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2020 年 5 月 3 日  星期日   晴天


之所以男人容易生痔瘡,是他們的凶手! 分類: 未分類

痔瘡已經嚴重影響學習到了人的正常工作生活,因此,我們國家必須從根源上預防。而導致痔瘡的原因之一就是通過以下幾點。

1、 長期坐臥

從病理角度看,痔瘡實際上是由於淤血而形成靜脈叢.. 在現代生活中,絕大多數年輕人都處於久坐的現狀,在辦公室塈允q腦,一份工作是7到8個小時,回家也是久坐的沙發。 久坐可使血管不能流通,靜脈腫脹,從而引起痔瘡。

2、 飲食作息不規律

飲食作息不規律也是痔瘡的根本原因之一。絕大多數男性吸煙和飲酒習慣,這些習慣除了傷胃肺損傷,可導致痔瘡。吸煙和飲酒會使身體的消化問題,便秘的情況發生,導致痔瘡。

3、性事過程中我們不注意個人生活衛生

這樣做,雙方很容易處於高度精神緊張的狀態。 特別是臀部兩側肌肉放松收縮快時,精液容易回流肛門,造成細菌感染,進而出現腫脹,從而形成痔瘡.. 此外,短期與不同的人發生性關系也容易發生肛周感染,導致痔瘡,甚至更嚴重的不可逆轉的疾病。

那么,我們應該怎么辦有痔瘡?

如果企業一旦我們發現自己得了痔瘡,必須具有高度重視學生起來。在出現痔瘡的問題時,做到以下幾點,讓你盡快擺脫痔瘡的煩惱。

及時求醫

很多人患痔瘡卻不敢告訴任何人,也不想去醫院就醫,想了很久,痔瘡就會消失.. 但事實並非如此。 對於痔瘡,一定要高度重視,及時到醫院門診就醫,絕不能耽誤病情,否則情況只會加重..

注意肛周衛生

唔想再次經歷流血和痔瘡 痕癢的苦況,塗抹痔瘡藥膏便是推薦的治療方法。

來自苦難除了醫院接受治療後。在日常生活中,還要注意肛周衛生。上完廁所後,與水,個人衛生清洗。

鍛煉身體,積極運動

患上痔瘡之後,患者進行不適合久坐。最好的方法主要就是通過戶外走走散步,減少坐臥的時間。積極參與運動可以鍛煉自己身體,避免久坐。

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痔瘡患者在保健發展過程中應注意學生做到“五要”

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2020 年 2 月 11 日  星期二   晴天


How Will AI Improve the way forward for Seo? 分類: 未分類

Synthetic intelligence (AI) is penetrating each and every office of each marketplace, from automating manufacturing facility do the job to strengthening places previously assumed untouchable by equipment (like human methods). But being a veteran in the on the internet internet marketing environment, I just can't aid but let my creativity wander on how AI and machine finding out will impact the whole world of search engine optimization (Seo)-the methods corporations use to rank larger in online search engine benefits webpages (SERPs).

Currently, we’re observing the beginnings of the full-scale AI revolution in Search engine marketing, and look for marketers are scrambling to help keep tempo using the variations. But what's going to the next few years bring? How about the following decade?

The large Picture
We say “search engines,” but most of time, we’re talking about Google. Bing, Yahoo!, DuckDuckGo, together with other engines only share a portion with the research user base, and most of their systems are modeled following Google’s from the initially place. So our massive dilemma is, how is Google going to incorporate AI inside the upcoming to alter how search is effective with the average user?

Historically, Google has up-to-date its algorithms with two major goals in your mind:

Improve user encounter. Google needs end users to locate the answers they’re looking for, and receive correct, useful written content. This is certainly an essential class, and also a sophisticated 1; to attain this, Google not merely should ideal how its online search engine functions, and also the way it finds, organizes, and evaluates the caliber of articles over the world wide web.
Keep users on Google. Google can make cash when persons utilize it, and keep over the system as long as achievable. We’ll see why that’s significant in a foreseeable future portion.
Google is already using equipment finding out in the few various ways, and it’s merely a make any difference of your time just before it innovations.

RankBrain and Device Finding out
Very first, let’s take into account RankBrain, a device learning-based update to Google’s Hummingbird algorithm, which introduced in 2015. The Hummingbird update, from 2013, initially rolled out “semantic search” abilities. It absolutely was designed to examine the context of consumer queries, instead than the actual contents; fairly than prioritizing actual match keywords and phrases, Hummingbird authorized Google to take into consideration synonyms, linked phrases, plus much more. This was a phase during the right path, due to the fact it intended people could find far better success, and lookup optimizers could no more get away with keyword stuffing.

RankBrain was a modification that allowed Google to check huge portions of consumer lookup data and instantly increase its interpretation of consumer phrases. It had been generally concentrated on prolonged, convoluted, or hard-to-understand phrases, finally lessening them down to a duration and ease stage the algorithm could extra quickly deal with. It’s been self-updating and increasing at any time due to the fact.

That is a significant indication of how search will evolve from the future; I’m guessing that fairly than seeing handbook update following manual update, we’ll see a lot more algorithm adjustments built to self-update dependant on machine understanding insights. This is certainly considerably faster and fewer pricey than having people accomplishing every one of the get the job done.

Material High quality and Website link Top quality
I suspect we’ll also see important AI improvements utilized to higher recognize the caliber of the material and one-way links manufactured by lookup optimizers.

Backlinks and content are classified as the focal details of most Search engine marketing techniques. Google experiments one-way links to compute domain- and page-level authority (or trustworthiness); frequently, the more hyperlinks a web page has pointed to it, as well as the greater these links are, the upper it is likely to rank. Likewise, better-written, additional related content material tends to increase in SERP rankings-and attract net consumers. Greater content and improved inbound links suggest you are going to close up which has a bigger return on expense (ROI) for the Search engine marketing technique.

Over the years, Google has gotten greater at examining the standard of information and links from internet websites; lookup marketers have progressed from seeking to trick Google’s algorithm to simply trying to make their finest achievable get the job done.

Right this moment, Google’s procedures for assessing the subjective “quality” of articles and inbound links are good-but they may constantly be far better. It might be less complicated for an AI agent to slowly find out what tends to make excellent information “good,” than to rely with a guide agent coding all those parameters right into a technique. I believe Google is likely to make far more endeavours to automate quality evaluation during the around potential.

Individualization
Google has also taken fantastic efforts to individualize its search results. In the event you seek out precisely the same phrase in Phoenix, Arizona and Cleveland, Ohio, you are in all probability going to have radically distinctive outcomes. You might also get diverse outcomes dependant on your search historical past, as well as the demographic information Google “knows” about you.

At this time, these individualization efforts are impressive, but minimal. We’re not surprised that Google is aware where we are, or perhaps the very last number of factors we have searched for. But inside the around future, Google may be effective at using AI to create much more intensive predictions. Based on your historic queries and research data from hundreds of thousands of other users such as you, Google could possibly propose queries or search results before you even know you need them.

For research marketers, this is the two a possibility along with a menace. For those who can capitalize on predictive queries, you are able to obtain a huge edge about the competition-but nevertheless, if Google’s algorithmic techniques are opaque, chances are you'll have a really hard time being familiar with how and whenever your success appear for end users.

Good Success
In the last number of yrs, Google has stepped up its endeavours to maintain consumers over the SERPs, rather than clicking back links to visit other web-sites. The Know-how Graph and abundant snippets now seem to deliver speedy answers to user queries, preventing the necessity to simply click any even further. As Google gets superior at dissecting user queries with RankBrain and Hummingbird, and will become superior at parsing the web with clever algorithms, I suspect we’ll see all the more of those user-attention-grabbing entries.

For search entrepreneurs, this really is yet again both equally an opportunity as well as a danger. In the event you can game the system and obtain your material to appear inside the SERPs previously mentioned your competitors’, you’ll have a important raise to the brand name reputation. But within the identical time, if users keep in the SERPs, and never ever take a look at, you will overlook out with a ton of natural targeted traffic.

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Genuine Time Variations and adaptability
AI is remarkably great at examining broad amounts of data, and much more rapidly than even a highly trained human group. Historically, Google has created periodic updates to its algorithm with significant, game-changing algorithm changes dropped every few months. But not long ago, those people algorithm updates have tapered off in favor of substantially more compact, significantly much more repeated updates.

This pattern will probably build even more while in the foreseeable future as Google’s AI devices improve towards real-time analytics. It will “learn” consistently, with each individual new lookup question, and maybe roll new updates to its dwell algorithm on a continuous basis, rendering it challenging to sustain with its iterative evolution.

Articles Manufacturing and Onsite Optimization
It is also well worth noting that AI won’t just be harnessed by Google and other search engines like yahoo. We’ll also begin to see the progress and utility of AI on behalf of research entrepreneurs. AI-based articles generators have become additional innovative and much more popular; finally, lookup entrepreneurs may be able to make use of them to provide and distribute articles good enough to “fool” Google’s algorithms. From there, this could probably switch into an arms race between search marketers and look for algorithms-not much too contrary to what we have already got.

Also, intelligent onsite optimization engines could significantly simplify the technological initiatives that look for marketers currently really have to make. Present-day plugins and onsite Search engine optimisation equipment are handy, but incomplete; while in the near potential, AI and machine understanding could make these significantly a lot more able.

General, it is unlikely that we’ll see this kind of a radical transformation that SERPs come to be unrecognizable, or that Seo disappears being an on the web advertising and marketing tactic. Even so, research entrepreneurs and end users will both really need to make some major changes if they are likely to remain pertinent as AI infiltrates this place.

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2019 年 12 月 16 日  星期一   晴天


Solar Modeling & Monitoring Granularity Boost Efficiency 分類:

The days of over-designing and over-building solar power plants to make up for unforeseen generation losses are gone. This is largely thanks to the emerging photo voltaic strategy of pursuing every tenth of a percent of system performance by better understanding the impact of equipment specifications, plant monitoring, and maintenance on the performance Ratio, and therefore on the bottom line.

The industry is in the midst of a technology boom that is increasing the granularity of solar design improvements, with enhanced monitoring and advanced algorithms to fine-tune pV plant operations and management from a host of perspectives.

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Granularity in measurement and data analysis enables more efficient operation, which results in a higher energy yield. This is because it pinpoints substandard functionality, enabling designers to improve systems and operators to enhance yield through remedial action.

This detailed monitoring and analysis can begin with the most basic of environmental problems, soiling of pV modules.

This more granular monitoring also takes place at the power optimization level, within sophisticated smart inverters that are now attuned to slight deviations from the expected performance and use technologies such as maximum power point tracking.

Software supports bifacial granularity
One of the elements of evolving photo voltaic technology that enables more granularity is better software.

research and development experts gathered to compare notes on solar modeling software advances, building on widely used plant design programs by pVsyst and other companies.

A hot topic is the increasing interest in the advantages of bifacial modules, which gather reflected light from the surface below on the rear face and can boost yield by double-digit percentages. Among new approaches that take into account bifacial design issues is a trend towards three-dimensional modeling, which should also include soiling effects. This and other new technologies were displayed and discussed at the Symposium in May, which was co-sponsored by Sandia National Laboratories, CFV Solar Test Laboratory, and the Electric power Research Institute (EpRI).

One new design solution highlighted is from Australia’s pV Lighthouse.The company is using its software to model bifacial systems, incorporating real world data sets, including weather measurement feeds from the National Renewable Energy Lab (NREL), resulting in some two billion ray calculations. That is granularity!

Another solar software technology development underway is at the University of Iowa, where a team is developing a performance prediction model that uses a reverse ray-tracing method, based on Radiance and python software.

NREL’s V3 Bifacial Radiance software is being used to investigate single-axis tracking bifacial design variables; including tracker table height and torque tube clearance and table separation. Such software programs are providing more advanced algorithms to help photo voltaic system designers and operators focus on the important data within key timeframes.

Optimizing yield using new technologies
Once more advanced photo voltaic arrays have been designed and built, very robust monitoring of the system operation and yield is being adopted to help squeeze out as much generation as possible. Measurements are now being logged in terms of seconds, rather than minutes, with individual module performance compared in detail with other modules in an array.

For example, the build-up of dust, sand, pollen, and other soiling can cut energy yield by double-digit percentages in relatively short time-scales. This is being analyzed in detail on solar modules, thanks to new technology like the DustIQ, which can measure a 1% loss of yield caused by soiling. In a recent White paper, Kipp & Zonen lays out the science for advanced soiling monitoring to maximize solar yield.

Fleets of camera drones are also offering real-time monitoring data that can zoom in on specific modules, using heat-sensing and other technology to pinpoint hot spots in arrays, triggering the replacement of individual modules. Solar system owners no longer need to take the time to dispatch a technician in a truck to figure out what has gone wrong with the generation system.

Advanced communications needed for data-intensive energy monitoring

Communicating this more detailed monitoring data is also an area of advancing technology. Rather than using hard-wired cable to transmit the data, solar plant monitoring systems are now incorporating wireless modes; including Wi-Fi, Zigbee, Bluetooth, and cellular mobile networks. It is also possible to use utility power lines to transmit monitoring data. The Internet Of Things is a major part of continuing advances in monitoring technology.

Order now our energy monitoring system from the extensive assortment on our website. Compare from different manufacturers, always at affordable prices.

Smart home automation and control systems alert users to remotely engage in energy efficiency measures, like heating and cooling, washing machine operation, battery storage, and EV charging. The systems include an analysis of the utility’s most expensive and cheapest electricity rates and helps users program home operation for optimal energy charge savings, and of course, this can be linked with residential solar power generation.

Utilities are rapidly becoming heavy users of detailed solar monitoring data, including the manipulation of aggregated smart meter data throughout distributed photo voltaic power networks to help stabilize the grid during peak hours. This new real-time relationship between generators, distributors and consumers (large and small) is helping to optimize the construction of new electrical energy capacity.

Solar-powered microgrids are also permitting communities, large buildings and campuses to operate largely autonomously. With new energy storage systems becoming available microgrids that support emergency services, for example, can switch to back-up power instantly so that critical systems remain operational.

Better design paired with detailed monitoring
The upshot of all this new technology is that overall photo voltaic energy plant performance Ratios are climbing at the same time that module prices continue to fall. Better design, paired with detailed monitoring, contribute to photo voltaic energy becoming more and more cost-competitive with other power sources. The future is looking sunny.

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2019 年 9 月 30 日  星期一   晴天


三個測試,自我檢查,頭皮受傷? 分類: 未分類

你珍惜每英寸的皮膚。但是頭皮怎麼辦?你有沒有把能量倒在你的頭發後面的頭皮上?事實上,頭發的狀態在很大程度上取決於它的基礎-頭皮。當你盡力為三千人煩惱時,你應該考慮把頭發護理焦點延伸到頭皮上。

測試1:緊張時頭皮的程度

方法:張開手指,盡量抱緊整個頭部,盡量前後移動頭皮,在鏡子中觀察面部輪廓是否被擠壓。

解釋:如果你發現頭皮難以移動,面部特征沒有被壓縮,這意味著由於壓力,你的頭皮已經太緊了。

提示:這是最容易被忽視的頭皮問題,當頭皮緊張時,毛孔會很緊,使頭發得不到營養而脫落。如果這種緊張狀態持續下去,頭皮不休息,毛囊總是收縮緊密,新發不會生長,導致脫發,頭痛和面部線條可能是其衍生物。

測試2:頭皮毛孔

方法:觀察頭皮毛孔的健康狀況通常很困難。建議我們去專業美發沙龍通過儀器測試。

不少人有頭皮屑、頭皮臭味和頭皮毛囊發炎等問題,真髮重生中心所提供的產品和頭髮護理服務主要改善頭皮毛囊健康、淨化毛囊和增強髮囊內的細胞功能,以固本培元的方式修護髮絲,令客人重拾強健髮質和頭皮,不再受各種頭髮問題困擾。

解釋:健康的毛孔看起來像幹淨的小凹槽,長出2-4根頭發。當頭皮壓力大,代謝不良時,油水可能不平衡,根部會有明顯的油脂。

小貼士:不要以為毛囊油是天生的。你的情緒和飲食會反映在這個小小的頭皮毛孔上。如果長期循環不良,會加速毛囊角化,使頭發變白,頭發會減少。

測試3:頭皮屑

方式:清晰可見頭皮的頭皮屑是最難以忽視的問題。

解釋:如果頭皮幹燥或中性,頭皮屑會脫落;如果是油性的,頭皮屑會聚集在頭皮上。

提示頭皮屑常伴有頭皮瘙癢。瘙癢引起的瘙癢會進一步損害頭部皮膚,加重頭皮屑脫落,越來越令人尷尬。

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2019 年 9 月 12 日  星期四   晴天


劉海總是出油怎么辦? 分類: 未分類

油膩的劉海真的很難看,你還在等什么?看看劉海爾的油的關鍵,然後開出正確的藥物!

一、選控油洗發水

洗發水似乎不是什么大問題,有些女孩會在超市家媔R瓶,不管它有什么效果,都可以洗頭就行了,這個主意絕對是不可能的!幹燥,烘焙油,滋養型。當然,分類洗發水是有原因的。頭發油應該容易選擇含有含油成分的洗發水來處理,然後用護發素為發尖做滋養護理,避免幹性頭發粗糙。

第二,不要經常用手碰劉海

有時候你可能沒有注意到你有一些壞習慣,比如經常下意識地用你的手接觸劉海,因為我們的手會被油汙和灰塵汙染,接觸劉海會粘在頭發上,造成劉海中油汙的情況,劉海會觸碰前額,甚至導致粉刺,所以限制你的手。

如果你有掉髮、頭髮稀疏、頭髮薄、髮線上移等問題,你需要一個專業及有效的頭皮治療療程。真髮重生中心是港澳首間引入韓式科研技術,提供非入侵性手術的生髮及護髮專利科技,讓顧客可以於舒適的治療中享受專業有效的生髮護髮效果。

第三,充分利用面部吸墨紙

如上所述,頭發上的油脂接觸額頭,會引起粉刺。如果前額皮膚上的油脂分泌旺盛,沾在頭發上,也會使頭發發亮!因此,要做好面部吸油工作,一定要把吸油紙放在包堙A並不時用蘸油的方法擦拭額頭,這樣才能保持面部和劉海的幹淨清爽。

第四,用發飾遮住

如果劉海爾油膩到讓你難堪,那就用發飾把劉海區的頭發收起來,發夾、發帶和發帶都是適用的,但一旦你把劉海分開,今天就得堅持露水,沒有機會把劉海爾放下。

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