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خرافة ريادة الأعمال : لماذا لا تنجح معظم المشروعات الصغيرة وما العمل حيال ذلك ؟
يحمل هذا اكتاب بين دفتيه إجابات عن أسئلة كثيرة من تلك التي أثارها هذه الخرافة على مدى سنوات ويمنح قراءة الجدد والسابقين على السواء فرصة التعامل مع مشروعاتهم بحيوية متجددة وعقل ثاقب من خال ما يكتسبونه من دراية واسعة بمبادئ خرافة ريادة الأعمال وفي سبيل تحقيق هذه الغاية، سعيت للإجابة عن أهم الأسئلة التي وجهت إلي بشأن المبادئ التي استعرضها في كل فصل عبر حوار أجريته مع سيدة رائعة اسمها \"سارة\" (وليس هذا هو اسمها الحقيقي) أمضيت معها وقتا طويلا على مدار العام الماضي.
BOOK
Using a Random Forest Model to Combine Airborne Lidar and Snotel Data for Daily Estimates of Snow Depth Across Mountain Drainage Basins of Colorado
Machine learning (ML) has emerged as an effective tool for estimating snow depth and snow water equivalent at unsampled times and locations. Airborne lidar surveys are particularly useful for ML applications: the high‐resolution, high‐precision snow depth data allow for algorithm training and testing to an extent and spatial resolution not previously possible. Here, we train a random forest model to estimate snow depth relative to a nearby Snotel site using static physiographic data and dynamic (i.e., time‐dependent) snowpack data as predictor variables and lidar for the target variable. The model output is daily, 50 m resolution snow depth for basins that have both lidar and Snotel data in Colorado. We evaluated multiple approaches for random forest training: using historic lidar data in a basin (temporal transfer), using lidar data from other basins in a region (spatial transfer), and both together. The three approaches yield RMSE values ranging from 0.37 to 0.44 m at 50 m resolution, achieving lower errors compared to ML studies at higher resolutions. Model error decreases when outputs are upscaled, with RMSE values of 0.17 and 0.10 m for the 4 km and basin scales, respectively. The model scenario which includes both temporally and spatially transferred lidar data is the most robust to the number and timing of lidar surveys used in model training. This framework extends the spatial footprint of Snotel and the temporal coverage of lidar by leveraging the strengths of the two data sets, with applications for water resource management and validation of gridded snow products.
Journal Article
Human Influences on Nitrogen Removal in Lakes
Human activities have increased the availability of reactive nitrogen in many ecosystems, leading to negative impacts on human health, biodiversity, and water quality. Freshwater ecosystems, including lakes, streams, and wetlands, are a large global sink for reactive nitrogen, but factors that determine the efficacy of freshwater nitrogen removal rates are poorly known. Using a global lake data set, we show that the availability of phosphorus, a limiting nutrient, affects both annual nitrogen removal rate and efficiency. This result indicates that increased phosphorus inputs from human activities have stimulated nitrogen removal processes in many lakes. Recent management-driven reductions in phosphorus availability promote water column accumulation and export of nitrogen from large lakes, an unintended consequence of single-element management that argues for greater control of nitrogen as well as phosphorus sources.
Journal Article
الصين المتغيرة : احتمالات الديمقراطية في الداخل والدبلوماسية الجديدة تجاه \الدول المارقة\
تقوم هذه الدراسة التي جاءت تحت عنوان (الصين المتغيرة) الباحثون (جون ثورنتون، ستيفاني كلين، أندرو سمول) للإضاءة على المحادثات التي أجريت طوال الشهور الأربعة عشرة الأخيرة الماضية مع مجموعة عريضة من الصينيين ومن ذلك أعضاء اللجنة المركزية للحزب الشيوعي الصيني وهي المجموعة القيادية في الصين المكونة من 370 قائدا وكبار المسؤولين الحكوميين وفي هذا السياق يطرح الكتاب إشكالية مهمة وهي هل على الصين أن تأخذ بالديمقراطية حسب المفهوم الذي لها أنها تقدم رؤية جديدة، فكبار المسؤولين يشددون على وجوب المحافظة على قيادة الحزب الشيوعي الصيني عن طريق الشكل التداوي الذي يسمح للأفراد والجماعات بالمشاركة في اتخاذ القرارات، أكثر من التنافس المفتوح والمتعدد الأحزاب على السلطة.
Book
Quantifying nutrient recovery efficiency and loss from compost-based urban agriculture
The use of compost in urban agriculture offers an opportunity to increase nutrient recycling in urban ecosystems, but recent studies have shown that compost application often results in phosphorus (P) being applied far in excess of crop nutrient demand, creating the potential for P loss through leachate and runoff. Management goals such as maximizing crop yields or maximizing the mass of nutrients recycled from compost may inadvertently result in P loss, creating a potential ecosystem disservice. Here, we report the results from the first two years of an experimental study in which four different crops grown in raised-bed garden plots with high background P and organic matter received one of two types of compost (municipal compost made from urban organics waste, or manure-based compost) at two different levels (applied based on crop N or P demand), while additional treatments received synthetic N and P fertilizer or no soil amendments. Because of the low N:P ratio of compost relative to crop nutrient uptake, compost application based on crop N demand resulted in overapplication of P. Crop yield did not differ among treatments receiving compost inputs, and the mass of P recovered in crops relative to P inputs decreased for treatments with higher compost application rates. Treatments receiving compost targeted to crop N demand had P leachate rates approximately twice as high as other treatments. These results highlight tradeoffs inherent in recycling nutrients through UA, but they also show that targeted compost application rates have the capacity to maintain crop yields while minimizing nutrient loss. UA has the potential to help close the urban nutrient loop, but if UA is to be scaled up in order to maximize potential social, economic, and environmental benefits, it is especially important to carefully manage nutrients to avoid ecosystem disservices from nutrient pollution.
Journal Article
تحليل الجريمة في 60 خطوة مبسطة للمعنيين بمكافحة الجريمة
يتناول كتاب (تحليل الجريمة في 60 خطوة مبسطة للمعنيين بمكافحة الجريمة) والذي قام بتأليفه (Ronald V. Clarke, John E. Eck) في حوالي (306) صفحة من القطع المتوسط موضوع (التحقيق الجنائي) مستعرضا المحتويات التالية : قم بإعداد نفسك، كن ملما بأسلوب الشرطة الموجه نحو حل المشكلات، قم بدراسة علم الإجرام البيئي، بحث عن المشكلات المتعلقة بالجرائم، قم بالتحليل المتعمق.
Book
Modeling bulk density and snow water equivalent using daily snow depth observations
Bulk density is a fundamental property of snow relating its depth and mass. Previously, two simple models of bulk density (depending on snow depth, date, and location) have been developed to convert snow depth observations to snow water equivalent (SWE) estimates. However, these models were not intended for application at the daily time step. We develop a new model of bulk density for the daily time step and demonstrate its improved skill over the existing models. Snow depth and density are negatively correlated at short (10 days) timescales while positively correlated at longer (90 days) timescales. We separate these scales of variability by modeling smoothed, daily snow depth (long timescales) and the observed positive and negative anomalies from the smoothed time series (short timescales) as separate terms. A climatology of fit is also included as a predictor variable. Over half a million daily observations of depth and SWE at 345 snowpack telemetry (SNOTEL) sites are used to fit models and evaluate their performance. For each location, we train the three models to the neighboring stations within 70 km, transfer the parameters to the location to be modeled, and evaluate modeled time series against the observations at that site. Our model exhibits improved statistics and qualitatively more-realistic behavior at the daily time step when sufficient local training data are available. We reduce density root mean square error (RMSE) by 9.9 and 4.5% compared to previous models while increasing R2 from 0.46 to 0.52 to 0.56 across models. Focusing on the 21-day window around peak SWE in each water year, our model reduces density RMSE by 24 and 17.4% relative to the previous models, with R2 increasing from 0.55 to 0.58 to 0.71 across models. Removing the challenge of parameter transfer over the full observational record increases R2 scores for both the existing and new models, but the gain is greatest for the new model (R2 = 0.75). Our model shows general improvement over existing models when data are more frequent than once every 5 days and at least 3 stations are available for training.
Journal Article
Field guide to birds of the Middle East
The ultimate field guide to the birds of the Middle East, an indispensable companion for any traveller to the region. The Middle East - the region stretching from Cyprus and the Levant to Iran, including Turkey and the Arabian Peninsula, plus Socotra - has a wonderfully broad and diverse avifauna, featuring a host of wintering and passage migrants, enigmatic breeders, and even a few endemics that occur nowhere else. This authoritative book covers more than 895 species recorded in the Middle East, including details of all regular visitors and breeding species, from the Purple Sunbird to the Northern Bald Ibis.
BOOK
Controls on surface soil drying rates observed by SMAP and simulated by the Noah land surface model
Drydown periods that follow precipitation events provide an opportunity to assess controls on soil evaporation on a continental scale. We use SMAP (Soil Moisture Active Passive) observations and Noah simulations from drydown periods to quantify the role of soil moisture, potential evaporation, vegetation cover, and soil texture on soil drying rates. Rates are determined using finite differences over intervals of 1 to 3 days. In the Noah model, the drying rates are a good approximation of direct soil evaporation rates, and our work suggests that SMAP-observed drying is also predominantly affected by direct soil evaporation. Data cover the domain of the North American Land Data Assimilation System Phase 2 and span the first 1.8 years of SMAP's operation. Drying of surface soil moisture observed by SMAP is faster than that simulated by Noah. SMAP drying is fastest when surface soil moisture levels are high, potential evaporation is high, and when vegetation cover is low. Soil texture plays a minor role in SMAP drying rates. Noah simulations show similar responses to soil moisture and potential evaporation, but vegetation has a minimal effect and soil texture has a much larger effect compared to SMAP. When drying rates are normalized by potential evaporation, SMAP observations and Noah simulations both show that increases in vegetation cover lead to decreases in evaporative efficiency from the surface soil. However, the magnitude of this effect simulated by Noah is much weaker than that determined from SMAP observations.
Journal Article