Uwarunkowania stosowania miar ilościowych w geografii fizycznej = The acceptability of application quantitative measures in physical geography

Despite the increasing use of statistical tools in other fields of knowledge and study, the use of quantitative methods in broadcasting research has languished since the middle 1940's. Mr. Porter's article is both a valuable study of the method of paired comparisons for determining program preferences, and a reminder of some of the values and pitfalls of quantitative research.

Celebrating the 25th International Conference of The International Environmetrics Society

The understanding of the reasons for human suffering and the identification of effective means to mitigate it had two major developments in the history of civilization. Aristotle, Hippocrates and other Greek philosophers were the leaders of the first revolution, when they started to explain natural phenomena through the use of logic and observation, leaving aside metaphysical grounds, and creating the philosophical basis of the scientific method. After a long period of recrudescence of religious explanations for the facts of life, the Renascence experienced the second major revolution in the development of the scientific method. Rather than returning to the Greek philosophers, the thinkers of this new era started to challenge them. Descartes, Bacon and others proposed that the use of quantitative methods could better explain natural phenomena than the scholastic interpretation of reality. At the beginning of the 16th century, the natural philosophy of Aristotles was still taught in Jesuit and other colleges, saying, for example, that things are divided into those which could move by an intrinsic power and into those which would depend on an extrinsic power. Surprisingly, stones were classified as a special case of the first condition, since they had a dormant intrinsic power, which would need activation such as elevation from the ground. The theory of gravity proposed by Newton is certainly a better explanation for the fall of stones, and may be recognized as a major example of the transformation of the scientific method that occurred at that time. In the field of biology and medicine, the move from qualitative to quantitative explanations for natural phenomena led to the development of physiology, pathology, pharmacology and other sciences, which modified profoundly the understanding of the causes, consequences, and methods of prevention and treatment of diseases. On the clinical scene, however, the qualitative method for

Until Mandelbrot introduced the concept of fractal geometry and fractal dimension in early 1970s, it has been generally considered that the geometry of nature should be too complex and irregular to describe analytically or mathematically. Here fractal dimension indicates a non-integer number such as 0.5, 1.5, or 2.5 instead of only integers used in the traditional Euclidean geometry, i.e., 0 for point, 1 for line, 2 for area, and 3 for volume. Since his pioneering work on fractal geometry, the geometry of nature has been found fractal. Mandelbrot introduced the concept of fractal geometry. For example, fractal geometry has been found in mountains, coastlines, clouds, lightning, earthquakes, turbulence, trees and plants. Even human organs are found to be fractal. This suggests that the fractal geometry should be the law for Nature rather than the exception. Fractal geometry has a hierarchical structure consisting of the elements having the same shape, but the different sizes from the largest to the smallest. Thus, fractal geometry can be characterized by the similarity and hierarchical structure. A process requires driving energy to proceed. Otherwise, the process would stop. A hierarchical structure is considered ideal to generate such driving force. This explains why natural process or phenomena such as lightning, thunderstorm, earth quakes, and turbulence has fractal geometry. It would not be surprising to find that even the human organs such as the brain, the lung, and the circulatory system have fractal geometry. Until now, a normal frequency distribution (or Gaussian frequency distribution) has been commonly used to describe frequencies of an object. However, a log-normal frequency distribution has been most frequently found in natural phenomena and chemical processes such as corrosion and coagulation. It can be mathematically shown that if an object has a log-normal frequency distribution, it has fractal geometry. In other words, these two go hand in hand. Lastly, applying fractal principles is discussed, focusing on pulp and paper industry. The principles should be applicable to characterizing surface roughness, particle size distributions, and formation. They should be also applicable to wet-end chemistry for ideal mixing, felt and fabric design for papermaking process, dewatering, drying, creping, and post-converting such as laminating, embossing, and printing.

The natural environment provides material essentials for human survival and development. The characteristics, processes, regional differentiation and forcing mechanisms of the elements of the natural environment (e.g. geomorphology, climate, hydrology, soil, etc.) are the main objects of research in physical geography. China has a complex natural environment and huge regional differentiation and therefore it provides outstanding reserach opportunities in physical geography. This review summarizes the most important developments and the main contributions of research in the physical geography and human living environment in China during the past 70 years. The major topics addressed are the uplift of the Tibetan Plateau and the evolution of its cryosphere, the development of fluvial systems, the acidification of the vast arid region of the Asian interior, variations in the monsoon and westerly climate systems on multiple timescales, the development of lakes and wetlands, the watershed system model, soil erosion, past human-environment interactions, biogeography, and physical geographic zonality. After briefly introducing international research developments, we review the history of research in physical geography in China, focusing on the major achievements and major academic debates, and finally we summarize the status of current research and the future prospects. We propose that in the context of the national demand for the construction of an ecological civilization, we should make full use of the research findings of physical geography, and determine the patterns and mechanisms of natural environmental processes in order to continue to promote the continued contribution of physical geography to national development strategies, and to further contribute to the theory of physical geography from a global perspective.

The researches carried out by the AIGeo (Italian Association of Physical Geography and Geomorphology) members, also in collaboration with other researchers, cover various important topics of the Environmental and Earth Sciences and focus on scientific goals and on the development of educational strategies and applications as well. Topics and novelties concerning Physical Geography and Geomorphology fit well with the indications included in the Ministerial National Guidelines for the secondary schools of 2nd level and in the general goals referred to the secondary school of 1st level, where the landscape is discussed by the Geography teachers and natural phenomena by the Science teachers.In this paper, we present an overview about education in Physical Geography and Geomorphology and some examples of the most recent researches planned and tested for the secondary school (1st and 2nd level) and for present and future teachers.

For decades, computer benchmarkers have fought a War of Means. Although many have raised concerns with the geometric mean (GM), it continues to be used by SPEC and others. This war is an unnecessarymisunderstanding due to inadequately articulated implicit assumptions, plus confusio namong populations, their parameters, sampling methods, and sample statistics. In fact, all the Means have their uses, sometimes in combination. Metrics may be algebraically correct, but statistically irrelevant or misleading if applied to population distributions for which they are inappropriate. Normal (Gaussian) distributions are so useful that they are often assumed without question,but many important distributions are not normal.They require different analyses, most commonly by finding a mathematical transformations that yields a normal distribution,computing the metrics, and then back-transforming to the original scale. Consider the distribution of relative performance ratios of programs on two computers. The normal distribution is a good fit only when variance and skew are small, but otherwise generates logical impossibilities and misleading statistical measures. A much better choice is the lognormal (or log-normal) distribution, not just on theoretical grounds, but through the (necessary) validation with real data. Normal and lognormal distributions are similar for low variance and skew, but the lognormal handles skewed distributions reasonably, unlike the normal. Lognormal distributions occur frequently elsewhere are well-understood, and have standard methods of analysis.Everyone agrees that "Performance is not a single number," ... and then argues about which number is better. It is more important to understanding populations, appropriate methods, and proper ways to convey uncertainty. When population parameters are estimated via samples, statistically correct methods must be used to produce the appropriate means, measures of dispersion, Skew, confidence levels, and perhaps goodness-of-fit estimators. If the wrong Mean is chosen, it is difficult to achieve much. The GM predicts the mean relative performance of programs , not of workloads. The usual GM formula is rather unintuitive, and is often claimed to have no physical meaning. However, it is the back-transformed average of a lognormal distribution , as can be seen by the mathematical identity below. Its use is not onlystatistically appropriate in some cases, but enables straightforward computation of other useful statistics.<display equation>"If a man will begin in certainties, he shall end in doubts, but if he will be content to begin with doubts, he shall end with certainties." — Francis Bacon, in Savage.

Purpose: The heterogeneity of human tumor radiation response to is well known. Researchers have used the normal distribution to describe interpatient tumor radiosensitivity. However, many natural phenomena show a lognormal distribution. Lognormal distributions are common when mean values are low, variances are large and values cannot be negative. These conditions apply to radiosensitivity. The aim of this work was to evaluate the lognormal distribution to predict clinical TCP data and compare the results with the homogeneous (single α value) and normal distributions. Method and Materials: The clinically‐derived TCP data for four tumor types: melanoma, breast, squamous cell carcinoma and nodes were used as the benchmark to fit the TCP models. Three forms of interpatient tumor radiosensitivity were considered: the lognormal, normal and δ‐function (homogeneous). The free parameters in the models were the radiosensitivity mean, standard deviation and clonogenic cell density. The evaluation metric was the minimum square difference between the predicted and clinical data. Results: The normal and lognormal distributions match the clinical data significantly better than the δ‐function distribution. The means and standard deviations of the normal and lognormal distributions are similar. Though the clinical data match was slightly better for the lognormal data, the difference was not statistically significant (p=0.13). The clonogenic cell density value yielding the best clinical data match (101–105) is much less than the expected tumor cell density (107–109). Three explanations are intratumor radiosensitivity heterogeneity, tumor ‘stem’ cells and multiple cells required for tumor growth. Conclusion: The lognormal and normal distribution of interpatient tumor radiosensitivity heterogeneity more closely describe clinical TCP data than a single radiosensitivity value. The lognormal distribution trends towards significance in its ability to match clinical TCP data compared to the normal distribution. The lognormal also has some theoretical and practical advantages over the normal distribution.

Recently it was shown that a stopwatch-measured IELT distribution can be transformed to a mathematical formula of a specific mathematical type distribution. The IELT distribution of men in the general population is a Lognormal distribution whereas that of Caucasian men with lifelong premature ejaculation (PE) is a Gumbel Max distribution. In this article, we developed the mathematical formula of the IELT distribution of two other previously published stopwatch-mediated IELT studies in the general male population of the USA and Europe, respectively, by investigating the fitness of various well-known mathematical probability density distributions into the IELT distribution of the two studies. The better the fitness the lower is the goodnes of fit (GOF). We found that the lognormal distribution most accurately fitted the IELT distribution of 1405 men in the general population of the USA, and 1026 men in the general population of Europe, with a GOF of 0.056 and 0.061, respectively. The current study also shows that the Lognormal IELT distribution of two European studies in Caucasian males are quite similar but that the Lognormal IELT distribution of men in the USA deviates compared to the two European IELT distributions. As the USA study also included 25% of non-Caucasian males it may be speculated that ethnical factors play a role in this deviation of the IELT curve. In conclusion, the Lognormal distribution of the IELT distribution in USA and European general male populations reconfirms our previous finding of a Lognormal IELT distribution in two random samples of the general male population in four European countries and USA. The Lognormal IELT distributions of the general male population highly contrasts to the Gumbel Max IELT distribution in Caucasian males with lifelong PE, as has previously been found.

Geography is the study of the earth, including the physical environment, humans, natural and cultural places/regions, and the complex relationships among human-environment interactions. Geography is relevant to the environmental sciences for many reasons but particularly for its focus on distributions of various environmental- and human-related interactions and the factors controlling such distributions over varied spatial and temporal scales. Geography as an applied discipline provides many field-based and geospatial computational methods, techniques, and tools for analyzing local to global earth surface interactions. Environmental science benefits from these contributions. Geography inherently spans the physical and social sciences, commonly integrating aspects of each as they influence one another. This selection of resources focuses on the subdisciplines of geography that are distinctly environmental, including applied and basic process-based physical geography, human-environmental interactions, geographic information sciences, and considerations of scale. Physical geography is the study of the natural environment and all the components and processes that interact across the earth’s surface to influence the distribution and development of natural phenomena, including weather, climate, landforms, soils, plants, and animals. Physical geography is traditionally subdivided by the three major research areas: climatology, geomorphology, and biogeography. Climatology is the study of weather and climate processes and energy fluxes and the factors that control spatial and temporal variations in temperature and precipitation; such controls range from local topographic influences to global wind and ocean current circulation patterns, to human-influenced climate change. Geomorphology is the study of landforms and the processes (water, wind, ice, tectonics, etc.) that shape different erosional and depositional features of the earth surface. Geomorphology includes (but is not limited to) the study of rivers, mountains, coasts, glaciers, and many other earth surface features and landscapes. Biogeography is the study of the distributions of plants and animals (avian, terrestrial, marine, and freshwater organisms), their interactions within an ecosystem or landscape, and the factors controlling their presence and resilience. Climatology, geomorphology, and biogeography can all be examined across a range of spatial and temporal scales, and there is often an emphasis on explaining and quantifying how natural phenomena within these disciplines change over space and time and how they are influenced directly and indirectly by humans. Human-environmental geography includes natural hazards, environmental management, nature-society interactions, and the global environment. Geographic information sciences include GIS (geographic information systems) and remote sensing technologies designed for studying the earth surface environment. Although not a distinct subdiscipline, the concept of scale and the spatial and temporal dimensions of scale are a central tenet of most geography research. Global environmental change, as influenced by physical and human influences and interactions, is a more recent area of study within geography that is rapidly evolving.

خشکسالی‌ها رویدادهای کرانه‌ای هستند که براساس تداوم در زمان و تاثیرات مکانی آن مشخص می‌شوند. بطورکلی خشکسالی‏های منطقه‌ای متاثر از گردش عمومی جو (در مقیاس بزرگ) و عوامل طبیعی منطقه‌ای شامل شرایط توپوگرافی، دریاچه‌های طبیعی، موقعیت نسبت به مرکز و مسیر جریان‌های آب و هوایی در جو (در مقیاس ریز) بوده و اثرات کاملأ همسانی در یک منطقه وسیع را نشان نمی‌دهند. لذا در این مطالعه توزیع احتمال توام بزرگی-مساحت تحت پوشش خشکسالی در حوضه آبریز دریاچه ارومیه با استفاده از تکنیک توابع مفصل انجام پذیرفته و منحنی بزرگی-مساحت-فراوانی/احتمال خشکسالی (S-A-F) توسعه داده شده است. بدین منظور از سری داده‌های شاخص خشکسالی یکماهه SPI در 24 ایستگاه هواشناسی در محدوده مطالعاتی و 7 خانواده تابع مفصل شامل کلایتون، گامبل، فرانک، جو، گالامبوس، پلاکت و نرمال برای مدل‌سازی توزیع احتمال توام دو متغیر همبسته بزرگی و مساحت تحت پوشش خشکسالی استفاده شده است. عملکرد توابع مفصل هفتگانه مذکور براساس معیارهای آماری رایج مورد آزمون قرار گرفته و در نهایت بازای مناسب‌ترین تابع مفصل (مفصل فرانک)، دوره‏های بازگشت شرطی تعیین و منحنی S-A-F برای منطقه مطالعاتی استخراج شد. نتایج مطالعه نشان می‏دهد که رفتارهای کرانه‌ای اقلیمی (خشکسالی یا ترسالی) اکثریت محدوده مطالعاتی را تحت تاثیر قرار می‏دهند. درحالیکه رفتارهای نیمه یا شبه‏خشک دارای پوشش مساحت متفاوت با پراکندگی قابل توجه در محدوده مطالعاتی بوده و با افزایش بزرگی خشکسالی مساحت بیشتری از حوضه آبریز را در بر می‏گیرند. بطوریکه بعنوان مثال، بزرگی خشکسالی برای زمان برگشت 50 ساله با کمترین و بیشترین مقادیر در منطقه یعنی 42/0 و 0/1 بترتیب حدود 5 و 95 درصد مساحت محدوده مطالعاتی را پوشش می‏دهد.

The heterogeneity of human tumour radiation response is well known. Researchers have used the normal distribution to describe interpatient tumour radiosensitivity. However, many natural phenomena show a log-normal distribution. Log-normal distributions are common when mean values are low, variances are large and values cannot be negative. These conditions apply to radiosensitivity. The aim of this work was to evaluate the log-normal distribution to predict clinical tumour control probability (TCP) data and to compare the results with the homogeneous (δ-function with single α-value) and normal distributions. The clinically derived TCP data for four tumour types—melanoma, breast, squamous cell carcinoma and nodes—were used to fit the TCP models. Three forms of interpatient tumour radiosensitivity were considered: the log-normal, normal and δ-function. The free parameters in the models were the radiosensitivity mean, standard deviation and clonogenic cell density. The evaluation metric was the deviance of the maximum likelihood estimation of the fit of the TCP calculated using the predicted parameters to the clinical data. We conclude that (1) the log-normal and normal distributions of interpatient tumour radiosensitivity heterogeneity more closely describe clinical TCP data than a single radiosensitivity value and (2) the log-normal distribution has some theoretical and practical advantages over the normal distribution. Further work is needed to test these models on higher quality clinical outcome datasets.

Automated Detection of Whole-Cell Mitochondrial Motility and its Dependence on Cytoarchitectural Integrity

There are two important questions in the science of quantum. One is how a physical object such as brain has conscious experience. The other is how the consciousness affects or even creates the observed phenomena. In this paper, we presume and demonstrate how human consciousness manifests observed natural laws and phenomena. The basic constituents of human consciousness are proposed to be two basic pairs of duality consciousness: change–unchange duality consciousness and inclusion–exclusion duality consciousness. The mathematic action to describe the maximum amount of information created by human consciousness is derived as the holographic action. From this action, one can obtain the mathematic formula expressing the hologram which describes the possible information, energy and matter that can be manifested by human consciousness. In this way, one can study all the possible natural laws and phenomena observed by human consciousness. This holographic quantum theory of consciousness has five predictions: (1) The existence of grand unification theory which can use one mathematic formula to describe the observed natural laws and phenomena; (2) universality of space and time scale invariance; (3) the emergence of the observed phenomena from a hologram described by holographic action; (4) the one-way direction of conscious time and its relation to the total information of the system and (5) The possibility to transcend currently observed natural laws when one can go beyond duality consciousness and emerge into emptiness. This work demonstrates mathematically how the observed natural laws and phenomena are manifested from human’s conscious activities. It reveals the profound connection between the observed natural laws and human consciousness. This insight can lead to deep insight about the greater human potential and abilities. It also provides a new physical foundation and mathematical tool to study DNA, the brain, life, cosmology, grand unified theory, and all scientific and spiritual disciplines.

Drought is a natural and worldwide phenomenon that occurs when water availability is significantly below normal levels during a significant period of time and cannot meet demand. This work focused on the hydrologic drought defined by the streamflow drought index (SDI) for overlapping periods of 3, 6, 9 and 12 months at 14 hydrometric stations in the northwest of Iran over the period 1975–2009. It was found that some of the streamflow volume series did not follow the normal distribution. The ability of the log-normal, exponential and uniform probability distributions was examined in order to choose the most suitable distribution, and the log-normal distribution was used to fit the long-term streamflow data. The results of the hydrological drought analysis based on the SDI showed that almost all the stations suffered from extreme droughts during the study period. Additionally, extreme droughts occurred most frequently in the last 12 years from 1997–1998 to 2008–2009.