Estimating Tourist Growth at Destination Sites: A Mathematical Equation and a Connectivity Model Through Mobile Application

لقد سعى باحثو العلوم الاجتماعية إلى عرض الأدبيات المختلفة لأنظمة التوصية المتنقلة الفردية لمساعدة أصحاب المصلحة في قطاع السياحة. إن التحدي المتمثل في صياغة معادلة رياضية للتنبؤ بالنمو السياحي في مواقع محددة ينشأ بسبب الظروف البيئية المتنوعة الفريدة لكل وجهة. يسعى هذا البحث إلى تطوير نموذج لتطبيقات الهاتف المحمول يعزز الاتصال بين أصحاب المصلحة الرئيسيين في مجال السياحة. داخل التطبيق، يمكن لأصحاب المصلحة استرداد المعلومات حول الآخرين بسهولة والتفاعل مباشرة مع السلطات ذات الصلة دون الخروج من التطبيق. يوفر التطبيق أيضًا إرشادات ملاحية للوجهات السياحية. وتستكشف الدراسة معدل النمو النوعي للسياح، بافتراض تضاعف أعداد السياح بعد فترة زمنية محددة. في حين أنه قد يكون هناك نمو هائل مبدئي في أعداد السياح في الوجهة، إلا أن العدد يستقر في النهاية. تم استخدام معادلة مونود مع المعادلة السياحية للحصول على تمثيل شامل في هذه الدراسة. بالإضافة إلى ذلك، يتعمق البحث في التحليل الرسومي لشروط الجدوى التي يقترحها نموذج الاتصال الخاص بـCasagrand i و Rinaldi. و من الضروري ملاحظة أن هذا التحليل يظل مجردًا، وأن إنشاء نموذج رياضي رياضي قابل للتطبيق عالميًا لكل وجهة يكاد يكون مستحيلًا.Social science researchers have endeavored with the literature showcasing various individual mobile recommendation systems to assist stakeholders in the tourism sector. The challenge of formulating a mathematical equation to predict tourist growth at specific sites arises due to the diverse environmental conditions unique to each destination. This research seeks to develop a mobile application model fostering connectivity among significant tourism stakeholders. Within the app, stakeholders can effortlessly retrieve information about others and directly engage with relevant authorities without exiting the application. The app also provides navigation guidance to tourist destinations. The study explores the specific growth rate of tourists, assuming a doubling of tourist numbers after a specific time interval has been illustrated. While there may be an initial exponential growth in tourist numbers at a destination, the count eventually stabilizes. The Monod equation is employed in conjunction with the tourist equation for a comprehensive representation in this study. Additionally, the research delves into the graphical analysis of the feasibility conditions proposed by Casagrandi and Rinaldi's connectivity model. It is essential to note that this analysis remains abstract, and the creation of a universally applicable mathematical tourism model for every destination proves nearly impossible

Guiding the Design of Synthetic DNA-Binding Molecules with Massively Parallel Sequencing

Genomic applications of DNA-binding molecules require an unbiased knowledge of their high affinity sites. We report the high-throughput analysis of pyrrole-imidazole polyamide DNA-binding specificity in a 10^(12)-member DNA sequence library using affinity purification coupled with massively parallel sequencing. We find that even within this broad context, the canonical pairing rules are remarkably predictive of polyamide DNA-binding specificity. However, this approach also allows identification of unanticipated high affinity DNA-binding sites in the reverse orientation for polyamides containing β/Im pairs. These insights allow the redesign of hairpin polyamides with different turn units capable of distinguishing 5′-WCGCGW-3′ from 5′-WGCGCW-3′. Overall, this study displays the power of high-throughput methods to aid the optimal targeting of sequence-specific minor groove binding molecules, an essential underpinning for biological and nanotechnological applications

Fate of micro- and nanoplastics in water bodies: A critical review of current challenges, the next generation of advanced treatment techniques and removal mechanisms with a special focus on stormwater

Micro- and nanoplastics (MNPs) are a growing source of pollution from natural and plastic fibers to non-fiber particles in water matrices. The current review highlights the detection, pathways, measurements and fate of MNPs. Besides, it addresses various treatment technologies, the next generation of MNPs degradation and their removal mechanisms from water bodies especially stormwater. The removal efficiency of MNPs decreases with decreasing particle size, as smaller particles were able to pass more easily through the tertiary sand filter or membrane filter. NPs exhibited lower removal efficiency compared to MPs. Conventional methods for treating stormwater including bioretention filters and constructed wetlands are inadequate in removing MNPs effectively. Some novel methods, such as egg protein derived ultra-lightweight hybrid monolithic aerogel, rely solely on gravity and do not require water, demonstrating up to 100 % removal of microplastics from seawater. This method could also be applied to stormwater treatment. This is superior to membrane technologies including UF and MF, which operates with a substantial energy input and excess water. Integrated treatment systems that combine different technologies can overcome the limitations of individual methods. Furthermore, the core mechanisms involved in eliminating MPs/NPs via biofilm consist of electrostatic surface attachment, hydrophobic interaction, absorption onto the biofilm layer, intermolecular repulsion, and electrostatic interaction between MPs/NPs and the membrane surface

Key role of SMN/SYNCRIP and RNA-Motif 7 in spinal muscular atrophy: RNA-Seq and motif analysis of human motor neurons

Spinal muscular atrophy is a motor neuron disorder caused by mutations in SMN1. The reasons for the selective vulnerability of motor neurons linked to SMN (encoded by SMN1) reduction remain unclear. Therefore, we performed deep RNA sequencing on human spinal muscular atrophy motor neurons to detect specific altered gene splicing/expression and to identify the presence of a common sequence motif in these genes. Many deregulated genes, such as the neurexin and synaptotagmin families, are implicated in critical motor neuron functions. Motif-enrichment analyses of differentially expressed/spliced genes, including neurexin2 (NRXN2), revealed a common motif, motif 7, which is a target of SYNCRIP. Interestingly, SYNCRIP interacts only with full-length SMN, binding and modulating several motor neuron transcripts, including SMN itself. SYNCRIP overexpression rescued spinal muscular atrophy motor neurons, due to the subsequent increase in SMN and their downstream target NRXN2 through a positive loop mechanism and ameliorated SMN-loss-related pathological phenotypes in Caenorhabditis elegans and mouse models. SMN/SYNCRIP complex through motif 7 may account for selective motor neuron degeneration and represent a potential therapeutic target

Development and Validation of an Epitope Prediction Tool for Swine (PigMatrix) Based on the Pocket Profile Method

Background: T cell epitope prediction tools and associated vaccine design algorithms have accelerated the development of vaccines for humans. Predictive tools for swine and other food animals are not as well developed, primarily because the data required to develop the tools are lacking. Here, we overcome a lack of T cell epitope data to construct swine epitope predictors by systematically leveraging available human information. Applying the “pocket profile method”, we use sequence and structural similarities in the binding pockets of human and swine major histocompatibility complex proteins to infer Swine Leukocyte Antigen (SLA) peptide binding preferences. We developed epitope-prediction matrices (PigMatrices), for three SLA class I alleles (SLA-1*0401, 2*0401 and 3*0401) and one class II allele (SLA-DRB1*0201), based on the binding preferences of the best-matched Human Leukocyte Antigen (HLA) pocket for each SLA pocket. The contact residues involved in the binding pockets were defined for class I based on crystal structures of either SLA (SLA-specific contacts, Ssc) or HLA supertype alleles (HLA contacts, Hc); for class II, only Hc was possible. Different substitution matrices were evaluated (PAM and BLOSUM) for scoring pocket similarity and identifying the best human match. The accuracy of the PigMatrices was compared to available online swine epitope prediction tools such as PickPocket and NetMHCpan. Results: PigMatrices that used Ssc to define the pocket sequences and PAM30 to score pocket similarity demonstrated the best predictive performance and were able to accurately separate binders from random peptides. For SLA-1*0401 and 2*0401, PigMatrix achieved area under the receiver operating characteristic curves (AUC) of 0.78 and 0.73, respectively, which were equivalent or better than PickPocket (0.76 and 0.54) and NetMHCpan version 2.4 (0.41 and 0.51) and version 2.8 (0.72 and 0.71). In addition, we developed the first predictive SLA class II matrix, obtaining an AUC of 0.73 for existing SLA-DRB1*0201 epitopes. Notably, PigMatrix achieved this level of predictive power without training on SLA binding data. Conclusions: Overall, the pocket profile method combined with binding preferences from HLA binding data shows significant promise for developing T cell epitope prediction tools for pigs. When combined with existing vaccine design algorithms, PigMatrix will be useful for developing genome-derived vaccines for a range of pig pathogens for which no effective vaccines currently exist (e.g. porcine reproductive and respiratory syndrome, influenza and porcine epidemic diarrhea)

Human Iron−Sulfur Cluster Assembly, Cellular Iron Homeostasis, and Disease†

ABSTRACT: Iron-sulfur (Fe-S) proteins contain prosthetic groups consisting of two or more iron atoms bridged by sulfur ligands, which facilitate multiple functions, including redox activity, enzymatic function, and maintenance of structural integrity. More than 20 proteins are involved in the biosynthesis of iron-sulfur clusters in eukaryotes. Defective Fe-S cluster synthesis not only affects activities of many iron-sulfur enzymes, such as aconitase and succinate dehydrogenase, but also alters the regulation of cellular iron homeostasis, causing both mitochondrial iron overload and cytosolic iron deficiency. In this work, we review human Fe-S cluster biogenesis and human diseases that are caused by defective Fe-S cluster biogenesis. Fe-S cluster biogenesis takes place essentially in every tissue of humans, and products of human disease genes, including frataxin, GLRX5, ISCU, and ABCB7, have important roles in the process. However, the human diseases, Friedreich ataxia, glutaredoxin 5-deficient sideroblastic anemia, ISCU myopathy, and ABCB7 sideroblastic anemia/ataxia syndrome, affect specific tissues, while sparing others. Here we discuss the phenotypes caused by mutations in these different disease genes, and we compare the underlying pathophysiology and discuss the possible explanations for tissue-specific pathology in these diseases caused by defective Fe-S cluster biogenesis. HUMAN CELLULAR IRON HOMEOSTASI

Distribution and determinants of patient satisfaction in oncology with a focus on health related quality of life

<p>Abstract</p> <p>Background</p> <p>Cancer patients usually undergo extensive and debilitating treatments, which make quality of life (QoL) and patient satisfaction important health care assessment measures. However, very few studies have evaluated the relationship between QoL and patient satisfaction in oncology. We investigated the clinical, demographic and QoL factors associated with patient satisfaction in a large heterogeneous sample of cancer patients.</p> <p>Methods</p> <p>A cohort of 538 cancer patients treated at Cancer Treatment Centers of America^®(CTCA) was assessed. A patient satisfaction questionnaire developed in-house by CTCA was used. It covered the following dimensions of patient satisfaction: hospital operations and services, physicians and staff, and patient endorsements for themselves and others. QoL was assessed using the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire (QLQ-C30). The clinical, demographic and QoL factors were evaluated for predictive significance using univariate and multivariate logistic regression.</p> <p>Results</p> <p>The mean age of our patient population was 54.1 years (SD = 10.5, range 17-86), with a slight preponderance of females (57.2%). Breast cancer (n = 124) and lung cancer (n = 101) were the most frequent cancer types. 481 (89.4%) patients were "very satisfied" with their overall experience. Age and several QoL function and symptom scales were predictive of overall patient satisfaction upon univariate analysis. In the multivariate modeling, only those with a score above the median on the fatigue measure (i.e. worse fatigue) had reduced odds of 0.28 of being very satisfied (p = 0.03).</p> <p>Conclusion</p> <p>Patient fatigue, as reported by the QoL fatigue scale, was an independent significant predictor of overall patient satisfaction. This finding argues for special attention and programs for cancer patients who report higher levels of fatigue given that fatigue is the most frequently reported symptom in cancer patients.</p

Integrative Identification of Arabidopsis Mitochondrial Proteome and Its Function Exploitation through Protein Interaction Network

Mitochondria are major players on the production of energy, and host several key reactions involved in basic metabolism and biosynthesis of essential molecules. Currently, the majority of nucleus-encoded mitochondrial proteins are unknown even for model plant Arabidopsis. We reported a computational framework for predicting Arabidopsis mitochondrial proteins based on a probabilistic model, called Naive Bayesian Network, which integrates disparate genomic data generated from eight bioinformatics tools, multiple orthologous mappings, protein domain properties and co-expression patterns using 1,027 microarray profiles. Through this approach, we predicted 2,311 candidate mitochondrial proteins with 84.67% accuracy and 2.53% FPR performances. Together with those experimental confirmed proteins, 2,585 mitochondria proteins (named CoreMitoP) were identified, we explored those proteins with unknown functions based on protein-protein interaction network (PIN) and annotated novel functions for 26.65% CoreMitoP proteins. Moreover, we found newly predicted mitochondrial proteins embedded in particular subnetworks of the PIN, mainly functioning in response to diverse environmental stresses, like salt, draught, cold, and wound etc. Candidate mitochondrial proteins involved in those physiological acitivites provide useful targets for further investigation. Assigned functions also provide comprehensive information for Arabidopsis mitochondrial proteome

Fragmentation and Multifragmentation of 10.6A GeV Gold Nuclei

We present the results of a study performed on the interactions of 10.6A GeV gold nuclei in nuclear emulsions. In a minimum bias sample of 1311 interac- tions, 5260 helium nuclei and 2622 heavy fragments were observed as Au projec- tile fragments. The experimental data are analyzed with particular emphasis of target separation interactions in emulsions and study of criticalexponents. Multiplicity distributions of the fast-moving projectile fragments are inves- tigated. Charged fragment moments, conditional moments as well as two and three -body asymmetries of the fast moving projectile particles are determined in terms of the total charge remaining bound in the multiply charged projectile fragments. Some differences in the average yields of helium nuclei and heavier fragments are observed, which may be attributed to a target effect. However, two and three-body asymmetries and conditional moments indicate that the breakup mechanism of the projectile seems to be independent of target mass. We looked for evidence of critical point observable in finite nuclei by study the resulting charged fragments distributions. We have obtained the values for the critical exponents gamma, beta and tau and compare our results with those at lower energy experiment (1.0A GeV data). The values suggest that a phase transition like behavior, is observed.Comment: latex, revtex, 28 pages, 12 figures, 3tables, submitted to Europysics Journal