gravis cohort was 5/469 (1.1%), and of myasthenia gravis in the epilepsy cohort was 5/1432 (0.35%). All patients suffered focal epilepsy, mainly fronto-central, and drug-resistant in half of them. Myasthenia gravis was generalized and with exacerbations in half of them. Three patients were thymectomized. Other autoimmune diseases were found in 2 (40%). Epilepsy onset preceded myasthenia gravis onset in all patients. Both diseases were considered autoimmune-related in 3/5 (60%). Conclusion: Epilepsy and myasthenia gravis are only infrequently associated. In adult patients, epilepsy onset precedes myasthenia onset in most cases. In some cases, epilepsy has an autoimmune aetiology and coexists with other autoimmune conditions.

This paper looks at key elements of global culture that are driving a new paradigm shift in museums causing them to question their raison d'être, their design and physical space, recognizing the need to accommodate visitor interaction and participation, and to reprioritize institutional outcomes and goals reexamining their priorities. As heritage sharing in online spaces reaches across national, political, and social boundaries on platforms and networks, this has been driven by museum engagement with Internet life during the pandemic. Museum relationships and interactions with communities both local and global, continue to challenge core values and precepts, leading to radical changes in how museums define their roles and responsibilities. In this new cultural landscape, museums are responding to human digital identity in a tidal wave of human interactions on the Internet, from social media to online sharing of images and videos. This is revealing shared perspectives on cultural conflict as being tied to freedom of expression of one’s heritage embedded in digital identity.

Online identity-based theft is known to be one of the most serious and growing threats to victims, such as individuals and organizations, over the last 10 years due to the enormous economic damage these crimes have caused. The availability of personal information on the Internet has increased the chances of this cyber-crime. Online identity theft crime is the result of a combination of cyber-crimes on the one hand and lack of awareness and training of users on the other hand to protect personal data on the other. Education and awareness, which also contributes to early detection, is the strongest tool for consumers to safeguard themselves from online identity fraud. This paper provides a comprehensive explanation of online identity theft, the various approaches that thieves use to attack individuals and organizations and the types of fraud involved in this cyber-crime. The aim of this research is to evaluate the need for a reformulation of the concept of identity theft in order to be compatible with the evolution of behaviors and fraud.

1) Background: Traditionally, complex biological products such as vaccines presented unique challenges to implementation of even rudimentary characterization packages; thus, the product was defined almost exclusively by its manufacturing process. The advances in technology and analytical tools allowed the application of more comprehensive characterization packages for products such as adsorbed combination vaccines, which contain several antigens in a single formulation to protect against more than one disease, and may contain adjuvants and excipients. Aluminum phosphate (AlPO4) is a well-established adjuvant for enhancing the uptake of vaccines and to induce robust immunity against pathogens. During manufacturing, adjuvant is mixed with protein antigens which may in turn impact their higher order structure and stability. 2) Methods: To study the structural changes of protein antigens after adsorption several analytical tools including DLS, FTIR, Fluorescence, LD, and SEM were used. 3) Results: the AlPO4 adjuvant suspension consists of small submicron particles that form a continuous porous surface. Secondary structure alpha-helix and beta-sheet content of DT and TT increased after adsorption to AlPO4 adjuvant, whereas no significant changes were noted for other protein antigens. Interactions were noted between AlPO4 adjuvant and DT, TT, and FHA. 4) Conclusions: here we report for the first time the use of SEM for the visualization of adsorbed multivalent vaccine components. A unique signature profile detected for each multivalent vaccine by FTIR can be used as a lean in-process test to verify vaccine product composition and identity prior to filling.

Introduction Emergency laparotomy is a surgical procedure associated with significantly higher mortality rates compared to elective surgeries. Awake laparotomy under neuraxial anaesthesia has recently emerged as a promising approach in abdominal surgery to improve patient outcomes. This study aims to evaluate the feasibility and potential benefits of using lumbar spinal anaesthesia as the primary anaesthetic technique in emergency laparotomies. Methods We conducted a case series involving 16 patients who underwent emergency laparotomy for bowel ischemia, perforation, or occlusion. Lumbar spinal anaesthesia was employed as the main anaes-thetic technique. We analysed patient demographics, clinical characteristics, intraoperative details, and postoperative outcomes. The primary outcome measures included the adequacy of postoper-ative pain control, the incidence of postoperative complications, and mortality rates. Results Among the 16 patients, adequate postoperative pain control was achieved, with only 2 patients requiring additional analgesia. Postoperative complications, including sepsis, wound dehiscence, and pneumonia, were observed in 7 patients (44%). The observed mortality rate was relatively low at 6% (1 patient). Notably, conversion to general anaesthesia was not necessary in any of the cases, and no early readmissions were reported. Discussion Our findings highlight the feasibility and potential benefits of using neuraxial anaesthesia in emergency laparotomies. The observed low mortality rate and the avoidance of conversion to general anaesthesia suggest that lumbar spinal anaesthesia may be a useful alternative in emer-gency settings. However, the occurrence of postoperative complications in 44% of patients indi-cates the need for cautious patient selection and close monitoring. Further research with larger sample sizes is warranted to fully elucidate the efficacy, safety, and potential impact of this tech-nique on patient outcomes in emergency laparotomies.

Selecting the optimal activation function for training deep neural networks has always been challenging because it significantly impacts the neural network’s performance and training speed. At this point, researchers are more likely to employ RELU than other well-known activation functions. After RELU, researchers have proposed many activation functions to improve RELU. None of them was capable of surpassing RELU as their most significant rival. SWISH outperformed RELU in several challenging experiments like classification, object detection, and tracking. Replacing RELU units with SWISH, which improves performance in many tasks. This paper proposed a new activation function surpassing Google’s brain’s SWISH function, Which we named AIF. Experiments indicate that our proposed activation function outperforms SWISH in various tasks.

A body plan is a stable configuration of characters for a major taxonomic group, such as chordates or arthropods. Despite widespread casual reliance on the concept for guiding comparisons within and between groups, the nature of body plans as well as the biological causes underlying their evolution have remained elusive. This paper proposes an abstract mechanistic model of body plan identity. We hypothesize that body plans are an evolutionary phenomenon that only applies to a relatively small subset of major clades, rather than being associated with each and every so-called “phylum.” Body plans arise in evolution by stepwise accretion, and require a level of developmental complexity that is only found in some animal clades. Further, we suggest that, parallel to the developmental mechanisms controlling character identity, there are “body plan identity mechanisms” (BpIMs) that maintain entire configurations of characters while possessing a mechanistic architecture that is itself stable and traceable through evolutionary change. These BpIMs, we suggest, are entrenched intercellular signaling networks operating between transient embryonic structures that are destined to differentiate into distinct individualized characters. The activity of a BpIM results in a transient long-range integration of the embryo that is highly sensitive to genetic and environmental perturbations, and that can be detected morphologically as a conserved phylotypic stage. This model is illustrated with detailed interpretations of the notochord signaling system and the segment polarity network as candidate BpIMs in vertebrates and arthropods, respectively. We conclude by contrasting the proposed developmental-mechanistic conception of body plans with the phylogenetic notion of ground plans, and sketch the general outlines of an empirical research program on body plan evolution.

We show how every power series gives rise to a Fibonacci series and a companion series involving Lucas numbers. For illustrative purposes, Fibonacci series arising from trigonometric functions, inverse trigonometric functions, the gamma function and the digamma function are derived. Infinite series involving Fibonacci and Bernoulli numbers and Fibonacci and Euler numbers are also obtained.

As technology evolves, our digital footprint keeps increasing. Now, everything we do is largely related to us being online, connected and logged. Therefore, if someone’s online data is exposed, then their life will be compromised. This is called identity theft and in this era of technology, it has become one of the most serious forms of crime. When someone’s data is compromised, there is a huge chance of harming the person financially, morally and socially. New technology and the knowledge gap it creates when it first comes out is perfect for identity thieves to exploit. If we are not cautious, our future will be very different than what we dream of due to the very technology created to make it better. Hence, we need to understand the technology, identify the loopholes and educate ourselves to avoid being held captive by our digital footprint.

The voice contains elementary social communication cues, conveying speech, as well as paralinguistic information pertaining to the emotional state and the identity of the speaker. In contrast to vocal-speech and vocal-emotion processing, voice-identity processing has been less explored. This seems surprising, given the day-to-day significance of person recognition by voice. A valuable approach to unravel how voice-identity processing is accomplished is to investigate people who have a selective deficit in recognising voices. Such a deficit has been termed phonagnosia. In the present chapter, we provide a systematic overview of studies on phonagnosia and how they relate to current neurocognitive models of person recognition. We review studies that have characterised people who suffer from phonagnosia following brain damage (i.e. acquired phonagnosia) and also studies, which have examined phonagnosia cases without apparent brain lesion (i.e. developmental phonagnosia). Based on the reviewed literature, we emphasise the need for a careful behavioural characterisation of phonagnosia cases by taking into consideration the multistage nature of voice-identity processing and the resulting behavioural phonagnosia subtypes.

In this paper, we derive and prove, by means of Binomial theorem and Faulhaber's formula, the following identity between $m$-order polynomials in $T$ $$\sum_{k=1}^{\ell}\sum_{j=0}^m A_{m,j}k^j(T-k)^j=\sum_{k=0}^{m}(-1)^{m-k}U_m(\ell,k)\cdot T^k=T^{2m+1}, \ \ell=T\in\mathbb{N}.$$

In this part of the series of two papers, we extend the theorems discussed in part I for infinite series. We then use these theorems to develop distinct novel results involving the Hurwitz zeta function, Riemann zeta function, Polylogarithm and Fibonacci numbers. In continuation, we obtain some zeros of the newly developed zeta functions and explain their behaviour using plots in complex plane. Furthermore, we provide particular cases for the theorems and corollaries which show that our results generalise the currently available functions and series such as the Riemann zeta function and the geometric series. Finally, we provide four miscellaneous examples to showcase the vast scope of the developed theorems.

In the paper, the authors discover several series identities involving the Catalan numbers, the Catalan function, the Riemanian zeta function, and the alternative Hurwitz zeta function.

The dielectric constant (ε) reflects the ability of a material to align and orient electrical dipoles within its structure in response to an externally applied electric field; the greater the polarizability of molecules, the greater the value of dielectric constant. In this study a data set of 86 polymers was investigated to develop a structure-property quantitative relations (QSPR) model to predict the dielectric constant in polymers. An initial set of 1273 descriptors was used to select a best set of descriptors and to construct two machine learning models with Gradient Boosting Regressor (GB_A and GB_B). The best performing model (GB_A) with 8 descriptors, exhibited a performance of (R2train) = 0.938 and (R2test) = 0.802. The models were internally validated by 5 folds cross-validation, demonstrating robustness. Additionally, using the Accumulative Local Effect (ALE) technique, we analyzed the relationship between the 8 descriptors involved and the impact of these descriptors to dielectric constant of polymers.

In this paper, we study the asymptotic behavior of the sequential empirical process and the sequential empirical copula process, both constructed from residuals of multivariate stochastic volatility models. Applications for the detection of structural changes and specification tests of the distribution of innovations are discussed. It is also shown that if the stochastic volatility matrices are diagonal, which is the case if the univariate time series are estimated separately instead of being jointly estimated, then the empirical copula process behaves as if the innovations were observed; a remarkable property. As a by-product, one also obtains the asymptotic behavior of rank-based measures of dependence applied to residuals of these time series models.

Let be a power function $f_{r,M}(s)$ defined for every $s$ within the finite set $M$ as follows $$f_{r,M}(s)= \begin{cases} s^r, \ &s\in M,\\ 0, \ &\mathrm{otherwise}. \end{cases} $$ Let a discrete convolution of $f_{r,M}(s)$ be denoted as follows $\mathrm{Conv}_{r,M}[n]=(f_{r,M}*f_{r,M})[n]$. Let a real coefficients $A_{m,j}$ be given by the following recurrence $$ A_{m,j} = \begin{cases} 0, & \mathrm{if } \ j<0 \ \mathrm{or } \ j>m, \\ (2j+1)\binom{2j}{j} \sum_{d=2j+1}^{m} A_{m,d} \binom{d}{2j+1} \frac{(-1)^{d-1}}{d-j} B_{2d-2j}, & \mathrm{if } \ 0 \leq j < m, \\ (2j+1)\binom{2j}{j}, & \mathrm{if } \ j=m. \end{cases} $$ In this paper we show that for every $n>0$ the following odd-power identities involving coefficients $A_{m,j}$ and convolution transform $\mathrm{Conv}_{r,M}[n]$ hold $$ \begin{split} n^{2m+1}+1&=\sum_{r=0}^{m}A_{m,r}\mathrm{Conv}_{r,\mathbb{N}}[n],\\ n^{2m+1}-1&=\sum_{r=0}^{m}A_{m,r}\mathrm{Conv}_{r,\mathbb{Z}_{>0}}[n],\\ n^{2m+1}&=\sum_{r=0}^{m}A_{m,r}\sum_{k=1}^{n} k^r(n-k)^r\\ &=\sum_{r=0}^{m}A_{m,r}\sum_{k=0}^{n-1} k^r(n-k)^r. \end{split} $$

This paper addresses the evolving landscape of electricity markets in Europe, with a focus on the integration of Renewable Energy Communities as introduced by the Renewable Energy Directive 2018/2001. Residents within a postal code area are highly incentivized to join a community, which enables them to exchange energy among themselves at lower procurement costs. Thereby, energy management systems optimize the operation of respective energy systems, with electrical load forecasting playing a key role. Given that prosumers may switch between communities on a daily basis, electricity demands within these groups will vary, leading to data that is non-stationary, discontinuous as well as non-identical and independently distributed. To encounter this issue, we propose a sophisticated forecasting model that applies federated learning, using informations from various distributed communities to learn domain-invariant features. To achieve this, we initially utilize synthetic electrical load time series at district level and aggregate them to profiles of Renewable Energy Communities with dynamic portfolios. Subsequently, we develop a forecasting model that accounts for the composition of residents of a Renewable Energy Community, adapt data pre-processing in accordance with the time series process, and detail a federated learning algorithm that incorporates weight averaging and data sharing. Following the training of various experimental setups, we ultimately evaluate their effectiveness. The findings suggest that our proposed framework is capable of effectively forecast non-stationary and discontinuous time series and that it can be applied to new, unseen data through the integration of knowledge from multiple sources.

Purpose: This study investigates the influence of human brands on the formation of Generation Z's digital identity. Given the increasing importance of the digital space in this generation's life, understanding how their identity is shaped by human brands in this environment is crucial. Method: Using a netnographic approach, qualitative data was collected and analyzed from 500 posts and interactions of Gen Z users on Instagram and TikTok platforms. Thematic content analysis was conducted using NVivo 12 software, with inter-coder reliability confirmed (κ = 0.85). Findings: Results indicate that human brands influence Gen Z's digital identity through three main mechanisms: 1) lifestyle emulation (β = 0.42, p < 0.001), 2) value alignment (β = 0.38, p < 0.001), and 3) self-presentation modeling (β = 0.35, p < 0.01). Multiple regression analysis showed these three factors explain 67\% of the variance in digital identity formation (R² = 0.67, F(3,496) = 335.42, p < 0.001). Conclusion: This study demonstrates that human brands play a significant role in shaping Generation Z's digital identity. Understanding this influence can help marketers and policymakers design more effective strategies for engaging with this generation.

In nature and engineering applications, flexible fiber beds covering biological surfaces can play a role in reducing resistance. These fibers deform under the action of fluids, and this deformation affects the fluid flow state, forming a complex fluid-solid interaction phenomenon. To quantitatively analyze such issues, the physical model is simplified to the deformation problem of an soft hair bed caused by Stokes flow, and the deformation problem of a single fiber caused by Stokes flow is further studied. The deformation problem of an elastic single fiber in a channel caused by Stokes flow can be described by a nonlinear integral equation. We have obtained a new series solution, which has been compared with the previous perturbation method to verify the accuracy and effectiveness of the series solution. Meanwhile, we have further provided an extended form of flexible fiber deformation through experimental fitting. This fluid-solid interaction problem involves multiple fields and is very important in many natural and engineering systems. The research in this paper can not only help us better understand complex phenomena in nature but also delve into the interaction mechanism between fluids and solids, providing a theoretical basis for future scientific research and engineering applications.

Purpose: We present a theoretical framework that formalizes and defines the constructs of communicative congruence and communicative dysphoria that is rooted within a comprehensive and mechanistic theory of personality. Background: Voice therapists have likely encountered a patient who states that a therapeutic target voice “isn’t me.” The ability to accurately convey a person’s sense of self, or identity, through their voice, speech, and communication behaviors seems to have high relevance to both patients and clinicians alike. However, to date, we lack a mechanistic theoretical framework through which to understand and interrogate the phenomenon of congruence between one’s communication behaviors and their sense of self. Results: We review the initial notion of congruence, first proposed by Carl Rogers. We then review several theories on selfhood, identity, and personality. After reviewing these theories, we explain how our proposed constructs fit within our chosen theory, the Cybernetic Big Five Theory of Personality. We then discuss similarities and differences to a similarly named construct, the Vocal Congruence Scale. Next, we review how these constructs may come to bear on an existing theory relevant to voice therapy, the Trans Theoretical Model of Health Behavior Change. Finally, we state testable hypotheses for future exploration, which we hope will establish a foundation for future investigations into communicative congruence. Conclusion: To our knowledge, the present paper is the first to explicitly define communicative congruence and communicative dysphoria. We embed these constructs within a comprehensive and mechanistic theory of personality and, in doing so, hope to provide a rigorous and comprehensive theoretical framework that will allow us to test and better understand these proposed constructs.

Mutual survival among different species of living organisms is quite common in our living world. That mutual survival can produce symbiotic or parasitic relationship among different living organisms. But at the same time, some relationships are harmful to the living organisms creating pathogenic relationships. Why some mutual survivals are beneficial, whereas some relationships are harmful creating different diseases in the living world? That harmful or pathological relationship producing different diseases in both the animal and plant kingdom has been extensively studied by the scientific community several times under the heading of ‘Host-pathogen interaction’ and ‘Disease pathogenesis’. But it is still not clear why some mutual survivals are beneficial or non-harmful, whereas some co-survivals are harmful producing different disease conditions in the living world mainly due to different immune mediated reactions or direct toxic effect of substances produced by an organism. To find the answer to this question, we have to search retrospectively to the evolutionary pattern of our diverse living world. If it is assumed that we have originated from Last Universal Common Ancestor (LUCA) by different cumulative mutations, horizontal gene transfer, mobile genetic elements (MGE), transposition and natural selection, then it would be quite pragmatic to consider that two things were moving side by side in our ancient living world. On one hand it’s purpose was to create the diversification of both unicellular and multi-cellular living world and on the other hand it’s another purpose was to maintain the specific identity of the living organisms. It is the second purpose or the maintenance of specific identity that ultimately led to the development of Immune system.

Catastrophic mass flows originating from the high mountain cryosphere often cause hazard cascades. With increasing human activities in the alpine region and the sensitivity of glaciers, snow and permafrost to climate warming, the cryospheric hazard risks tend to be more active in the Tibetan Plateau(TP). The remoteness and inaccessibility of high mountain regions make the remote sensing technology the most effective approach for monitoring and investigating the cryospheric hazards. Exploring the evolution process and impact of ice avalanches and subsequent hazards are crucial to understand drivers and nature of mass flow process chain in order to prevent and mitigate potential hazard consequences. In this study, the glacier and ice-rock avalanches occurred in Arutso and Sedongpu basins in Tibet were investigated on the basis of Sentinel-2 time-series images and in-situ investigation, the evolution process of these events were reconstructed, and impacts and driving factors were analyzed. The massive Chamoli rock-ice avalanche occurred in February 2021 in the western Himalayas was also reviewed using using same methods. The study shows that Arutso glacier No. 53 (Arutso-53) avalanche completely melted away in July 2018 after two years from occurrence to final disappearance, while Arutso glacier No. 50 (Arutso-50) avalanche completely melted by the end of August 2023 after lasting for seven years. Four large-scale ice-rock avalanche and debris flow events in the Sedongpu basin in 2017 and 2018 not only had significant impacts on the river flow, landscape and geomorphologic shape in the basin, but also caused serious disasters in the basin and downstream. In March 2021, a small-scale ice-rock avalanche and debris flow event occurred again in the Sedongpu basin. The glacier and ice-rock avalanches occurred in Tibet area were mainly induced by climate warming, heavy precipitation and seismic activity, which acting on specific topographic and geomorphic structure of glacier properties in the high mountain regions. Catastrophic hazard events originating from the high-elevation glacier and ice-rock collapses in the mountain cryosphere and subsequent hazard cascades in the TP and Himalayas highlight the importance of mountain hazard monitoring, early warning systems and sustainable mountain development.

When dealing with limited sample sizes or missing values in time series data, achieving high accuracy in forecasting becomes challenging. This challenge is particularly common in wind energy forecasting, where many wind farms lack complete data. In this paper, we employ the widely-used ARIMA (Autoregressive Integrated Moving Average) model for time series forecasting. To address the difficulties posed by limited sample sizes and missing values, we adopt a unique approach by utilizing multiple ARIMA models for different datasets. A key distinction from other multiple models methods for time series forecasting lies in each model within our approach using its own dataset, making the fusion process more intricate. To overcome this, we incorporate neural networks and two techniques for model fusion: direct fusion with a learning mechanism and compensation for missing data through training. For each ARIMA model, we introduce a noise estimation method to circumvent the white noise assumptions inherent in ARIMA models. Finally, we apply these methods to wind energy prediction, and our experimental results showcase a significant enhancement in forecasting accuracy.

This article aims to analyze the problem of the identity and persistence of objects based on the hylomorphic doctrine, that is, the doctrine according to which objects are mereological compositions of the elements of form and matter. After introducing the contemporary discussion on the problem of identity and persistence and identity of objects, we propose a brief formalism of the logic of the relationship between part and whole or mereology to define the solution to the problem under study that defines a possible solution for it.

Calcium (Ca2+) ions act as second messenger, regulating several cell functions. Mitochondria are critical organelles for the regulation of intracellular Ca2+. Mitochondrial calcium (mtCa2+) uptake is ensured by the presence in the inner mitochondrial membrane (IMM) of the mitochondrial calcium uniporter (MCU) complex, a macromolecular structure composed of pore-forming and regulatory subunits. MtCa2+ uptake plays a crucial role in the regulation of oxidative metabolism and cell death. Many evidences demonstrate that dysregulation of mtCa2+ homeostasis can have serious pathological outcomes. In this review, we briefly discuss the molecular structure and the function of the MCU complex and then we focus our attention on human diseases in which a dysfunction in mtCa2+ has been showed.

Due to the great nutritional and medicinal value of honey, there has been growing consumer’s preference towards honey of a known identity. However, honey now is the third food in the world subjected to adulteration. Therefore, the current study was focused on judging the identity of Sudanese honeys and checking whether there is any misdesignation from originality. Melissopalynology was used as a tool for this purpose. A number of 60 honey samples were purchased from honey sellers. Results indicated that honey bees foraged on a bio-diversified number of plant species constituted of 11 major families [Fabaceae (43.3%), being the predominant family] and 8 minor families. Respectively, 18.3% &amp; 2% of the honey samples were found to be misdesignated by the honey sellers from their botanical and geographical identities. Some samples were predicted by melissopalynology to be originated from Ethiopia by the presence of marker pollens such as Kniphofia foliosa, Guizotia abyssinica, and Acacia abyssinica an indigenous Ethiopian flora. Thus these findings proved that melissopalynology is an effective tool in judging the identity of honey and pro of being inexpensive.

Backyard chickens often suffer from foot pad dermatitis (FPD), a condition exacerbated by poor husbandry, nutritional deficiencies, and obesity. Pressure-relieving bandages, commonly used in treatment of FPD, are impractical for outdoor chickens as they quickly become wet and dirty, necessitating daily changes which are often unfeasible. This retrospective study explores the use of custom-fit silicone shoes, created via 3D-printed molds, as an alternative to traditional bandages. CT scans were used to design shoes, adapted from a design used for birds of prey. Over three years, 16 chickens with varying degrees of FPD were treated. The results demonstrated that sili-cone shoes were an effective treatment for FPD, allowing outdoor activity, and facilitated daily lesion care without frequent bandage changes. The median shoe-wearing period was 14 days, and most owners provided positive feedback. Despite some attachment issues, the occurrence of sec-ondary pressure marks and feather regrowth challenges, the silicone shoes offered better ventila-tion, reusability, and consistent pressure relief compared to traditional bandages. This study con-cludes that silicone shoes are a viable solution for managing FPD in backyard chickens, promoting faster healing and improved owner compliance.

Pancasila is the identity of the Indonesian nation, which means that Pancasila is a national characteristic that cannot be found in any country. Pancasila points are taken from the noble values of the Indonesian state. These principles contain culture, customs, and national character known as manners, cooperation, and high nationalism. As the successor to Indonesian culture, the young generation must be able to preserve and develop Pancasila. In this era of globalization, there are many challenges for the younger generation in preserving Pancasila. This study aims to provide an overview of the decline of Pancasila identity among the younger generation due to the impact of globalization. The research question that has been determined is how the practice behaviour of the younger generation towards the implementation of Pancasila, the solutions and efforts that all Indonesian people can make regarding the crisis of Pancasila identity in the era of globalization. This research method uses a literature review. The research sources were conducted from the latest journals and books published in 2019 until 2021 related to the theme of Pancasila and the millennial generation. The results showed that globalization has greatly facilitated foreign cultures to enter Indonesia. The younger generations use this foreign culture as a lifestyle without filtering it, whether it contains Pancasila values or not. This causes Pancasila has been forgotten and no longer applied in their everyday life. Young people can make various efforts to preserve the national identity, namely Pancasila. Apart from the role of the young generation itself, Indonesian society can also play an essential role in supporting the younger generation to continue implementing Pancasila in their lives. By conducting this research, it is hoped that Indonesia's young generation can understand, select, and stay away from the negative impacts of globalization that enter Indonesia freely. The solution that can be given from this research is that the younger generation must love their own culture more and practice every principle in Pancasila. Parents, educational institutions, and the government must also support the younger generation to maintain national identity, Pancasila values. The limitation of this research is that the researcher did not conduct any primary data, which means the data were not directly from the source. This causes the accuracy of this study to be less guaranteed. The recommendation that the researchers can give for further research is to obtain primary data to ensure accuracy and explore research topics regarding the fading of Pancasila identity in the younger generation in this era of globalization.

In this study, we present a novel approach to estimate the Hurst exponent of time series data using a variety of machine learning algorithms. The Hurst exponent is a crucial parameter in characterizing long-range dependence in time series, and traditional methods such as Rescaled Range (R/S) analysis and Detrended Fluctuation Analysis (DFA) have been widely used for its estimation. However, these methods have certain limitations, which we sought to address by modifying the R/S approach to distinguish between fractional Lévy and fractional Brownian motion, and by demonstrating the inadequacy of DFA and similar methods for data that resembles fractional Lévy motion. This inspired us to utilize machine learning techniques to improve the estimation process. In an unprecedented step, we train various machine learning models, including LightGBM, MLP, and AdaBoost, on synthetic data generated from random walks, namely fractional Brownian motion and fractional Lévy motion, where the ground truth Hurst exponent is known. Meaning that we can initialize and create these stochastic processes with a scaling Hurst/scaling exponent which, is then used as the ground truth for training. Furthermore, we perform the continuous estimation of the scaling exponent directly from the time series, without resorting to the calculation of the power spectrum or other sophisticated preprocessing steps, as done in past approaches. Our experiments reveal that the machine learning-based estimators outperform traditional R/S analysis and DFA methods in estimating the Hurst exponent, particularly for data akin to fractional Lévy motion. Validating our approach on real-world financial data, we observe a divergence between the estimated Hurst/scaling exponents and results reported in the literature. Nevertheless, the confirmation provided by known ground truths reinforces the superiority of our approach in terms of accuracy. This work highlights the potential of machine learning algorithms for accurately estimating the Hurst exponent, paving new paths for time series analysis. By marrying traditional finance methods with the capabilities of machine learning, our study provides a novel contribution towards the future of time series data analysis.

Leishmaniasis is the third most common vector-borne disease and a very important protozoan infection. Cutaneous leishmaniasis is one of the most common types of leishmaniasis infectious diseases with up to 2 million occurrences of new cases each year worldwide. A dynamic transmission multivariate time series model was applied to the data to account for overdispersion and evaluate the effects of three environmental layers as well as seasonality in the data. Furthermore, ecological niche modeling was used to investigate the geographical suitable conditions for cutaneous leishmaniasis using temperature, precipitation and altitude as environmental layers, together with the leishmaniasis presence data. A retrospective analysis of the cutaneous leishmaniasis spatial data in Afghanistan between 2003 and 2009 indicates a steady increase from 2003 to 2007, a small decrease in 2008, then another increase in 2009. An upward trend and regularly repeating patterns of highs and lows was observed related to the months of the year which suggests seasonality effect in the data. Two peaks were observed in the disease occurrence-- January to March and September to December -- which coincide with the cold period. Ecological niche modelling indicates that precipitation has the greatest contribution to the potential distribution of leishmaniasis.

In recent years, change in behaviour towards the environment has gained prominence as a policy tool to influence positive environmental value. Simultaneously, the role played by social identity in promoting pro-environmental action is gaining recognition. Within this work, the intersection between collective group identity and environmental behaviour has received very little attention. Group norms are considered a strong predictor of pro-environmental behaviour, yet the influence of social identity and collective action on environmental action has not been adequately investigated in a multi-ethnic setting. Within this context, this study examines the affective component of social identity influence on pro-environmental action. More succinctly, this study demonstrates how outgroups and in-groups’ relations and broader socio-cultural structures, values, interest, and norms impact environmental and sustainability transitions behaviours. Through interviews with participants across the four dominant social groups in South Africa, this study provides compelling evidence that country wide expressions of social identity and in-group dynamics shapes the individual behaviour regarding environmental and sustainability concerns and further strengthen the individual’s perspective for social environmental transformation. This study advances the need for a social-identity centred approach to foster pro-environmental and sustainability outcomes.

After the great success of Mobile wallet, the Internet of Things (IoT) leaves the door wide open for consumers to use their connected devices to access their bank accounts and perform routine banking activities from anywhere, anytime and with any device. However, consumers need to feel safe when interacting with IoT-based payment systems, and their personal information should be protected as much as possible. Unlike as usually done in the literature, in this paper, we introduce two lightweight and secure IoT-based payment protocols based on an identity-based signature scheme. We adopt a server-aided verification technique to construct the first scheme. This technique allows to outsource the heavy computation overhead on the sensor node to a cloud server while maintaining the user's privacy. The second scheme is built upon a pairing-free ECC-based security protocol to avoid the heavy computational complexity of bilinear pairing operations. The security reduction results of both schemes are held in the Random Oracle Model (ROM) under the discrete logarithm and computational Diffie-Hellman assumptions. Finally, we experimentally compare the proposed schemes against each other and against the original scheme on the most commonly used IoT devices: a smartphone, a smartwatch and the embedded device Raspberry Pi. Compared with existing schemes, our proposed schemes achieve significant efficiency in the term of communication and computational overheads

In this paper, we compile the fractional power series method and the Laplace transform to design a new algorithm for solving the fractional Volterra integro-differential equation. For that, we assume the Laplace power series (LPS) solution in terms of power q=1m,m∈Z+, where the fractional derivative of order α=qγ for which γ∈Z+. This assumption will help us to write the integral, the kernel, and the nonhomogeneous terms as a LPS with the same power. The recurrence relations for finding the series coefficients can be constructed using this form. To demonstrate the algorithm's accuracy, the residual error is defined and calculated for several values of the fractional derivative. Two strongly nonlinear examples are discussed to provide the efficiency of the algorithm. The algorithm gains powerful results for this kind of problem. Under Caputo meaning the obtained results are illustrated numerically, and graphically. Geometrically, the behavior of the solution declares that the changing of the fractional derivative parameter values' in their domain alters the style of the attained solution in a symmetrical meaning and fully coinciding to the ordinary derivative value'. From these simulations, the results report that the recommended novel algorithm is a straightforward, accurate, and superb tool to generate analytic-approximate solutions for Integral, and integro-differental equations of fractional order.

Thousands of antibodies for diagnostic and other analytical purposes are on the market. However, it is often difficult to identify duplicates, reagent changes, and to assign the correct original publications to an antibody. This slows down scientific progress and might even be a cause of irreproducible research and a waste of resources. Recently, activities were started to suggest the sole use of recombinant antibodies in combination with the open communication of their sequence. In this case, such uncertainties should be eliminated. Unfortunately, this approach seems to be rather a long-term vision since the development and manufacturing of recombinant antibodies remain quite expensive in the foreseeable future. Also, nearly all commercial antibody suppliers may be reluctant to publish the sequence of their antibodies, since they fear counterfeiting. De-novo sequencing of antibodies is also not feasible today for a reagent user without access to the hybridoma clone. Nevertheless, it seems to be crucial for any scientist to have the opportunity to identify an antibody undoubtedly to guarantee the traceability of any research activity using antibodies from a third party as a tool. For this purpose, we developed a method for the identification of antibodies based on a MALDI-TOF-MS fingerprint. To circumvent lengthy denaturation, reduction, alkylation, and enzymatic digestion steps, the fragmentation was performed with a simple formic acid hydrolysis step. Eighty-nine unknown monoclonal antibodies were used for this study to examine the feasibility of this approach. Although the molecular assignment of peaks was rarely possible, antibodies could be easily recognized in a blinded test, simply from their mass-spectral fingerprint. A general protocol is given, which could be used without any optimization to generate fingerprints for a database. We want to propose that in most scientific projects relying critically on antibody reagents, such a fingerprint should be established to prove and document the identity of the used antibodies and to assign a specific reagent to a datasheet of a commercial supplier, a public database record or an antibody ID.

This paper presents an approach to teacher identity heritage as result of the implementation of a research device created through Arts-based Research (ABR) methods, specifically with video elicitation and video essay used as research tools. Two main objectives were raised. The first one, to establish the real relevance of focusing performance on teacher identity. The second one, testing a new methodological proposal specifically designed for this purpose, but still useful in other contexts where heritage identity is as present as in teaching. The device, Body-camera, involves a process that allows new ways to understand the creation of identities using video to encourage the production of new meanings by visual and oral data. The participants were teachers in training during their internship period. Some notions about teachers' identity heritage were revealed, and also preserved, firstly, through personal perspectives by video elicitations and secondly, through collective perspectives by video essays. Both are video structures used in ABR which mix creative experience, memories, life experiences, relationships and links that shape the teachers’ professional identity.

Corporate identity has played a vital role in the Halal industry to create a strong foundation for its reputation in the long run. This paper used two modeling analyses for two different data. The first analysis aims to predict the relationship between Corporate Identity Management between Internal Brand and Employee Brand Support (consequence) mediated by CIM using partial-least squares-structural equation modeling (PLS-SEM). A total of 206 employees from Malaysia’s Halal food SMEs took part in the survey. The second analysis to identify topic proportions patterns using the topic modeling approach on Halal brand identity Machine learning approach of knowledge mining was applied for this analysis. Metadata of 1,091 articles were mined from the Scopus database on Halal studies across all social sciences fields. The result revealed that there was a partial relationship between Internal Brand (antecedent) and Employee Brand Support (consequence) mediated by CIM. This finding was supported by the identified topic proportions patterns from the topic modeling approach that pointed out a weak topic proportion on the Halal brand identity discussion globally, interestingly the result also found that the Halal brand identity discussion involving the Halal food industry is almost non-existed in Malaysia’s Halal food SMEs. The contributions of this paper were apparent in three major areas which are methodology, theoretical and future suggestions. The utilization of two different model analyses was able to confirm the consistency of the major findings with the literature review which opens up more possibilities for future researchers.

Understanding the biology underlying the mechanisms and pathways regulating pancreatic β-cell development is necessary to understand the pathology of diabetes mellitus (DM), which is characterized by the progressive reduction in insulin producing β-cell mass. Pluripotent stem cells (PSCs) can potentially offer an unlimited supply of functional β-cells for cellular therapy and disease modeling of DM. Homeobox protein NKX6.1 is a transcription factor (TF) that plays a critical role in pancreatic β-cell function and proliferation. In human pancreatic islet, NKX6.1 expression is exclusive toβ-cells and is undetectable in other islet cells. Several reports showed that activation of NKX6.1 in PSC-derived pancreatic progenitors (MPCs), expressing PDX1 (PDX1⁺/NKX6.1⁺), warrants their future commitment to monohormonal β-cells. However, further differentiation of MPCs lacking NKX6.1 expression (PDX1⁺/NKX6.1^-) results in an undesirable generation of non-functional polyhormonal β-cells. The importance of NKX6.1 as a crucial regulator in MPC specification into functional β-cells directs attentions to further investigating its mechanism and enhancing NKX6.1 expression as a mean to increase β-cell function and mass. Here, we shed light on the role of NKX6.1 during pancreatic β-cell development and in directing the MPCs to functional monohormonal lineage. Furthermore, we address the transcriptional mechanisms and targets of NKX6.1 as well as its association with diabetes.

Background and Objectives: In recent years Electronic scooters (E-Scooters) have gained popularity, whether for private use or as a publicly available transportation method. With introduction of these vehicles, reports of E-Scooter related accidents have surged, sparking a public debate and concern. Aim of this study was to analyse epidemiological data, characteristics and severity of traumatic brain injury (TBI) related to E-Scooter accidents. Materials and Methods: This retrospective case series evaluated 28 patients who were admitted to three largest neurosurgery clinics in Riga, Latvia between time period from April to October in two separate years – 2022 and 2023 after an E-Scooter related accident. Data were collected on patient demographics, time of the accident, alcohol consumption, helmet use, type of TBI, other related injuries, treatment and assessment at discharge. Results: A total of 28 patients were admitted with TBI related to E-Scooter use, with median age 30 years (Q1-Q3, 20.25-37.25), four individuals under age of 18, majority (64%) were male. In 23 cases the injury mechanism was fall, in 5 cases collision. None were wearing a helmet at time of injury. Alcohol intoxication was evident in over half of the patients (51.5%), with severe intoxication (&gt;1.2ppm) in 75% cases among them. Neurological symptoms upon admission were noted in 50% of cases. All patients had intracranial trauma - 50% brain contusions, 43% traumatic subdural hematoma, almost 30% - epidural hematoma. Craniofacial fractures were evident in 71% of cases, fractures in other parts of body in 3 patients. 6 patients required emergency neurosurgical intervention. Neurological complications were noted in 2 patients, 1 patient died. Conclusions: E-Scooter related accidents result in a significant number of brain and other associated injuries, with notable frequency linked to alcohol influence and lack of helmet use. Prevention campaigns to raise awareness of potential risks and implementation of more strict regulations should be done.

Accurate forecasting and efficient management of commodities are crucial for stakeholders in the industry, given the volatile nature of these markets. This study addresses these needs by leveraging advanced forecasting techniques and machine learning models to predict prices and enhance supply chain efficiency. TThe focus is on utilizing ARIMA, SARIMAX, and LSTM models to analyze historical trading data for commodities such as cocoa, coffee, and sugar sourced from Kaggle’s comprehensive dataset. The research applies ARIMA and SARIMAX models to forecast price trends, overcoming initial challenges related to data index frequency and seasonality. LSTM models are employed for more nuanced demand forecasting, particularly for random-length lumber, demonstrating the model's capability to predict future market trends accurately. The study highlights significant improvements in prediction accuracy and supply chain management through meticulous feature engineering and model optimization, offering valuable insights for strategic decision-making in the supply chain sector.

Cell identity is determined by chromatin structure and the profiles of gene expression, which are dependent on chromatin accessibility and DNA methylation of regions critical for gene expression, such as enhancers and promoters. These epigenetic modifications are required for mammalian development and are essential for the establishment and the maintenance of the cellular identity. DNA methylation was once thought to be a permanent repressive epigenetic mark, but systematic analysis in various genomic contexts reveals a more dynamic regulation than previously thought. In fact, both active DNA methylation and demethylation occur during cell fate commitment and terminal differentiation. To link methylation signatures of specific genes to their expression profiles, we have determined the methyl-CpG configurations of the promoters of five genes switched on and off during murine postnatal brain differentiation by bisulfite-targeted sequencing. We report here the structure of significant, dynamic and stable methyl-CpG profiles associated with silencing or activation of expression of genes during neural stem cell and brain postnatal differentiation. Strikingly, these methylation cores mark different mouse brain areas and cell types derived from the same areas during differentiation.

Objective: to retrospectively evaluate the incidence rate (IR) of echocardiographic signs suspected for pulmonary hypertension (PH) in Systemic sclerosis (SSc) patients after the introduction of a combination therapy with bosentan and sildenafil for treatment or prevention of digital ulcers. Methods: patients attending the Scleroderma Unit of the Universital Hospital of Careggi from July 2010 to July 2023 were enrolled. Patients older than 18 years old, with an history of digital ulcers, treated with bosentan and sildenafil in combination for at least 12 months were included. Patients with a diagnosis of PH preceding the introduction of the therapy were excluded. Demographical data, disease duration, laboratoristic and instrumental data (pulmonary function tests, echocardiographic estimation of pulmonary artery pressure (PAPs) and ultrasonographic value of renal resistive index) were collected. The IR of echocardiographic signs suspected for pulmonary hypertension and their 95% confidence interval were calculated in events/1000 patients-years.Results: forty-seven patients were enrolled; mean disease duration was 12,14 years (SD 5,87). Mean duration of the combination treatment was 78.33 (SD 41.37) months and total at-risk time was 3525 months. Two patients (4,2%) presented echocardiographic signs of PH (sPAP 50 mmHg and 40 mmHg); the IR was calculated to be 6.8/1000 patients-years (95% CI 6,02-7,7). In one of the 2 patients RHC excluded PAH, while the other patient refused to undergo to RHC and PAH could not be confirmed/excluded. A stability of PFTs and echocardiografic PAPs was observed during the observation time. Conclusions: the results of this retrospective study suggest that combination therapy with endothelin receptor antagonist and Phosphodiesterase-5 (PDE5) inhibitors could help in preventing PAH in SSc; prospective case-control studies on larger population are needed to improve knowledge in this field.

Part II, like Part I, discusses geometry, kinematics and statics in detail without taking into account power losses in meshing. The main goal of Part II, however, is to prove that there are complex and structurally coupled planetary gear systems, i.e. containing a closed circuit in which no circulation of power flow is generated. The power flow analysis is also carried out using the direct method, with a slight modification in the way of writing the equations identifying active and passive gears, i.e. at the same time the directions of power flow on all transmission paths. The analysed planetary gear system (PGS) is characterised by mobility equal to 1, i.e. single degree of freedom (DoF). It consists of three subsystems in the form of the 2KH type planetary units connected in series-parallel, specially selected to demonstrate the thesis of this paper. It consists of three subsystems in the form of single planetary subsystems of the 2KH type connected series-parallel, specially chosen to illustrate the thesis of this paper.

In the depths of inquiry, where thoughts unfurl like tendrils of smoke, this qualitative study ventures into the enigmatic realms of diaspora, migration, and the elusive brain drain within the tapestry of the Philippines. It is a journey guided by a sturdy theoretical framework, traversing the multifaceted dimensions of society, culture, and psyche. Here, the lens expands beyond the confines of economics, delving into the essence of these phenomena, seeking profound insights that dance beneath the surface. Through meticulous analysis of empirical data, hidden truths emerge, illuminating the intricate dynamics of diaspora, the intricate patterns of migration, and the intricate threads that shape migration decisions. Moreover, it peers into the intricate tapestry of impacts that diaspora and migration have on both sending and receiving societies, casting a beam of understanding upon their social, economic, and cultural implications. The study, in its wisdom, extends its reach to offer valuable policy recommendations, serving as a compass for stakeholders and decision-makers. It emphasizes the pivotal importance of harnessing the vast potential held within diaspora, fostering social integration, and bridging the gaps in knowledge that lie in wait. In its entirety, this research harmonizes with the existing body of knowledge, blending seamlessly with the symphony of understanding, and ignites the path towards evidence-based strategies that pave the way for sustainable development and the well-being of societies near and far.

Intersectional experiences, socio-cultural meanings, ethnic traditions and morals compound stigma-related stress (Jackson et al., 2020; Schmitz 2019). Sex workers are subject to various stigmatizing forces which can lead to secrecy, isolation and lack of social and cultural support (Koken 2012). Stigmatizing forces include structural humanitarian governance and aid interventions that conflate migration and sex work with insidious constraints and coercion. This study explored how migrant female sex workers from distinctive ethnic cultures manage their identity on a day to day basis in relation to the separation of work and home life. Methods: The perspectives of female sex workers were collected via a series of in-depth semi-structured interviews. The inclusion criteria were that the women had worked in sex work for over 18months, defined their involvement in sex work as voluntary, and were over 18yrs of age. The perspectives of seven women from South Asian (Pakistani), Brazilian, and British backgrounds were analyzed using Grounded Theory (Glaser and Strauss, 1967). Ethnicity was considered to explore how the women experienced stigma, how it impacted on the management of their identity, and how the process of change occurred. Results: The women used a variety of methods to maintain work and home life boundaries, processes they used switch into a role and all experienced stigma and tried to deal with it in ways such as concealment from friends and family. Two core categories and properties emerged from the data as participants felt guilt and/or shame but only the South Asian participants spoke of this with reference to their culture and religion. Conclusion: It was not migration per se but rather the relationship of migration to culture that was key to identity management. Participants reflected that as their country was considered collectivist country with interdependent thought, that any negativity felt could not only be reflected on the individual, but also the entire family. For these reasons Pakistani sex workers were subject to more complex stigmatizing forces, shame and guilt as regards risk and exposure. Discussion focusses on the processes and management strategies used to extend social and cultural support.

Due to the long duration and high cost of traditional pumping tests, the response of well water level to seismic wave, earth tide, and barometric pressure provides a feasible method for determining continuous changes in aquifer hydraulic parameters. Aiming at the problem that the response phase shift of well BB water level to tidal tide M2 is greater than that of tide O1, this paper preferentially calculated the time series changes of S, Be, n and BKu based on the response mechanism of well water level to barometric pressure and earth tide and with the help of smooth moving method. Then by using the mixed flow model, the variation of transmissivity and leakage coefficient over time were simultaneously obtained, and the evolution process and characteristics of aquifer parameters near well BB caused by the Wenchuan earthquake were ultimately discussed. The calculation results are basically consistent with the previous pumping test, and have been verified and compared by using other scholars' methods. This solving process avoids the problems such as excessive dependence on initial values, multiple solutions, and unstable tide O1, which has a promoting effect on the study of the impact of seismic activity on aquifer systems.

The aim of this study is to analyze the characteristics of drought such as intensity, cumulative curves and trends, based on SPEI (Standardized Precipitation Evapotranspiration Index) at 8 stations in Korea from 1981 to 2010. The traditional SPEI is based on Thornthwaite equation for estimating evapotranspiration; SPEI_th. However, a standard of agricultural water management in Korea suggests FAO Penman-Monteith equation; SPEI_pm. In this study, we analyzed the intensity and trends of drought using SPEI_th and SPEI_pm, respectively, and analyzed the relationship between them. Both of central and southern region, the SPEIs were below -1.0 (moderated drought) for the periods May-August in the representative drought year such as 1988, 2001, and 2008-09. The frequency of drought was higher in southern region than central region. In addition, SPEI_pm showed slightly more intensive drought rather than SPEI_th except for Chuncheon and Gwangju. In 5 stations except for Cheoncheon, Gwangju and Jinju, the cumulative probability that SPEI_pm is below -1.5 was significantly increased from 1981-1995 to 1996-2010. As the results of drought trends, the increasing trend of SPEIs was shown on fall season, and the cumulative probability that SPEI_pm is below -1.5 was also significantly increased.

The Jakarta LARP community, established in March 2020 and primarily active in Gelora Bung Karno, fosters inclusivity, diversity, and physical role-playing activities. It adheres to a policy of excluding ultra-nationalist ideologies and integrates new members despite language barriers. Bruhn (2011) defines this kind of community sharing the same goals, values, and lifestyles, while McMillan & Chavis (1986) outline four aspects of the sense of community.The research discovered that communities endure by utilizing solidarity built on the basis of their peculiarities. This study employed ethnographic methods alongside grounded research to identify the community's culture and their efforts to sustain and utilize it as community solidarity.

Monitoring the status and dynamics of desertification is one of the most important parts of combating desertification. In this study, 30m high-resolution information on land desertification and restoration in the HRB was extracted from the land cover database. The results indicate that land desertification coexists with land restoration in the HRB. At different periods, the area of land restoration is much larger than the area of land desertification in the HRB, and the HRB has been in a process of land restoration. Upstream of the HRB, there is a continuing trend of increasing land desertification associated with overgrazing in a context where climate change favors desertification reversal. In the middle and lower reaches, although both climate variability and human activities favor land desertification, the process of land desertification in the middle and lower reaches is still being reversed and land restoration dominates. The implementation of the Eco-Environmental Protection Project and desertification control measures, especially the EWDP, is contributing to the reversal of desertification in the middle and lower reaches of the HRB. However, the EWDP has indirectly led to the lowering of the water table in the middle reaches, resulting in local vegetation degradation. Therefore, there is therefore an urgent need to transform the economic structure of the middle reaches to cope with water scarcity and land desertification.

Signal approximation, is the basic idea of signal processing and mathematical analysis where complex signals can be represented with simpler ones. This paper explores unifying two mathematical fundamentals, Dirichlet-type problems, and hyperbolic series identities, into signal approximation. In this paper, we address a well-known classic topic in mathematical analysis - the Dirichlet problem - to improve (the approximation of) signal using Fourier series. We also discuss using hyperbolic series representations to increase signal modeling flexibility. In this way, we hope to create new links that span some distance along this dimension and result in a somewhat theoretical view of signal behavior - present with the mathematical rigor needed for speculation but absent from an understanding capable of appropriately handling real-world complexity. This paper provides a theoretical investigation of the mechanics at play and reveals by analogy how these mathematical tools can potentially advance signal processing techniques and understanding. This paper illustrates Fourier series and fuzzy logic methods by two case studies on signal processing, satellite communication and financial risk measurement. The first case study performs signal approximation using the Fourier series and hyperbolic function identities to provide insight into how signals behave and are modeled. The second case study deals with applying fuzzy logic for risk evaluation of investment portfolios, emphasizing the utility in evasion systems solving uncertainty and imprecision problems related to financial decisions.

The removal of non-climatic biases, so-called inhomogeneities, from long climatic records needs sophistically developed statistical methods. One principle is that usually the differences between a candidate series and its neighbour series are analysed instead of directly the candidate series, in order to neutralize the possible impacts of regionally common natural climate variation on the detection of inhomogeneities. In most homogenization methods, two main kinds of time series comparisons are applied, i.e. composite reference series or pairwise comparisons. In composite reference series the inhomogeneities of neighbour series are attenuated by averaging the individual series, and the accuracy of homogenization can be improved by the iterative improvement of composite reference series. By contrast, pairwise comparisons have the advantage that coincidental inhomogeneities affecting several station series in a similar way can be identified with higher certainty than with composite reference series. In addition, homogenization with pairwise comparisons tends to facilitate the most accurate regional trend estimations. A new time series comparison method is presented here, which combines the use of pairwise comparisons and composite reference series in a way that their advantages are unified. This time series comparison method is embedded into the ACMANT homogenization method, and tested in large, commonly available monthly temperature test datasets.

Education and heritage are fundamental to achieving sustainable development goals. Integrating heritage into education is crucial for cultivating children's connection to heritage and promoting sustainable development. However, the lack of a scientific framework to guide educational goals across age groups results in unclear integration. This study aims to develop a framework for cultural identity enlightenment within heritage education by conducting literature research and validating it through field observations in kindergartens. It identifies cognitive, emotional and behavioral dimensions, outlining the developmental trajectory of these goals. This framework illustrates how children's understanding progresses from direct experiences to deeper appreciation and creative involvement. It provides teachers with a tool to set goals that empower children as agents, fostering the emergence of cultural awareness and identity. This approach not only enhances cultural identity but also supports sustainable development by advancing the transmission and innovation of cultural heritage.

Art's unique style and creativity are essential in defining a work's identity, conveying emotions, and shaping audience perception. Recent advancements in diffusion models have revolutionized art design, animation, and gaming, particularly in generating original artwork and visual identities. However, traditional creative processes face challenges such as slow innovation, high costs, and limited scalability. Consequently, deep learning has emerged as a promising solution for enhancing painting-style creative design. In this paper, we present the Painting-Style Design Assistant Network (PDANet), a groundbreaking network architecture designed for advanced style transformation. Our work is supported by the Painting-42 dataset, a meticulously curated collection of 4,055 artworks from 42 illustrious Chinese painters, capturing the aesthetic nuances of Chinese painting and offering invaluable design references. Additionally, we introduce a lightweight Identity-Net, designed to enhance large-scale text-to-image (T2I) models by aligning internal knowledge with external control signals. This innovative Identity-Net seamlessly integrates image prompts into the U-Net encoder, enabling the generation of diverse and consistent images. Through extensive quantitative and qualitative evaluations, our approach has demonstrated superior performance compared to existing methods, producing high-quality, versatile content with broad applicability across various creative domains. Our work not only advances the field of AI-driven art but also offers a new paradigm for the future of creative design.

Brand visual identity is a critical component of brand image and impacts consumers' brand perception and attitude. Although scholars and practitioners have increasingly researched brand visual identity, most focus on brand communication and corporate management perspectives, necessitating a systematic review of consumer attitudes based on brand visual identity elements. This study aims to review the impact of brand visual identity on consumer attitudes and provide directions for future research. We conducted a systematic search using PRISMA guidelines, reviewed relevant articles published in four databases (Web of Sciences, ProQuest, Scopus, and Elsevier) in the past two decades (2004-2024), and obtained 559 articles in April 2024. We conducted a thorough peer-review of both theoretical and empirical journal articles, followed by a scoping review. Thirty-four studies were eligible, analysing consumers' perceptions of various core elements of brand visual identity (BVI) (such as brand logo, colour, name, typography, and font), as well as the impact of brand visual identity on consumer attitudes and the practical implications of brand management. The results show that the consumption of visual identification elements affects consumers' perceived brand quality, brand personality, brand satisfaction, loyalty, favourability, and so on., as well as purchase intentions and social attitudes. In summary, the findings indicate that brand visual identity elements impact consumer perceptions and attitudes. However, despite some progress, further research is necessary to arrive at more definitive and robust conclusions.

Increasing research has indicated a strong association between identity functioning and eating disorder (ED) symptomatology. However, a detailed investigation of identity throughout ED treatment is lacking. The present longitudinal study examined identity in inpatients with an ED and explored its co-development with ED symptomatology throughout treatment. At admission (Wave 1), 110 women with an ED (Mage=21, SD=6.08, range:14-45) participated, of whom 83.64% participated during treatment (Wave 2) and 55.45% at discharge (Wave 3). Questionnaires on identity synthesis, identity confusion, identity processes, and ED symptomatology were completed. Latent growth curve modeling was used to address the research questions. Throughout treatment, a decrease in identity confusion and an increase in identity synthesis and adaptive identity processes were found. Accordingly, increases in identity synthesis and identification with commitment were related to general decreases in drive for thinness and body dis-satisfaction. Similarly, such decreases in ED symptoms were related to general decreases in identity confusion and ruminative exploration. The present study points to an increase in identity functioning throughout treatment, and longitudinal associations between identity functioning and ED symptomatology were found. Helping the patient to decrease ruminative exploration and to increase identification with previously made life commitments seem important in ED treatment.

As a result of the COVID 19 outbreak that has affected the whole world, teacher leadership has gained more significance. Teacher leadership is a multidimensional concept. While some teachers exercise leadership only at the classroom level, others exercise leadership at macro level. This level of leadership enactment is directly related to how teachers construct their professional identity in relation to leadership. This study aims to explore the leadership-related professional identities of teachers who came to the fore especially during the COVID 19 pandemic period by using the latent profile analysis method. The data were collected a sample of 710 teachers. Teachers completed Teacher Leadership Behavior Scale that measures teacher leadership behaviors at four levels: classroom, parental, micro-level, macro-level. Participants also completed Rosenberg Self-Esteem Scale, Teacher Self-Efficacy Scale, Openness to Authority Scale, and Job Satisfaction Scale. As a result of latent profile analysis, three distinct profiles of teacher leadership identity emerged: those who exercise leadership at a minimum level, an intermediate level and a maximum level across all four levels of teacher leadership. These profiles were labeled as "extended professionality," "intermediate professionality," and "restricted professionality," drawing upon Hoyle's (1974) conceptualization of teacher professional identity. These findings suggest that teachers construct their identity differently about teacher leadership. It is essential for school leaders to first explore those different levels of professional identity and tailor their professional development activities accordingly.

The territory of Serbia is vulnerable to various types of natural and man-made disasters. The risk is not equal across the entire territory, depending on the type of hazard and the expected potential for damage. So far, the level of community disaster resilience has not been determined in Serbia. There are no scientific preconditions for its improvement to reduce the future material and intangible consequences of disasters. Regarding that, the project’s main objective is to develop and validate a predictive model of community disaster resilience based on social identity influences through an investigation impact of social identity indicators on the level of community disaster resilience in Serbia. The project is based on the upcoming research on whether the level of community disaster resilience can be predicted based on social identity indicators, how social identity indicators affect different dimensions of community disaster resilience, and how disasters shape social identity. The project is based on multimethod research in which quantitative (face-to-face interviews in 40 of the 191 municipalities), and qualitative (semi-structured interviews) research methodology will be applied. A developed predictive model with an index of community disaster resilience in Serbia will empower the creation of preconditions for designing public policies, strategies and procedures for improving resilience and reducing the consequences of disasters on people and their property and enhancing citizens’ security. The project will encourage the prediction of community disaster resilience based on social identity indicators, improving disaster foresight and preparing to limit disaster losses. Based on the development of analytical frameworks for understanding community disaster resilience and social identity in disasters, essential preconditions for designing innovative information systems will be created to enable local communities to increase their level of resilience.

Calcium-activated chloride secretion in epithelial tissues described for many years. However, the molecular identity of the channel responsible for the Ca2+-activated Cl− secretion in epithelial tissues has remained a mystery. More recently, TMEM16A has been identified as a new putative Ca2 -activated Cl- channel (CaCC),. The primary goal of this article will be to review the characterization of TMEM16A, as it relates to the physical structure of the channel, as well as, important residues that confer voltage and Ca2+-sensitivity of the channel. This review will also discuss the role of TMEM16A in epithelial physiology and potential associated-pathophysiology. This will include discussion of developed knockout models that have provided much needed insight on the functional localization of TMEM16A in several epithelial tissues. Finally, this review will examine the implications of the identification of TMEM16A as it pertains to potential novel therapies in several pathologies.

Introduction: Left ventricular dysfunction in an independent predictor of mortality in Chagas disease. Global longitudinal strain (GLS) is an emerging echocardiographic modality with possible incremental value in early detection of cardiac involvement. Objective: Compare left ventricular function with multiple echocardiographic parameters between patients with the indeterminate and chronic forms of Chagas and perform a literature review. Methods: In this observational study, 11 patients with a confirmed diagnosis of Chagas disease were evaluated. Individuals were distributed as follows: 5 with the indeterminate and 6 with the chronic forms. Conventional echocardiographic evaluation was followed by GLS measurement. Results: The mean left ventricle ejection fraction LVEF was 33 ± 2.88 and the mean GLS of the left ventricle was - 10.76 ± 2.20 in the chronic form as compared to 57.80 ± 6.49 and - 17.34 ± 3.82, respectively in the indeterminate group. Contractility was reduced in segments of the inferior, inferoseptal and anteroseptal walls in both groups. Conclusion: Analysis of longitudinal strain in the indeterminate form has potential incremental value to the conventional analysis of ejection fraction when compared to patients with chronic Chagas cardiomyopathy, especially with individual segmental analysis but the impact and clinical significance of these techniques is still unknown.

In this paper we discuss a problem of generalization of binomial distributed triangle, that is sequence A287326 in OEIS. The main property of A287326 that it returns a perfect cube n as sum of n-th row terms over k; 0 ≤ k ≤ n−1 or 1 ≤ k ≤ n, by means of its symmetry. In this paper we have derived a similar triangles in order to receive powers m = 5; 7 as row items sum and generalized obtained results in order to receive every odd-powered monomial n^2m+1; m ≥ 0 as sum of row terms of corresponding triangle. In other words, in this manuscript are found and discussed the polynomials D_m(n,k) and U_m(n,k), such that, when being summed up over k in some range with respect to m and n returns the monomial n^2m+1.

In contemporary narratives, the rural and regional identities of a place, as judged by its inhabitants’ sense of belonging, continue to be important points that need to be (re)considered when discussing places as instruments for local development. This paper pushes forward these debated and explores the construction of rural and regional identity in Romania with the help of a case study that focuses on two rural communities situated on opposite sides of the river Mureș. Based on participant and ethnographic observation and making use of a qualitative analysis, this paper highlights the most significant features of the local cultural identities expressed by the two sets of people, which often coincide with the most important characteristics attributed to the regions separated by the river Mureș. The results of this study underline the dividing role of a river in the preservation of rural and regional identity. They also demonstrate that rural identity construction along the river has generated both rural development opportunities and various risks.

The aim of this study was to study the effect of leisure identity, flow, satisfaction, and re-participate intention among outdoor leisure activity participants in South Korea. Due to the recent COVID-19 pandemic, there has been a tendency to more frequently participate in outdoor leisure activities as opposed to indoor leisure activities. Leisure activities bestow various benefits. Therefore, this study was used to analyze the relationships amongst leisure identity, flow, leisure satisfaction, and re-participate intention among various theories about leisure. The participants in this study were collected from amongst 369 people who were frequent participants in outdoor leisure activities. For the data analysis, the researchers used frequency, confirmatory analysis, reliability, correlation and structural equaling modeling. The findings were as follows: First, leisure identity had wielded an influence on leisure flow. Second, leisure identity had influence leisure satisfaction. did not have any significant influence on recreation specialization. Third, leisure identity had influence on re-participate intention. Fourth, leisure flow did not have any significant influence on leisure satisfaction. Fifth, leisure flow did not have any significant influence on leisure satisfaction. And finally, leisure satisfaction had an influence on re-participate intention. In the era of the COVID-19 pandemic, a new leisure identity has been formed, and it is believed to be a new study on leisure flow, leisure satisfaction, and re-participation intention. This study aims to provide basic data for constructing infrastructure to enable continued participation in outdoor sports in Korea.

Here, satellite images from 2006 to 2022 were collected to assess changes in the sandbar topography of the Nakdong River Estuary region, southeast of South Korea. The employed method of satellite image acquisition involves capturing images at the same time each year to facilitate a comparison of topographical changes over time. The shorelines of the islands in the study area, including Jinwoo Island, Shinja Island, and Doyo Sandbar, were analyzed. Shoreline analysis was performed using the digital shoreline analysis system (DSAS) package in ArcGIS. The results indicate that Jinwoo Island is expanding at 6.46 m/year in the direction of Nulcha Island. The western side of Shinja Island is expanding at 4.76 m/year, whereas the eastern side is retreating at a rate of 24.41 m/year. In the case of the Doyo Sandbar, the southern shoreline is retreating at a rate of 14.69 m/year; however, the speed is gradually decreasing. Marked topographical changes are evident in the Nakdong River Estuary, and the interlinked barrier islands undergo deposition and erosion, leading to alterations in the shoreline. These findings serve as foundational data for predicting and addressing environmental and social issues arising in the Nakdong River Estuary region due to climate change.

In contemporary society, organizations increasingly prioritize ESG (Environment, So-cial, Governance) management to generate social value alongside profit-seeking. This commit-ment to social responsibility plays a positive role for organizational members, contributing to overall organizational growth This study explores the impact of perceptions of ESG management within public sports organizations on organizational civic behavior and proposes strategies for improving management and attachment, with the goal of fostering a more sustainable and so-cially responsible organizational culture. A survey involving 343 employees from govern-ment-affiliated public sports organizations in South Korea was conducted. Structural equation modeling, coupled with dual mediation analysis, unveiled that the perceived performance of ESG management significantly relies on both social value orientation and organizational identifica-tion to drive organizational civic behavior, confirming complete mediation effects. These findings underscore ESG management's ability to foster social value orientation and organizational iden-tification, thereby bolstering organizational civic behavior and significantly shaping the culture and conduct of public sports organizations. This research offers valuable insights for upholding organizational social responsibility and ensuring sustainable development within such organi-zations.

Background: There is a lack of literature specifically examining the workplace bullying of apprentices and trainees in traditional, male-dominated sectors such as the Australian building and construction industry. Using social identity theory (SIT), the aim of this study was to gather the attitudes, thoughts, and feelings of construction industry leaders to better understand how social identification (i.e., group membership) impacts bullying on targets and perpetrators, and the willingness to report bullying for targets and bystanders. Method: One-on-one, semi-structured interviews using a purposive sample of eight leaders from construction and blue-collar industries. Qualitative data were analysed using reflexive thematic analysis. Results: Four overarching themes were identified: difficulties for apprentices transitioning into industry, the need for continued improvement to industry culture, reluctance to report bullying, and rethinking apprenticeships to empower. Each theme provides insight into the psychosocial phenomenon of the bullying of trade apprentices and suggests that an apprentices’ level of social identification with work groups shapes how bullying is identified, interpreted, and prevented. Conclusion: Findings from this study will be important for tailoring evidence-based interventions, human resource policies and initiatives for education and awareness training. Themes also highlight systemic inadequacies impacting apprentices’ mental health and skill development, with implications for the future sustainability of apprenticeship training agreements.

After 29 years of clinical practice treating odontogenic infections of the head, neck and oral cavity, my co-contributors and I sought to determine by a review of the literature and three clinical cases if Prevotella species were significant opportunistic pathogens in odontogenic infections of all kinds in the oral and maxillofacial region. We performed a PubMed review of 40 articles using terms associated with odontogenic infections, pericoronitis, Prevotella and antibiotics used to treat common oral and maxillofacial infections. Three cases were reported, and the treatment was discussed. An additional 26 articles were reviewed to describe the pathogenesis of Prevotella. Given the opportunity to become virulent—such as post-extraction wound healing of an extraction site adjacent to an intact dentition, excessive plaque and calculus, nearby gingivitis or periodontitis, or an immunocompromised host—we wondered if Prevotella could be targeted with antimicrobials mitigating, or even resolving, odontogenic infections in those cases refractory to conservative surgical therapy that includes source control. We found that Prevotella is a significant opportunistic pathogen in odontogenic infections. Prevotella is susceptible to Metronidazole (Flagyl), and it is effective in mitigating the disease process when basic principles of the treatment of odontogenic infections are employed. Infections not responsive to this empiric therapy should be cultured to determine the opportunistic organism’s sensitivity and susceptibility to specific antibiotic therapy.

Incarceration negatively affects well-being and can shift an individual’s identity through labeling theory and prisonization. Seven incarcerated girls at a juvenile residential facility were administered self-esteem and life satisfaction questionnaires, and interviews were conducted to assess the impacts of incarceration on happiness and well-being. Afterwards, an eight-week music program was implemented. Results indicated that life satisfaction was significantly lower than self-esteem (p = .037), yet all participants expressed an optimistic outlook on their future in their interviews, sharing a desire to pursue further education. Participant feedback following the music program suggests positive impacts on their emotional state and well-being.

Heat index (HI) is a biometeorological indicator that combines temperature and relative humidity. This study aimed to investigate the relationship between heat index and daily counts of diarrhoea hospitalisation in Dhaka, Bangladesh. Data on daily diarrhoea hospitalisations and meteorological variables from 1981–2010 were collected. We categorised heat index of >94.3°F, >100.7°F and >105°F as high, very high and extremely high heat index, respectively. We applied time-series adjusted generalised linear model (GLM) with negative binomial distribution to investigate the effects of heat index and extreme heat index on hospitalisations for diarrhoea. Effects were assessed for all ages, <5 children and by gender. A unit higher HI, and high, very high and extremely high HI were associated with 0.8%, 8%, 7% and 9% increase in diarrhoea hospitalisation in all ages, respectively. The effects varied slightly by gender and were most pronounced in <5 children with a rise of 1°F in high, very high and extremely high HI associated with a 14.1% (95% CI: 11.3% – 17.0%), 18.3% (95% CI: 13.4% – 23.5%) and 18.1% (95% CI: 8.4% – 28.6%) increase of diarrhoea, respectively. This suggest that heat index may serve as an alternative indicator for measuring the combined effects temperature and humidity on diarrhoea.

We propose a novel approach for time series forecasting with many predictors, referred to as the GO-sdPCA, in this paper. The approach employs a variable selection method known as the group orthogonal greedy algorithm and the high-dimensional Akaike information criterion to mitigate the impact of irrelevant predictors. Moreover, a novel technique, called peeling, is used to boost the variable selection procedure so that many factor-relevant predictors can be included in prediction. Finally, the supervised dynamic principal component analysis (sdPCA) method is adopted to account for the dynamic information in factor recovery. In simulation studies, we found that the proposed method adapts well to unknown degrees of sparsity and factor strength, which results in good performance even when the number of relevant predictors is large compared to the sample size. Applying to economic and environmental studies, the proposed method consistently performs well compared to some commonly used benchmarks in one-step-ahead out-sample forecasts.

The anomaly detection task is very important in computer science. And there are a lot of anomaly detection methods. Different from some thresholding methods, some unsupervised methods could make us get more accurate and faster result, which is the object of the project. In this paper, I tried to use EWMA and some other methods in two datasets: Webank time consuming indicators dataset and AIOps Challenge dataset. The paper consists nine parts: background of the project, related work, description of algorithms, implementation details, experimental setup and data sets used, experimental results and discussion, future directions, reference and meeting notes.

This paper proposes a novel approach to transitioning the classical TLS 1.3 protocol to a post-quantum version with minimal changes to the existing infrastructure. By integrating a hybrid KEMTLS protocol with Identity-Based Encryption (IBE), the solution achieves post-quantum security without incorporating post-quantum keys into TLS certificates. This enables the protocol to function with Certificate Authorities that do not support post-quantum keys, ensuring its security while simplifying the transition. The main challenge addressed is the immediate need for support of post-quantum algorithms by Certificate Authorities and servers. The proposed solution leverages existing certificates and keys, facilitating a smoother transition.

Abstract: Integration of Medical Cyber Physical Systems (MCPS) and Internet-of-Medical Devices (IoMT) with conventional hospital networks have facilitated easy and speedy data collection, vertical and horizontal connectedness and collaborations among healthcare providers. Federated identity management (FIM) provides a solution towards the identity management challenge arising from this integration of millions of MCPSs to get personalized care and frictionless experiences for the patients, doctors, and employees. FIM protocols such as OAuth, Security Assertion Markup Language (SAML) are highly susceptible to cyber attacks like theft of barrier token, replay attack, message insertion, and Man-in-Middle attacks. IoMT devices have vulnerabilities in their firmware, operating systems, data encryption, data at store and data transmission. Combined vulnerabilities of FIM framework and IoMT devices creates major cyber risks for the current digital healthcare system. Therefore, a comprehensive and evidenced based cyber risk assessment is an urgent need for a cyber-safe digital health care system that can avoid frequent life threatening situations. This paper proposes a comprehensive and evidenced based cyber risk assessment approach for FIM and IoMT based collaborative digital healthcare systems. The novelty of the proposed approach is that it considers three dimensional vulnerabilities arising from existing IT communication protocols and infrastructure, IoMT and MCPS medical devices, protocols of FIM and their combined impact on hospitals and provides corresponding recommendations of security controls. The proposed approaches combine two industry standards including Cyber Resilience Review (CRR) asset management, NIST SP 800-30 to take advantage of both approaches. We have used a large number of IoMT and MCPS devices from multiple providers for threat modelling and produced evidence based cyber-risks using attack trees and detailed attack sequence diagrams to validate proposed approaches. The corresponding recommendation of security controls will support healthcare professionals and providers significantly for improving both the patient and medical device safety management within the FIM enabled healthcare ecosystem.

It is not understood how the numbers and identities of vertebrae are controlled during mammalian development. The remarkable robustness and conservation of segmental numbers may suggest a digital nature of the underlying process. Here I propose a mechanism that allows cells to obtain and store the segmental information in digital form, and to produce a pattern of chromatin accessibility that in turn regulates Hox gene expression specific to the metameric segment. The model requires that a regulatory element be present such that the number of occurrences of the motif between two consecutive Hox genes equals the number of segments under the control of the anterior gene. This is true for the recently discovered HRC3 motif, associated with histone modifications and developmental genes. The finding not only allows correctly predicting the numbers of segments using only sequence information, but also resolves the 40-year-old enigma of the function of temporal and spatial collinearity of Hox genes. The logic of the mechanism is illustrated in an animated video: https://youtu.be/4a3XOQ7Lz28. I also discuss how different aspects of the proposed mechanism can be tested experimentally.

Identity is the basis and foundation of the cultural landscape. Despite the emphasis of international documents and charters on its various aspects and necessity, today, the cultural landscape is threatened by extinction due to changes of many parameters. Accordingly, it is crucial to find an approach that can sustain cultural identity and its values in the changing world of the twenty-first century. Given the qualitative and the changing nature of cultural identity, achieving an approach which can lead to its continuation is not straightforward. By reviewing and analyzing international conventions and documents, on the one hand, and expert opinions, on the other hand, the present study, therefore, aimed to find out how the approach of cultural landscape values conservation can lead to the continuation of cultural identity in the natural and cultural heritage of Uraman Takht. This paper employed qualitative research methods as a basis for data collection and analysis, which primarily involved the use of content analysis along with field observations and interviews with stakeholders and indigenous residents.

Using the method of the beta function, Sun has recently evaluated some series of the type $\sum_{k=0}^{\infty}(ak+b)x^k/\binom{mk}{nk}$. By factorization of the polynomial $t^{m-n}(1-t)^n-x$, we will give a general method to find new $\pi$-series.

We prove that the Legendre coefficients associated with a function f(x) can be represented as the Fourier coefficients of a suitable Abel-type transform of the function itself. Thus, the computation of N Legendre coefficients can be performed efficiently in O(NlogN) operations by means of a single Fast Fourier Transform of the Abel-type transform of f(x). We also show how the symmetries associated with the Abel-type transform can be exploited to further reduce the computational complexity. The dual problem of calculating the sum of Legendre expansions is also considered. We prove that a Legendre series can be written as the Abel transform of a suitable Fourier series. This fact allows us to state an efficient algorithm for the evaluation of Legendre expansions. Finally, numerical tests are presented to exemplify and confirm the theoretical results.

Perceived peer support is a critical factor in the academic adjustment of higher vocational college students. While previous studies have explored this relationship, few studies have delved into the underlying mechanisms. This study surveyed 9782 students from 35 higher vocational colleges in 13 provinces and cities in China to explore the relationship and mechanisms between perceived peer support and academic adjustment. Drawing on Conservation of Resources theory and Social Support Resource theory, the findings revealed that perceived peer support not only directly predicted the academic adjustment of higher vocational college students, but also indirectly through the independent mediating effect of academic hope and professional identity, as well as the chain-mediating effect of academic hope to professional identity. Additionally, students from vocational high schools showed a more significant increase in academic hope due to perceived peer support compared to those from general high schools, highlighting the moderating effect of educational background. The study provided a new theoretical perspective for understanding the complex mechanisms of academic adjustment in students and offers valuable guidance for educational practice, emphasizing the importance of fostering perceived peer support, academic hope, and professional identity in higher vocational education.

Architecture plays a crucial role in expressing identities. This study aims to create a model of sustainable continuity of cultural heritage as an approach to study architectural identity in Erbil City. The study combined visual analysis using graphical representation, analysis of previous studies, field surveys, and questionnaire surveys as methods of data collection. The rationale behind selecting Erbil City is related to its unique sustainable developments related to its cultural heritage through the ages, as the oldest continiously inhabited city in the world. The proposed model revealed a strong correlation between independent variables that represent cultural heritage frameworks of (typo-morphology of house layouts and façade, sociocultural factors, sustainable development factors) and the (continuity of architectural identity in houses situated in Erbil city) as a dependent factors. The regression analysis demonstrated that the most effective factor contributing to the continuity of the architectural identity of houses in Erbil city is the physical characteristics related to the typo morphology of the house's plan layout. The study revealed a comprehensive model that includes the relation between inherited and created sustainable elelments related to cultural heritage that effects on the continuity of architectural identity.

The purpose of this study was to investigate the relationships among student athlete’s identity and mental health during the COVID-19 pandemic. In addition, this study aimed to clarify the relationship between perceived social support from teammates and mental health in student-athletes. Two studies were conducted to investigate to clarify the mental health states of student-athletes in Japan during the COVID-19 pandemic. In Study 1 conducted in April 2020, the participants were 402 male student-athletes, and examined the relationships among student-athlete’s identity and mental health. The results of correlational analyses indicated that there were significant negative correlations between degree of student-athlete’s identity and depression and sports helplessness. In Study 2 conducted in March 2021, the participants were 136 male student-athletes, and examined the relationship between perceived social support from teammates, student-athlete’s identity and mental health. The results indicated that there was significant correlation among social support, student athlete’s identity and mental health. These results suggested that mental health may be improved if student-athletes are strongly aware of their social identity, which is their social role, when unforeseen events such as the COVID-19 pandemic occur. In addition, social support provided by significant others such as teammates may contribute to the improvement of mental health.

Color change is the most obvious characteristic of tomato ripening stage and an important indicator of tomato ripening condition, which directly affects the commodity value of tomato. To visualize the color change of tomato fruit in mature stage, a gated recurrent unit network with an encoder-decoder structure that dynamically simulates tomato growth and development with time-dependent lines using tomato color and shape as real-time data was proposed in this paper. Firstly, the .json file was converted into a mask.png file, the tomato mask was extracted, and the tomato was separated from the complex background environment, and the tomato growth and development data set was successfully constructed. Then, a network of gated recurrent units with encoder-decoder structure was constructed to predict the future growth trend of tomato under different greenhouse temperatures. The experimental results showed that for the gated recurrent unit network of encoder-decoder structure proposed, when the hidden layer number was 1 and hidden layer number was 512, a high consistency and similarity between the model predicted image sequence and the actual growth and development image sequence would be realized, and the structural similarity index measure was 0.746. It was proved that when the average temperature was 24.93℃, the average soil temperature was 24.06℃, and the average light intensity was 11.26 Klux, the environment was the most suitable for tomato growth. The environmental data-driven tomato growth model was constructed to explore the growth status of tomato under different environmental conditions, thus to understand the growth status of tomato in time. The statement provided a theoretical foundation for determining the optimal greenhouse environmental conditions to achieve tomato maturity. And it offered recommendations for investigating the growth cycle of tomatoes, as well as technical assistance for standardized cultivation in solar greenhouses.

In analogy with entanglement in physics, the concept of entanglement has been developed in mathematics as a symmetry to build upon as a tool to study 'proximity' relations between different number sequences and series in a unifying way. Examples of entanglement are shown. A general algorithm for detecting entangled sequences/series is given in the appendix. The novelty of this paper is to propose the concept of entanglement as a tool to study different sequences and se-ries-series phenomena. To enable useful treatment suggested by Poincaré.

The purpose of this project is to explore the potential of Long Short-Term Memory (LSTM), a type of recurrent neural network (RNN), as a tool for making directional predictions for assets. The focus will be on using LSTM for classifying up/down moves in stock indices, stocks, and FX rates (EUR/USD). Various financial ratios, advanced technical indicators, and volatility estimators will be used as features to enhance the predictive power of the model. Incorporating credit spreads and news indicators can also improve the model. The advantage of LSTM is its ability to handle sequences of arbitrary length, which means that longer time frames such as 5-day, 10-day, or 1-week returns can be used for prediction. Before using RNNs, exploratory data analysis (EDA) will be performed to understand the underlying patterns in the data. This may include dimensionality reduction techniques such as autoencoding, self-organizing maps, or decision tree regression. The results of the EDA will be used to guide the selection of features for the LSTM model. It is important to note that long memory and stationarity are common characteristics of time series data, such as interest rates or economic indicators. Power-law autocorrection, Hurst exponent fractional, or Markov processes may be used to model these data. Predicting 5-day, 10-day returns for equities or 1-week, 1-month returns for financial factors presents two challenges. First, a large amount of data is required, typically 7–10 years of data. Second, positive autocorrelation in the 5-day or 10-day returns in equity time series must be isolated.

We study the problem of predicting time series data using the autoregressive integrated moving average (ARIMA) model in an online manner. Existing algorithms require model selection, which is time consuming and inapt for the setting of online learning. Using adaptive online learning techniques, we develop algorithms for fitting ARIMA models with fewest possible hyperparameters. We analyse the regret bound of the proposed algorithms and examine their performance using experiments on both synthetic and real world datasets

Introduction: Neonatal mortality has declined in Cambodia but remains a key contributor to under-five deaths. The aim of this study was to further understanding of potential factors contributing to high neonatal mortality rates in Cambodia through assessment of verbal autopsies collected following newborn deaths. The study team analyzed verbal autopsies of perinatal deaths in order to describe timing and causes of neonatal deaths, demographic data, and factors potentially related to mortality. Methods: The case series data derive from 13 verbal autopsy reports collected in rural southern Cambodia. The mortality review was nested within a trial of a behavioral intervention to improve newborn survival, and was conducted after the close of the trial. The study examined all neonatal deaths occurring to infants born at 16 health centers between in the study site of Takeo province. The World Health Organization standardized definition of neonatal mortality was employed, and two pediatricians independently reviewed data collected from each event to assign a cause of death. Results: Thirteen newborn deaths of infants born at a health facility were reported during the time period February 2015–November 2016. Ten out of the 13 deaths (76.92%) were early neonatal deaths, two (15.38%) were late neonatal deaths, and one was a stillbirth. Five out of 13 deaths (38.46%) occurred within the first day of life, indicating death was likely due to an intrapartum event. The largest single contributor to mortality was neonatal sepsis; six of 13 deaths (46.15%) were attributed to some form of sepsis. Twenty-three percent of the deaths were attributed to asphyxia. Other causes of death included stillbirth and prematurity. Eight deaths (61.54%) occurred within the control group of the larger intervention study. Conclusion: The study highlights the continuing need to improve both intrapartum and postnatal quality of care and infection prevention and control, and to fully address causes of sepsis, in order to effectively reduce mortality in the newborn period.

Time irreversibility, i.e. the lack of invariance of the statistical properties of a system under time reversal, is a fundamental property of all systems operating out of equilibrium. Time reversal symmetry is associated with important statistical and physical properties and is related to the predictability of the system generating the time series. Over the past fifteen years, various methods to quantify time irreversibility in time series have been proposed, but these can be computationally expensive. Here we propose a new method, based on permutation entropy, which is essentially parameter-free, temporally local, yields straightforward statistical tests, and has fast convergence properties. We apply this method to the study of financial time series, showing that stocks and indices present a rich irreversibility dynamics. We illustrate the comparative methodological advantages of our method with respect to a recently proposed method based on visibility graphs, and discuss the implications of our results for financial data analysis and interpretation.

Background: Identity diffusion plays a central role in the onset of borderline personality and disorders. The Dialectical Behavioral Therapy for Adolescents (DBT-A) is a treatment program for adolescents with emotional instability and dysregulation. The interest of this study is to examine the influence of a standardized and certified DBT-A therapy program on identity development of adolescents with emotion dysregulation in an inpatient setting. Methods: 138 adolescents aged 13 to 18 years with symptoms of emotional instability were assessed before and after a curricular 12-weeks in-patient DBT-A program with standardized instruments for the assessment of identity (AIDA), emotion regulation (FEEL-KJ, SEE) and general psychopathology (SCL-90-R, DIKJ). Results: The results indicate a significant change in identity development, emotion regulation and general symptoms of psychopathology after treatment with DBT-A. A connection between identity scales and psychopathological symptoms of adolescents with diagnosed borderline disorders and impaired emotion regulation could be established. Conclusion: In this large sample of adolescents, DBT-A significantly improved identity and reduced identity diffusion. As identiy disturbance is a core symptom of borderline personality disorder, our results may become clinically relevant for the prevention of personality disorders in emotionally unstable adolescents

In this manuscript, I build and expand on prior work by myself (Author 2016) and others exploring the dynamics of embodiment among people with chronic health conditions. Specifically, I critically investigate the intersecting social and medical elements of responses to bodies perceived as too thin and otherwise lacking in physical ability, using my own experiences of living and aging with cystic fibrosis (CF) as a case example. In these explorations, I center gendered identity and its intersection with disabling physical illness. I do so by using my own lived experiences as autoethnographic anchor points to guide critical review of key concepts from the nexus of these two content areas. I focus throughout on exploring how others’ reactions to a frail-looking body often constitute a form of forced gendering via the narratives people attempt to construct for why a person’s body appears that way. The title of the manuscript supports this framework by referencing three cornerstones of patient experience in the CF community: the general trend of patients having salty skin due to the pathology of the disease, a prior embodiment project called Salty Girls (Pettigrew 2012) that engages this idea, and the more abstract concept of “saltiness” in describing the grit marginalized people display in responding to microaggressions.

Time series forecasting has been a challenging area in the field of Artificial Intel-ligence. Various approaches such as linear Neural Networks, Recurrent Linear Neural Networks, Convolutional Neural Networks and recently Transformers have been attempted for the time series forecasting domain. Although, Trans-former-based architectures have been outstanding in the Natural Language Pro-cessing domain, especially in autoregressive language modeling, the initial at-tempts to use transformers in the time series arena have met with mixed success. One of the recent papers demonstrated that modeling the multi-variate time se-ries problem as independent channels on a transformer architecture produced lower mean square and mean absolute errors on benchmarks, however, another recent paper claimed that a simple linear neural network out-performs previous approaches including transformer-based designs. We investigate this paradox in detail comparing the linear Neural Network and Transformer based designs, provide insights to why a certain approach may be better for a particular type of problem. We also improve upon the recently proposed simple linear Neural Network based architecture by using dual pipelines with batch normalization and reversible instance normalization. Our enhanced architecture outperforms all existing architectures for time series forecasting on majority of the popular benchmarks.

(1) Background: Hemispherotomy is the generally accepted treatment for hemispheric drug resistant epilepsy (DRE). Lateral or vertical approaches are performed according to the surgeon's preference. Multiples technical variations have been proposed since Delalande first described his vertical technique. We propose a sub-insular variation of the vertical parasagittal hemispherotomy (VPH) and describe our case series of patients operated on with this procedure. (2) Methods: a continuous series of patients operated on by the senior author (CR) with the modified sub-insular VPH was retrospectively analyzed. We report the demographic pre-operative characteristics, epilepsy and functional outcome as well as the surgical complications.(3) Results: Twenty-five patients were operated on between August 2008 and August 2023, twenty-three of them have at least a 3-month follow-up. On this last group 86,3% of patients were seizure-free. Only two patients developed post-operative hydrocephalus (8.7%), all patients with autonomous preoperative walk and 86,3% of the total series were able to walk without assistance (86.3%) and perform adapted social activities at last follow-up.(4) Conclusion: The modified vertical parasagittal sub-insular hemispherotomy is a successful surgical technique for hemispheric DRE with seizure freedom rates similar to the biggest series reported in the literature. Compared to other series, patients operated with our modified technique had a lower rate of postoperative hydrocephalus and excellent long-term motor and cognitive outcome.

Due to increase demand of food grain in the world, assessment of yield before actual production is important in making policies and decisions in agricultural production system. For a large area, forecast models developed from vegetation indices derived from remote sensing satellite data possesses the potential to give quantitative and timely information on crops over large areas. Different vegetation indices are being made used for this purpose, however, their efficiency in estimating crop yield is needed to be certainly tested. In this study, wheat yield forecast was derived by regressing ground truthing yield data against time series of spatial vegetation indices for the 2013 to 2019 growing seasons. These spatial vegetation indices derived from Landsat 8 image data: Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI) were compared to evaluate the most appropriate index that performs better in forecasting wheat production at Karcag, Kunhegyes and Ecsegfalva settlements in Jász-Nagykun-Szolnok county, in the Northern Great Plain region of central Hungary. The best time for making wheat yield prediction with Landsat 8- SAVI and NDVI was found to be the beginning of ripening period (160th day of the year) with higher correlation between the vegetation indices and the wheat yield. The validation results revealed that the model from SAVI provides more consistent and accurate forecasts yield compared to NDVI. The SAVI model forecast yield for the validation years, 2018 and 2019 were within 6.00% and 4.41% of the final reported values while that of NDVI model were within 8.31% and 6.27%. Nash-Sutcliffe efficiency index is positive with E1= 0.99 for the model from SAVI and for NDVI, E1=0.57, which connote that the forecasting method developed and evaluated performs acceptable forecast efficiency.

This study delves into heterosexual identity-behavior discordance, exploring the interaction between sexual identification and behavior in U.K. Analyzing representative 2010 data from the British population (N=12,472), the research categorizes participants into different groups: nonheterosexual, concordant heterosexual, and three discordant heterosexual categories (closeted, experimenters, and desisters). These groups were compared in terms of sociodemographics, attitudes towards sexuality, risk behaviors and health indicators. Discordance was associated with permissive social attitudes, including behaviors such as adultery and one-night stands, and with increased substance abuse and risky sexual behaviors, especially among the closeted. Surprisingly, physical and mental health of discordant heterosexuals was similar to concordant heterosexuals, in contrast to the poorer health of nonheterosexuals. Due to the significant variations in lifestyles and health indicators among different groups, this study highlights the importance of providing targeted services and interventions.

Fault detection at the early stage of development is of great importance in the maintenance of electric motors. In this regard, Motor Current Signature Analysis (MCSA) is cited in many articles to detect rotor bar fracture. The popularity of MCSA is due to its non-invasive and non-destructive nature, simplicity, and, compatibility with several signal processing tools. The vast variety of the signal processing tools which are commonly used for detecting the broken rotor bar fault is based on the Fast Fourier Transform (FFT) of the stator current signal and analysis of the produced Fourier spectrum; however, because of the small amplitude at the fault frequency relative to the main frequency amplitude, the former cannot be easily discriminated from the latter. Therefore, the peak at the fault frequency is hidden in the shadow of the main frequency component, hence the fault will not be detectable. As a solution to vanish the base frequency component, a method based on the Algebraic Identity of trinomial expansion is proposed in this paper which enables us to display the difference between the frequency of the fault signature and the base frequency. In this article, the fault of the broken rotor bars of the squirrel cage induction motor is revealed by the proposed method. In addition, a frequency weighting technique is presented to magnify the component at the fault related frequency compared to the lower frequencies. To validate the proposed methods, they are examined on the laboratory data obtained from three different operating conditions including the direct online start, the direct torque control, and the scalar control and the results show the ability of the proposed methods in fault detection of an induction motor.

Foot pain related to the plantar fascia is common in adults regardless of athletic background. Many pathologies can lead to the diagnosis of plantar enthesopathy, but the most relevant to this case study is related to structural defects within the plantar fascia. Due to the variety and sometimes unclear etiology of plantar fasciosis, no single standard of care treatment protocol is recognized. Often, patients receive NSAIDs, night splints, taping, physical therapy, foot orthosis, and extracorporeal shock wave therapies. This study presents Wharton Jelly (WJ) tissue allografts as an additional intervention for patients who fail standard-care treatments. WJ allografts are applied to supplement connective tissue defects directly, unlike other therapies, which aim to reduce swelling and symptomatic pain. This retrospective study includes seven patients who have previously failed standard-of-care treatment. Each received extracorporeal pulse-activated therapy (EPAT), WJ, laser therapy, and an orthotic. Patient progress was tracked using a visual analog scale, 0-10 scoring, reported by the patient at the initial visit and approximately thirteen weeks following, reporting an average improvement of 50%. The study's limitations include a small cohort size and a non-blinded retrospective design. These promising results provide evidence for a more extensive, randomized study to define dosage protocols further and confirm safety and efficacy.

Background: Although confirmed cases of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been declining since late 2020 due to general vaccination, little research has been done regarding the impact of vaccines against SARS-CoV-2 in Spain in terms of hospitalizations and deaths. Objective: Our aim was to identify the reduction in severity and mortality of coronavirus disease 2019 (COVID-19) at a nationwide level due to vaccination. Methods: We designed a retrospective, population-based study to define waves of infection and to describe the characteristics of the hospitalized population. We also studied the rollout of vaccination and its relationship with the decline in hospitalizations and deaths. Finally, we developed two mathematical models to estimate non-vaccination scenarios using machine learning modeling (with the ElasticNet and RandomForest algorithms). The vaccination and non-vaccination scenarios were eventually compared to estimate the number of averted hospitalizations and deaths. Results: In total, 498,789 patients were included, with a global mortality of 14.3%. We identified six waves or epidemic outbreaks during the observed period. We established a strong relationship between the beginning of vaccination and the decline in both hospitalizations and deaths due to COVID-19 in all age groups. We also estimated that vaccination prevented 170,959 hospitalizations (CI 95% 77,844–264,075) and 24,546 deaths (CI 95% 2,548–46,543) in Spain between March 2021 and December 2021. We estimated a global reduction of 9.19% in total deaths during the first year of COVID-19 vaccination. Conclusions: Demographic and clinical profiles changed over the first months of the pandemic. Patients over 80 years old and other age groups obtained clinical benefit from early vaccination. The severity of COVID-19, in terms of hospitalizations and deaths, decreased due to vaccination.

The purpose of this article is to present a multi-criteria model designed to evaluate the potential of Sincelejo's cultural identity for tourism development. A descriptive quantitative methodology was used, which included a survey of 211 participants. A decision support method was applied, using the Weighted Additive Sum approach, following the multi-attribute method. Based on the information gathered, the elements of cultural identity shared by most of the criteria were identi-fied, highlighting the gastronomic, social, and cultural traditions and customs of the region, the results of which made it possible to design a composite indicator to evaluate the tourism potential of cultural identity in the area.

In recent years, transformer-based models have gained prominence in multivariate long-term time series forecasting (LTSF), demonstrating significant advancements despite facing challenges such as high computational demands, difficulty in capturing temporal dynamics, and managing long-term dependencies. The emergence of LTSF-Linear, with its straightforward linear architecture, has notably outperformed transformer-based counterparts, prompting a reevaluation of the transformer's utility in time series forecasting. In response, this paper presents an adaptation of a recent architecture termed extended LSTM (xLSTM) for LTSF. xLSTM incorporates exponential gating and a revised memory structure with higher capacity that has good potential for LTSF. Our adopted architecture for LTSF termed as xLSTMTime surpasses current approaches. We compare xLSTMTime's performance against various state-of-the-art models across multiple real-world datasets, demonstrating superior forecasting capabilities. Our findings suggest that refined recurrent architectures can offer competitive alternatives to transformer-based models in LTSF tasks, potentially redefining the landscape of time series forecasting.

Introduction the outbreak of the Israel-Gaza conflict, initiated by a major attack on the civilian population in Israel provided a tragic opportunity to study the community wide association between severe emotional stressors related to acts of war and the incidence and clinical characteristics of Takotsubo cardiomyopathy (TCM) in this scenario. Methods Eight consecutive cases of TCM diagnosed during the first 50 days of the Israel-Gaza conflict were retrospectively collected from two southern medical centers who provided care to most of the war victims throughout the period of monitoring. The medical records were thoroughly reviewed and analyzed. Results During the monitoring period, the incidence of TCM increased substantially compared to the control period. Eight patients were included in the analysis. All patients were female and 100% of patients presented within the first 3 weeks of conflict whereas after this initial phase, despite the continuing war, the incidence of TCM reverted to pre-conflict levels. Two patients (25%) were under 50 years of age. All patients had hazardous clinical characteristics including severe left ventricular (LV) dysfunction (≤35%) and prolonged QTc interval (>500 ms). Five patients (62.5%) experienced complications. Nevertheless, no in-hospital mortality was reported. Conclusions Repeated exposure to severe emotional stress, on both personal and national level, due to mass crisis such as war is associated with an increased incidence of TCM potentially with high-risk phenotype in comparison to TCM following other, less potent, psychological insults.

The emergence of M. tuberculosis strains resistant to Isoniazid (INH) and Rifampicin (RIF), the two most potent drugs of first-line anti-TB therapy is termed multidrug drug-resistant TB (MDR-TB). Multidrug-resistant tuberculosis has been a serious medical and epidemic problem all over the world. We present here a series of clinical cases consist of two patients diagnosed with isoniazid resistant tuberculosis. Histopathological examination supports the diagnosis of tuberculous granulomas. And the pathology molecular examination revealed the presence of Isoniazid-resistant Mycobacterium tuberculosis1,2 via the following mutation c.947G&gt;A; p.Gly316Asp. Isoniazid-resistance is associated with mutations in the furA-katG and fabG1-inhA operons, as well as mutations in the ahpC gene. 64% of the isoniazid-resistance phenotypes were associated with the katG315 mutation worldwide. The second most common mutation is inhA-15, and it has been reported in 19% of the Isoniazid-resistant isolates. The significant association between the two mutations, inhA c-15 and katG 315 respectively, and the high-level resistance is of interest in the interpretation of current and future molecular diagnostic testing, as an early prediction of the level of Isoniazid-resistance is essential to decide the benefit of high-dose Isoniazid use.